Improving reflexive surfaces efficiency with genetic algorithms
01 Mar 2023-Journal of Instrumentation (Journal of Instrumentation)-Vol. 18, Iss: 03, pp P03008-P03008
TL;DR: In this article , a genetic algorithm was used to improve the efficiency of the ARAPUCA photodetector where the receiver's position is different from the classic parabolic antenna.
Abstract: We propose using a Genetic Algorithm to improve the efficiency of reflexive surfaces in devices where the receiver's position is different from the classic parabolic antenna. With this technique, we show that we can improve the efficiency of the ARAPUCA photodetector.
TL;DR: The analysis of recent advances in genetic algorithms is discussed and the well-known algorithms and their implementation are presented with their pros and cons with the aim of facilitating new researchers.
Abstract: In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching.
••01 Jan 2018
TL;DR: This chapter aims to review of all metaheuristics related issues by dividing metaheuristic algorithms according to metaphor based and non-metaphor based in order to differentiate between them in searching schemes and clarify how the metaphor based algorithms simulate the selected phenomenon behavior in the search area.
Abstract: Metaheuristic algorithms are computational intelligence paradigms especially used for sophisticated solving optimization problems. This chapter aims to review of all metaheuristics related issues. First, metaheuristic algorithms were divided according to metaphor based and non-metaphor based in order to differentiate between them in searching schemes and clarify how the metaphor based algorithms simulate the selected phenomenon behavior in the search area. The major algorithms in each metaphor subcategory are discussed including: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Water Waves Optimization (WWO), Clonal Selection Algorithm (CLONALG), Chemical Reaction Optimization (CRO), Harmony Search (HS), Sine Cosine Algorithm (SCA), Simulated Annealing (SA), Teaching–Learning-Based Optimization (TLBO), League Championship Algorithm (LCA), and others. Also, some non-metaphor based metaheuristics are explained as Tabu Search (TS), Variable Neighborhood Search (VNS). Second, different variants of metaheuristics are categorized into improved metaheuristics, adaptive, hybridized metaheuristics. Also, various examples are discussed. Third, a real-time case study “Welded Beam Design Problem” is solved with 10 different metaheuristics and the experimental results are statistically analyzed with non-parametric Friedman test in order to estimate the different performance of metaheuristics. Finally, limitation and new trends of metaheuristics are discussed. Besides, the chapter is accompanied with literature survey of existing metaheuristics with references for more details.
TL;DR: In this paper, a photon trap is used for scintillation light detection in large Time Projection Chambers, where the ratio between the area of the active devices and the optical window can be adjusted.
Abstract: We present a totally innovative device for the detection of liquid argon scintillation light, that has been named ARAPUCA (Argon R&D Advanced Program at UniCAmp). It is composed of a passive light collector and of active devices. The latters are standard SiPMs that operate at liquid argon temperature, while the passive collector is based on a new technology, never explored in this field before. It is a photon trap, that allows to collect light with extremely high efficiency. The total detection efficiency of the device can be tuned by modifying the ratio between the area of the active devices (SiPM) and the area of the optical window. For example, it will allow to reach a detection efficiency at the level of 1% on a surface of 50 × 50 cm2 with an active coverage of 2 × 2 cm2 (two/three large area SiPM). It is also a cheap device, since the major part of its cost is represented by the active devices. For these reason this appears to be the ideal device for scintillation light detection in large Time Projection Chambers. With appropriate modifications it can be used also in next generation Dark Matter detectors.
TL;DR: This work reports on a new type of directional reflective surface consisting of an array of sub-wavelength Helmholtz resonators with varying internal coiled path lengths, which induce a reflection phase gradient along a planar acoustic meta-surface.
Abstract: Artificially designed acoustic meta-surfaces have the ability to manipulate sound energy to an extraordinary extent. Here, we report on a new type of directional reflective surface consisting of an array of sub-wavelength Helmholtz resonators with varying internal coiled path lengths, which induce a reflection phase gradient along a planar acoustic meta-surface. The acoustically reshaped reflective surface created by the gradient-impeding meta-surface yields a distinct focal line similar to a parabolic cylinder antenna, and is used for directive sound beamforming. Focused beam steering can be also obtained by repositioning the source (or receiver) off axis, i.e., displaced from the focal line. Besides flat reflective surfaces, complex surfaces such as convex or conformal shapes may be used for sound beamforming, thus facilitating easy application in sound reinforcement systems. Therefore, directional reflective surfaces have promising applications in fields such as acoustic imaging, sonic weaponry, and underwater communication.
TL;DR: A genetic algorithm with hierarchically structured population to solve unconstrained optimization problems is applied and indicates that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success.