Structural design using multi-objective metaheuristics. Comparative study and application to a real-world problem

Many structural design problems in the field of civil engineering are naturally multi-criteria, i.e., they have several conflicting objectives that have to be optimized simultaneously. An example is when we aim to reduce the weight of a structure while enhancing its robustness. There is no a single solution to these types of problems, but rather a set of designs representing trade-offs among the conflicting objectives. This paper focuses on the application of multi-objective metaheuristics to solve two variants of a real-world structural design problem. The goal is to compare a representative set of state-of-the-art multi-objective metaheuristic algorithms aiming to provide civil engineers with hints as to what optimization techniques to use when facing similar problems as those selected in the study presented in this paper. Accordingly, our study reveals that MOCell, a cellular genetic algorithm, provides the best overall performance, while NSGA-II, the de facto standard multi-objective metaheuristic technique, also demonstrates a competitive behavior.     

Imaging with low-voltage scanning transmission electron microscopy: a quantitative analysis

A dedicated specimen holder has been designed to perform low-voltage scanning transmission electron microscopy in dark field mode. Different test samples, namely InGaAs/GaAs quantum wells, InGaAs nanowires and thick InGaAs layers, have been analysed to test the reliability of the model based on the proportionality to the specimen mass-thickness, generally used for image intensity interpretation of scattering contrast processes. We found that size of the probe, absorption and channelling must be taken into account to give a quantitative interpretation of image intensity. We develop a simple procedure to evaluate the probe-size effect and to obtain a quantitative indication of the absorption coefficient. Possible artefacts induced by channelling are pointed out. With the developed procedure, the low voltage approach can be successfully applied for quantitative compositional analysis. The method is then applied to the estimation of the In content in the core of InGaAs/GaAs core-shell nanowires.     

Flow measurements in sewers based on image analysis: automatic flow velocity algorithm

Discharges of combined sewer overflows (CSOs) and stormwater are recognized as an important source of environmental contamination. However, the harsh sewer environment and particular hydraulic conditions during rain events reduce the reliability of traditional flow measurement probes. An in situ system for sewer water flow monitoring based on video images was evaluated. Algorithms to determine water velocities were developed based on image-processing techniques. The image-based water velocity algorithm identifies surface features and measures their positions with respect to real world coordinates. A web-based user interface and a three-tier system architecture enable remote configuration of the cameras and the image-processing algorithms in order to calculate automatically flow velocity on-line. Results of investigations conducted in a CSO are presented. The system was found to measure reliably water velocities, thereby providing the means to understand particular hydraulic behaviors.     

Samplinghelper a web-based tool to assess the reliability of sampling strategies in sewers and receiving waters

Sampling is a key step in the analysis of chemical compounds. It is particularly important in the environmental field, for example for wastewater effluents, wet-weather discharges or streams in which the flows and concentrations vary greatly over time. In contrast to the improvements that have occurred in analytical measurement, developments in the field of sampling are less active. However, sampling errors may exceed by an order of magnitude those related to analytical processes. We proposed an Internet-based application based on a sampling theory to identify and quantify the errors in the process of taking samples. This general theory of sampling, already applied to different areas, helps to answer questions related to the number of samples, their volume, their representativeness, etc. The use of the internet to host this application facilitates use of theoretical tools and raise awareness of the uncertainties related to sampling. An example is presented, which highlights the importance of the sampling step in the quality of analytical results.     

Harvesting light with transformation optics

Transformation optics （TO） is a new tool for controlling electromagnetic fields. In the context of metamaterial technology, it provides a direct link between a desired electromagnetic （EM） phenomenon and the material response required for its occurrence. Recently, this powerful framework has been successfully exploited to study surface plasmon assisted phenomena such as light harvesting. Here, we review the general strategy based on TO to design plasmonic devices capable of harvesting light over a broadband spectrum and achieving considerable field confinement and enhancement. The methodology starts with two-dimensional （2D） cases, such as 2D metal edges, crescent-shaped cylinders, nanowire dimers, and rough metal surfaces, and is well extended to fully-fledged three-dimensional （3D） situations. The largely analytic approach gives physical insights into the processes involved and suggests a way forward to study a wide variety of plasmonic nanostructures.