Variable-fidelity electromagnetic simulations and co-kriging for accurate modeling of antennas

Accurate and fast models are indispensable in contemporary antenna design. In this paper, we describe the low-cost antenna modeling methodology involving variable-fidelity electromagnetic (EM) simulations and co-Kriging. Our approach exploits sparsely sampled accurate (high-fidelity) EM data as well as densely sampled coarse-discretization (low-fidelity) EM simulations that are accommodated into one model using the co-Kriging technique. By using coarse-discretization simulations, the computational cost of creating the antenna model is greatly reduced compared to conventional approaches, where high-fidelity simulations are directly used to set up the model. At the same time, the modeling accuracy is not compromised. The proposed technique is demonstrated using three examples of antenna structures. Comparisons with conventional modeling based on high-fidelity data approximation, as well as applications for antenna design, are also discussed

Multi-objective design of antenna structures using variable-fidelity EM simulations and co-kriging

A methodology for low-cost multi-objective design of antenna structures is proposed. To reduce the computational effort of the design process the initial Pareto front is obtained by optimizing the response surface approximation (RSA) model obtained from low-fidelity EM simulations of the antenna structure of interest. The front is further refined by iterative incorporation of a limited number of high-fidelity training points into the RSA surrogate using co-kriging. Our considerations are illustrated using two examples of antenna structure

Fast design optimization of UWB antenna with WLAN Band-Notch

In this paper, a methodology for rapid design optimization of an ultra-wideband ( UWB) monopole antenna with a lower WLAN band-notch is presented. The band-notch is realized using an open loop resonator implemented in the radiation patch of the antenna. Design optimization is a two stage process, with the first stage focused on the design of the antenna itself, and the second stage aiming at identification of the appropriate dimensions of the resonator with the purpose of allocating the band-notch in the desired frequency range. Both optimization stages are realized using surrogate-based optimization involving variable-fidelity electromagnetic ( EM) simulation models as well as an additive response correction ( first stage), and sequential approximate optimization ( second stage). The final antenna design is obtained at the CPU cost corresponding to only 23 high-fidelity EM antenna simulations

Birth Order and BMI in Teenage Girls

The goal of this study was to investigate the relation of birth order to relative weight and prevalence of obesity in a group of 13–15 years old girls. In 1997, 1458 girls were examined. The height and weight measured by trained staff were recorded. Family size and birth order were obtained by a questionnaire. For the purpose of the present study, 776 and 250 girls coming from two- and three-child full families, respectively, were selected from the total sample on the basis of complete information. The Body Mass Index (kg/m2) was adjusted to reference US population (NCHS) by means of the LMS parameters. Prevalence of overweight and obesity was defined according to recommendation of the International Obesity Task Force. The effect of birth order on BMI was tested by one-way analysis of variance. Prevalence of obesity was tested by the means of Pearson chi-square. First and second born girls from two-sibling families did not show significant differences in average standardized BMI. Relative weight significantly differs among girls coming from three sibling families, decreasing along with the birth order. The first-born girls were 1.5 times at higher risk of obesity in comparison to later- born girls. Differences in the proportion of overweight girls among birth order groups showed a high significance within three sibling families

Multicolour photometry of Balloon 090100001: linking the two classes of pulsating hot subdwarfs

We present results of the multicolour UBVR photometry of the high-amplitude EC14026-type star, Balloon 090100001. The data span over a month and consist of more than a hundred hours of observations. Fourier analysis of these data led us to the detection of at least 30 modes of pulsation of which 22 are independent. The frequencies of 13 detected modes group in three narrow ranges, around 2.8, 3.8 and 4.7 mHz, where the radial fundamental mode, the first and second overtones are likely to occur. Surprisingly, we also detect 9 independent modes in the low-frequency domain, between 0.15 and 0.4 mHz. These modes are typical for pulsations found in PG1716+426-type stars, discovered recently among cool B-type subdwarfs. The modes found in these stars are attributed to the high-order g modes. As both kinds of pulsations are observed in Balloon 090100001, it represents a link between the two classes of pulsating hot subdwarfs. At present, it is probably the most suitable target for testing evolutionary scenarios and internal constitution models of these stars by means of asteroseismology. Three of the modes we discovered form an equidistant frequency triplet which can be explained by invoking rotational splitting of an $\ell$ = 1 mode. The splitting amounts to about 1.58 $\mu$Hz, leading to a rotation period of 7.1 $\pm$ 0.1 days.Comment: 12 pages, 14 figures, accepted for publication in MNRAS. For full-resolution postscript file, visit http://www.as.wsp.krakow.pl/~andy/balloon.ps.g

A warped kernel improving robustness in Bayesian optimization via random embeddings

This works extends the Random Embedding Bayesian Optimization approach by integrating a warping of the high dimensional subspace within the covariance kernel. The proposed warping, that relies on elementary geometric considerations, allows mitigating the drawbacks of the high extrinsic dimensionality while avoiding the algorithm to evaluate points giving redundant information. It also alleviates constraints on bound selection for the embedded domain, thus improving the robustness, as illustrated with a test case with 25 variables and intrinsic dimension 6

Cost-efficient modeling of antenna structures using Gradient Enhanced Kriging

Reliable yet fast surrogate models are indispensable in the design of contemporary antenna structures. Data-driven models, e.g., based on Gaussian Processes or support-vector regression, offer sufficient flexibility and speed, however, their setup cost is large and grows very quickly with the dimensionality of the design space. In this paper, we propose cost-efficient modeling of antenna structures using Gradient-Enhanced Kriging. In our approach, the training data set contains, apart from the EM-simulation responses of the structure at hand, also derivative data at the respective training locations obtained at little extra cost using adjoint sensitivity techniques. We demonstrate that introduction of the derivative information into the model allows for considerable reduction of the model setup cost (in terms of the number of training points required) without compromising its predictive power. The Gradient-Enhanced Kriging technique is illustrated using a dielectric resonator antenna structure. Comparison with conventional Kriging interpolation is also provided