This article presents an overview of 3-D-printed microwave and millimeter-wave components integrating gallium-based (Ga-based) liquid metal (LM). The LM is considered here as a fourth degree of freedom for the design of 3-D-printed antennas, filters, and wireless sensors. The 3-D printing combined with LM technology can be considered as a 4-D printing technology. It can benefit from the advantages offered by 3-D printing technologies (low cost and fast manufacturing) and LM at room temperature (flexibility and reconfigurability). To date, in microwave and millimeter-wave applications, 4-D printing technology is mainly used to achieve the metallization and/or reconfigurability and/or mechanical flexibility of high-frequency 3-D-printed components.

This article reports the yield estimation of vineyards from using a mobile millimeter-wave radar system. The proximal radar sensor is a 122-GHz FM-CW radar mounted on a rover that moves along the furrows between vine plants. The proposed yield estimation is based on the classification of radar echoes measured for various grape varieties, for different meteorological conditions, and at different stages of grape development. As yield estimation errors are found to be lower than 10%, the proposed radar technique is suitable for precision viticulture applications.

In this paper, we report the accurate estimation of vine grape yield from a 3-D radar imagery technique. Three ground-based frequency-modulated continuous-wave radars operating, respectively, at 24, 77, and 122 GHz are used for the contact-less estimation of grape mass in vineyards. The 3-D radar images are built from the beam scanning of the vine plants and allow estimating the mass of grapes from the computation of appropriate statistical estimators. These estimators are derived from the measured polarization and magnitude of radar echoes. It is shown that the estimation of grape mass from the proposed ground-based radar imagery technique at millimeter-wave frequency range may be accurate within 1%.

Summary This paper deals with the parallel computing and computation time prediction applied to computational electromagnetics based on rigorous methods for large and complex structures, such as tunnels and airplane cabins. The main objective of this work is represented by the electromagnetic computation of an airplane cabin in order to characterize the propagation channel for a given frequency inside the structure. A well‐known three‐dimensional numerical method, transmission‐line matrix, is adopted for this work. Transmission‐line matrix modelling method is applied to volumes, using the symmetrical condensed node. The planar structures are modelled with the mode matching approach. In order to analyse the electromagnetic field at high frequencies inside large structures as an airplane cabin, the transmission‐line matrix mesh step is very small compared with the size of the physical structure. Thus, the total amount of data that need to be processed exceeds the RAM memory presented on a traditional computing machine. The implementation of the parallel transmission‐line matrix algorithm is a viable solution to this problem taking full advantage of the parallel and distributed architectures, as clusters, grids and supercomputers. The results prove the benefits of the grid computing and supercomputer environments to solve electrically large structures. The parallel hybrid approach, based on Message Passing Interface, is designed for Single Programme Multiple Data programming model. The study highlights the role of parallelization scheme, grid versus supercomputer, with respect to the size of the problem and its repartition. In order to access the computing resources available on different parallel computing platforms, users need to respect a charter containing time and resource number restrictions when doing reservations. So, a time prediction model based on the profile of the transmission‐line matrix algorithm has been developed to allow safe reservations of the computing nodes on grid environment. To have a good agreement between the measured and the predicted values for the computation time, the problem of the cache misses appearing during the simulation has been considered in the profile‐based prediction model of the transmission‐line matrix/modal hybrid application, according to the processor cache memory size. The maximum error for the estimated values of the computation times is about 6.09%. The relevance of this work is based on the fact that is given a complete tool to deal with the large electromagnetic structures: a parallel transmission‐line matrix implementation to take the advantage of the distributed architectures and a time prediction model in order to optimize the resource reservation and the simulation execution on the computing nodes. Copyright © 2014 John Wiley & Sons, Ltd.

The heterogeneous nature of distributed platforms such as computational Grids is one of the main barriers to effectively deploy tightly-coupled applications. For those applications, one common problem that appears due to the hardware heterogeneity is the load imbalance which slows down the application to the pace of the slower processor. One solution is to distribute the load adequately taking into account hardware capacities. To do so, an estimation of the hardware capacities for running the application has to be obtained. In this paper, we present a static load balancing for iterative tightly-coupled applications based on a profile prediction model. This technique is presented as a successful example of the interaction between experiment management tools and parallel applications. The experiment management tool Expo is used that enabled to: (1) provide a general, lightweight and descriptive way to capture the tuning and deployment of a parallel application in a computing infrastructure, (2) perform the tuning of the application efficiently in terms of human effort and resources needed. This paper reports the costs for carrying out the tuning of a large electromagnetic simulation based on TLM for the platform Grid'5000 and the improvements obtained on the total execution time of the application.