scholarly journals Multiple Solutions Starting from Real Shaped Beams in Equispaced Linear Arrays

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 62
Author(s):  
Aarón Ángel Salas-Sánchez ◽  
Camilo López-Castro ◽  
Paolo Rocca ◽  
Juan Antonio Rodríguez-González ◽  
María Elena López-Martín ◽  
...  
Keyword(s):  
Multiple Solutions ◽  
Space Vehicle ◽  
Linear Arrays ◽  
Resonant Structures ◽  
Planar Arrays ◽  
Half Wavelength ◽  
Standard Linear ◽  
Beam Patterns ◽  
Flat Top Beam

In the present work, the theoretical basis of the multiplicity of solutions obtained from an initial real symmetric distribution is derived. This initial solution is devoted to generating an equivalent pure real shaped-beam pattern for a concrete synthesis scenario. However, these new solutions are not based on real symmetric distributions; hence, not based on the generation of pure real patterns. The bandwidth performances and tolerance to errors provided by the multiple solutions in the array design are analyzed by considering different architectures, also including mutual coupling models and element factor expressions due to accuracy purposes. In addition, a technique to obtain efficient linear arrays by designing resonant structures is addressed. Examples involving both standard linear arrays of half-wavelength cylindrical dipoles and resonant linear arrays generating flat-top beam patterns are reported and discussed. Additionally, an extension to planar arrays performed by means of a generalisation of the Baklanov transformation through collapsed distribution techniques inspired in the well-known method devised by Tseng and Cheng is performed. In such a way, an analysis of the quality of solutions for generating circular and elliptical footprints with controlled both SLL and ripple which are highly interesting in the framework of space vehicle applications.

scholarly journals Thermos Array: Two-Dimensional Sparse Array with Reduced Mutual Coupling

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Lei Sun ◽  
Minglei Yang ◽  
Baixiao Chen
Keyword(s):  
Closed Form ◽  
Degrees Of Freedom ◽  
Mutual Coupling ◽  
Doa Estimation ◽  
Two Dimensional ◽  
Spatial Smoothing ◽  
Planar Arrays ◽  
Half Wavelength ◽  
Planar Array ◽  
Small Spacing

Sparse planar arrays, such as the billboard array, the open box array, and the two-dimensional nested array, have drawn lots of interest owing to their ability of two-dimensional angle estimation. Unfortunately, these arrays often suffer from mutual-coupling problems due to the large number of sensor pairs with small spacing d (usually equal to a half wavelength), which will degrade the performance of direction of arrival (DOA) estimation. Recently, the two-dimensional half-open box array and the hourglass array are proposed to reduce the mutual coupling. But both of them still have many sensor pairs with small spacing d, which implies that the reduction of mutual coupling is still limited. In this paper, we propose a new sparse planar array which has fewer number of sensor pairs with small spacing d. It is named as the thermos array because its shape seems like a thermos. Although the resulting difference coarray (DCA) of the thermos array is not hole-free, a large filled rectangular part in the DCA can be facilitated to perform spatial-smoothing-based DOA estimation. Moreover, it enjoys closed-form expressions for the sensor locations and the number of available degrees of freedom. Simulations show that the thermos array can achieve better DOA estimation performance than the hourglass array in the presence of mutual coupling, which indicates that our thermos array is more robust to the mutual-coupling array.

scholarly journals The Neural Network Assisted Land Use Regression

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 452
Author(s):  
Jan Bitta ◽  
Vladislav Svozilík ◽  
Aneta Svozilíková Krakovská
Keyword(s):  
Neural Network ◽  
Land Use ◽  
Linear Regression ◽  
Dispersion Model ◽  
Land Use Regression ◽  
Emission Data ◽  
Pollution Dispersion ◽  
Factors Affecting ◽  
Standard Linear

Land Use Regression (LUR) is one of the air quality assessment modelling techniques. Its advantages lie mainly in a much simpler mathematical apparatus, quicker and simpler calculations, and a possibility to incorporate more factors affecting pollutant concentration than standard dispersion models. The goal of the study was to perform the LUR model in the Polish-Czech-Slovakian Tritia region, to test two sets of pollution data input factors, i.e., factors based on emission data and pollution dispersion model results, to test regression via neural networks and compare it with standard linear regression. Both input datasets, emission data and pollution dispersion model results, provided a similar quality of results in the case when standard linear regression was used, the R2 of the models was 0.639 and 0.652. Neural network regression provided a significantly higher quality of the models, their R2 was 0.937 and 0.938 for the factors based on emission data and pollution dispersion model results respectively.

scholarly journals Dream Machine

2007 ◽  
Vol 129 (06) ◽  
pp. 36-39
Author(s):  
Jeffrey Winters
Keyword(s):  
High Efficiency ◽  
Fuel Efficiency ◽  
Space Vehicle ◽  
Gasoline Prices ◽  
Group Setting ◽  
Private Company ◽  
Safety Standards ◽  
Physical Attributes ◽  
Important Objective

This article discusses features of a high-efficiency car. The group setting up the contest, the X Prize Foundation, used a cash prize to lure a private company to launch its own space vehicle. Automakers have been better at producing high-efficiency concepts, such as the Chevy Volt than actual high-mileage cars. After the success of the Ansari X Prize, the directors of the X Prize Foundation looked for other fields in need of a push. In an era of rising gasoline prices and stagnant fuel efficiency marks, the idea of setting up a prize for a highly fuel-efficient vehicle was a natural. The contest tests vehicles on several factors, not just the single metric of fuel economy. The eventual winner of the Automotive X Prize will be much different. For starters, the car must meet federal safety standards and will be judged on physical attributes such as exterior styling, interior comfort, and the quality of the workmanship. According to the managers of the competition, the most important objective of the Automotive X Prize is to encourage not only the mainstream industry but also people on the periphery to really layout on the table some strong ideas.

Multiobjective Optimization of Bioethanol Production via Hydrolysis Using Hopfield-Enhanced Differential Evolution

2014 ◽  
pp. 340-359 ◽  
Author(s):  
T. Ganesan ◽  
I. Elamvazuthi ◽  
K. Z. K. Shaari ◽  
P. Vasant
Keyword(s):  
Differential Evolution ◽  
Multiple Solutions ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Gravitational Search Algorithm ◽  
Pareto Frontier ◽  
Weighted Sum ◽  
Bioethanol Production ◽  
Hypervolume Indicator

Many industrial problems in process optimization are Multi-Objective (MO), where each of the objectives represents different facets of the issue. Thus, having in hand multiple solutions prior to selecting the best solution is a seminal advantage. In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). These methods are then employed to trace the approximate Pareto frontier to the bioethanol production problem. The Hypervolume Indicator (HVI) is applied to gauge the capabilities of each algorithm in approximating the Pareto frontier. Some comparative studies are then carried out with the algorithms developed in this chapter. Analysis on the performance as well as the quality of the solutions obtained by these algorithms is shown here.

scholarly journals Insights into Acoustically Induced PiezoLuminescence: The Visualization of Ultrasonic Beam Patterns

Proceedings ◽  
2018 ◽  
Vol 2 (8) ◽  
pp. 491
Author(s):  
Simon Michels ◽  
Mathias Kersemans ◽  
Guillaume Lajoinie ◽  
Michel Versluis ◽  
Philippe F. Smet
Keyword(s):  
Ultrasonic Transducers ◽  
Non Destructive Testing ◽  
Ultrasonic Beam ◽  
Destructive Testing ◽  
Full Field ◽  
Ultrasound Field ◽  
Non Destructive ◽  
Beam Patterns ◽  
Ultrasonic Investigation

Ultrasonic transducers are used in many fields of application, including medical imaging/treatment, non-destructive testing and material characterization. To assure the quality of the ultrasonic investigation transducers require regular checks for possible deterioration and accurate calibration. Current methods rely on point-by-point scanning of the ultrasound field with a needle hydrophone, which is expensive and time consuming. Recently, we have developed a new concept, in which a fast full-field visualization of the radiation field is achieved through Acoustically induced PiezoLuminescence (APL). Here, we report on an improved ultrasonic beam visualization and provide further insights into the mechanism underlying APL and mechanoluminescence.

scholarly journals Multimodal trajectory optimization for motion planning

2020 ◽  
Vol 39 (8) ◽  
pp. 983-1001
Author(s):  
Takayuki Osa
Keyword(s):  
Motion Planning ◽  
Cost Function ◽  
Trajectory Optimization ◽  
Multiple Solutions ◽  
3D Space ◽  
Single Solution ◽  
Planning Methods ◽  
The Cost ◽  
2D And 3D

Existing motion planning methods often have two drawbacks: (1) goal configurations need to be specified by a user, and (2) only a single solution is generated under a given condition. In practice, multiple possible goal configurations exist to achieve a task. Although the choice of the goal configuration significantly affects the quality of the resulting trajectory, it is not trivial for a user to specify the optimal goal configuration. In addition, the objective function used in the trajectory optimization is often non-convex, and it can have multiple solutions that achieve comparable costs. In this study, we propose a framework that determines multiple trajectories that correspond to the different modes of the cost function. We reduce the problem of identifying the modes of the cost function to that of estimating the density induced by a distribution based on the cost function. The proposed framework enables users to select a preferable solution from multiple candidate trajectories, thereby making it easier to tune the cost function and obtain a satisfactory solution. We evaluated our proposed method with motion planning tasks in 2D and 3D space. Our experiments show that the proposed algorithm is capable of determining multiple solutions for those tasks.

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