Study of and design procedure for dual circularly polarized waveguide slot arrays

For the past sixty years, waveguide slot radiator arrays have played a critical role in microwave radar and communication systems. They feature a well-characterized antenna element capable of direct integration into a low-loss feed structure with highly developed and inexpensive manufacturing processes. Waveguide slot radiators comprise some of the highest performance—in terms of side-lobe-level, efficiency, etc. — antenna arrays ever constructed. A wealth of information is available in the open literature regarding design procedures for linearly polarized waveguide slots. By contrast, despite their presence in some of the earliest published reports, little has been presented to date on array designs for circularly polarized (CP) waveguide slots. Moreover, that which has been presented features a classic traveling wave, efficiency-reducing beam tilt. This work proposes a unique CP waveguide slot architecture which mitigates these problems and a thorough design procedure employing widely available, modern computational tools. The proposed array topology features simultaneous dual-CP operation with grating-lobe-free, broadside radiation, high aperture efficiency, and good return loss. A traditional X-Slot CP element is employed with the inclusion of a slow wave structure passive phase shifter to ensure broadside radiation without the need for performance-limiting dielectric loading. It is anticipated this technology will be advantageous for upcoming polarimetric radar and Ka-band SatCom systems. The presented design methodology represents a philosophical shift away from traditional waveguide slot radiator design practices. Rather than providing design curves and/or analytical expressions for equivalent circuit models, simple first-order design rules – generated via parametric studies — are presented with the understanding that device optimization and design will be carried out computationally. A unit-cell, S-parameter based approach provides a sufficient reduction of complexity to permit efficient, accurate device design with attention to realistic, application-specific mechanical tolerances. A transparent, start-to-finish example of the design procedure for a linear sub-array at X-Band is presented. Both unit cell and array performance is calculated via finite element method simulations. Results are confirmed via good agreement with finite difference, time domain calculations. Array performance exhibiting grating-lobe-free, broadside-scanned, dual-CP radiation with better than 20 dB return loss and over 75% aperture efficiency is presented.

Testing Wisconsin asphalt mixtures for the 2002 AASHTO mechanistic design procedure

There has been a continuous evolutionary process in asphalt pavement design. In the beginning it was crude and based on past experience. Through research, empirical methods were developed based on materials response to specific loading at the AASHO Road Test. Today, pavement design has progressed to a mechanistic-empirical method. This methodology takes into account the mechanical properties of the individual layers and uses empirical relationships to relate them to performance. The mechanical tests that are used as part of this methodology include dynamic modulus and flow number, which have been shown to correlate with field pavement performance. This thesis was based on a portion of a research project being conducted at Michigan Technological University (MTU) for the Wisconsin Department of Transportation (WisDOT). The global scope of this project dealt with the development of a library of values as they pertain to the mechanical properties of the asphalt pavement mixtures paved in Wisconsin. Additionally, a comparison with the current associated pavement design to that of the new AASHTO Design Guide was conducted. This thesis describes the development of the current pavement design methodology as well as the associated tests as part of a literature review. This report also details the materials that were sampled from field operations around the state of Wisconsin and their testing preparation and procedures. Testing was conducted on available round robin and three Wisconsin mixtures and the main results of the research were: The test history of the Superpave SPT (fatigue and permanent deformation dynamic modulus) does not affect the mean response for both dynamic modulus and flow number, but does increase the variability in the test results of the flow number. The method of specimen preparation, compacting to test geometry versus sawing/coring to test geometry, does not statistically appear to affect the intermediate and high temperature dynamic modulus and flow number test results. The 2002 AASHTO Design Guide simulations support the findings of the statistical analyses that the method of specimen preparation did not impact the performance of the HMA as a structural layer as predicted by the Design Guide software. The methodologies for determining the temperature-viscosity relationship as stipulated by Witczak are sensitive to the viscosity test temperatures employed. The increase in asphalt binder content by 0.3% was found to actually increase the dynamic modulus at the intermediate and high test temperature as well as flow number. This result was based the testing that was conducted and was contradictory to previous research and the hypothesis that was put forth for this thesis. This result should be used with caution and requires further review. Based on the limited results presented herein, the asphalt binder grade appears to have a greater impact on performance in the Superpave SPT than aggregate angularity. Dynamic modulus and flow number was shown to increase with traffic level (requiring an increase in aggregate angularity) and with a decrease in air voids and confirm the hypotheses regarding these two factors. Accumulated micro-strain at flow number as opposed to the use of flow number appeared to be a promising measure for comparing the quality of specimens within a specific mixture. At the current time the Design Guide and its associate software needs to be further improved prior to implementation by owner/agencies.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.