High-efficiency, radiation-resistant GaAs space cells

Although many GaAs solar cells are intended for space applicatons, few measurements of cell degradation after radiation are available, particularly for cells with efficiencies exceeding 20 percent (one-sun, AMO). Often the cell performance is optimized for the highest beginning-of-life (BOL) efficiency, despite the unknown effect of such design on end-of-life (EOL) efficiencies. The results of a study of the radiation effects on p-n GaAs cells are presented. The EOL efficiency of GaAs space cell can be increased by adjusting materials growth parameters, resulting in a demonstration of 16 percent EOL efficiency at one-sun, AMO. Reducing base doping levels to below 3 x 10(exp 17)/cu m and decreasing emitter thickness to 0.3 to 0.5 micron for p-n cells led to significant improvements in radiation hardness as measured by EOL/BOL efficiency ratios for irradiation of 10(exp -15)/sq cm electrons at 1 MeV. BOL efficiency was not affected by changes in emitter thickness but did improve with lower base doping

High-efficiency GaAs concentrator space cells

High efficiency Al sub x Ga sub 1-x As/GaAs heteroface solar concentrator cells have been developed for space applications. The cells, which were grown using metalorganic chemical vapor deposition (MOCVD), have been fabricated in both the p-n and n-p configurations. Magnesium and zinc are used as the p-type dopants, and Se is used as the n-type dopant. The space cells, which are designed for use in a Cassegrainian concentrator operating at 100 suns, AMO, have a circular illuminated area 4 mm in diameter on a 5 mm by 5 mm cell. These cells have exhibited flash-tested efficiencies as high as 23.6 percent at 28 C and 21.6 percent at 80 C

High-efficiency AlGaAs-GaAs Cassegrainian concentrator cells

AlGaAs-GaAs heteroface space concentrator solar cells have been fabricated by metalorganic chemical vapor deposition. AMO efficiencies as high as 21.1% have been observed both for p-n and np structures under concentration (90 to 100X) at 25 C. Both cell structures are characterized by high quantum efficiencies and their performances are close to those predicted by a realistic computer model. In agreement with the computer model, the n-p cell exhibits a higher short-circuit current density

Structural Design of Intelligent Wind Turbine Rotor Blades

The aim of the present master thesis is to investigate concepts of structural designs of wind turbine rotor blades, which should result into a load reduction. This load reduction should lead to larger rotor diameters being feasible for wind turbines, or existing blades being produced more cost-effectively by reducing the weight of the blade. With the help of automated processes, the structural models are constructed using a reference rotor blade and then the associated loads are simulated. The resulting loads and masses of the different concepts are compared with those of the reference rotor blade. The results show that both a structural design with a c-beam and a structural design with a swept beam leads to a load reduction. Another concept based on the use of an active trailing edge flap can only be evaluated using reference loads. This shows a significant increase in weight, which must be absorbed by a load reduction through the flap

Convolutional Neural Networks for Apnea Detection from Smartphone Audio Signals: Effect of Window Size

Although sleep apnea is one of the most prevalent sleep disorders, most patients remain undiagnosed and untreated. The gold standard for sleep apnea diagnosis, polysomnography, has important limitations such as its high cost and complexity. This leads to a growing need for novel cost-effective systems. Mobile health tools and deep learning algorithms are nowadays being proposed as innovative solutions for automatic apnea detection. In this work, a convolutional neural network (CNN) is trained for the identification of apnea events from the spectrograms of audio signals recorded with a smartphone. A systematic comparison of the effect of different window sizes on the model performance is provided. According to the results, the best models are obtained with 60 s windows (sensitivity-0.72, specilicity-0.89, AUROC = 0.88), For smaller windows, the model performance can be negatively impacted, because the windows become shorter than most apnea events, by which sound reductions can no longer be appreciated. On the other hand, longer windows tend to include multiple or mixed events, that will confound the model. This careful trade-off demonstrates the importance of selecting a proper window size to obtain models with adequate predictive power. This paper shows that CNNs applied to smartphone audio signals can facilitate sleep apnea detection in a realistic setting and is a first step towards an automated method to assist sleep technicians. Clinical Relevance- The results show the effect of the window size on the predictive power of CNNs for apnea detection. Furthermore, the potential of smartphones, audio signals, and deep neural networks for automatic sleep apnea screening is demonstrated

Recent advancements in monolithic AlGaAs/GaAs solar cells for space applications

High efficiency, two terminal, multijunction AlGaAs/GaAs solar cells were reproducibly made with areas of 0.5 sq cm. The multiple layers in the cells were grown by Organo Metallic Vapor Phase Epitaxy (OMVPE) on GaAs substrates in the n-p configuration. The upper AlGaAs cell has a bandgap of 1.93 eV and is connected in series to the lower GaAs cell (1.4 eV) via a metal interconnect deposited during post-growth processing. A prismatic coverglass is installed on top of the cell to reduce obscuration caused by the gridlines. The best 0.5 sq cm cell has a two terminal efficiency of 23.0 pct. at 1 sun, air mass zero (AM0) and 25 C. To date, over 300 of these cells were grown and processed for a manufacturing demonstration. Yield and efficiency data for this demonstration are presented. As a first step toward the goal of a 30 pct. efficient cell, a mechanical stack of the 0.5 sq cm cells described above, and InGaAsP (0.95 eV) solar cells was made. The best two terminal measurement to date yields an efficiency of 25.2 pct. AM0. This is the highest reported efficiency of any two terminal, 1 sun space solar cell

IA-GPS : uma ferramenta baseada em algoritmos de busca para alocação de equipes em projetos de software

The planning of a large project involves many variables, uncertainties and conflicting objectives, being a very complex task. Given that the manual process may lead to low quality solutions, recently some papers have proposed the use of Artificial Intelligence algorithms, in particular metaheuristics, to help the software project manager in the planning task. This form of modeling falls within the scope of Search-Based Software Engineering and the planning problem addressed in this work is known as Software Project Scheduling Problem whose goal is to allocate employees to project tasks, in order to optimize project cost and duration. This work presents IA-GPS, an application integrated with jMetal that simplifies the use of heuristic algorithms, providing a more user-friendly interface for software engineers to analyse the possible solutions for the problem, generated by the algorithms. IA-GPS provides managers with possible employee allocations for tasks and timelines, which can be viewed in a variety of ways. The application was developed in Java and was validated with synthetic case studies, extracted from the literature.O planejamento de um grande projeto envolve muitas variáveis, incertezas e objetivos conflitantes, sendo assim uma tarefa muito complexa. Dado que o processo manual pode incorrer em soluções de baixa qualidade, recentemente alguns trabalhos propuseram a utilização de algoritmos de Inteligência Artificial, em particular, meta-heurísticas, para ajudar o gerente de projeto de software na tarefa de planejamento. Esta forma de modelagem insere-se no âmbito da Engenharia de Software Baseada em Busca e o problema de planejamento tratado neste trabalho é conhecido como Problema do Escalonamento e Atribuição de Tarefas em Projetos de Software, o qual objetiva alocar funcionários a tarefas, de forma a otimizar o custo e a duração do projeto. Este trabalho apresenta a IA-GPS, uma aplicação integrada ao framework jMetal que simplifica a utilização de algoritmos heurísticos, provendo uma interface mais amigável para os engenheiros de software analisarem as possíveis soluções geradas para o problema. A IA-GPS fornece aos gerentes possíveis alocações de funcionários a tarefas e cronogramas, os quais podem ser visualizados de diversas formas. A aplicação foi desenvolvida em Java e foi validada com estudos de caso sintéticos, extraídos da literatura.São Cristóvão, S

The 25 percent-efficient GaAs Cassegrainian concentrator cell

Very high-efficiency GaAs Cassegrainian solar cells have been fabricated in both the n-p and p-n configurations. The n-p configuration exhibits the highest efficiency at concentration, the best cells having an efficiency eta of 24.5 percent (100X, AM0, temperature T = 28 C). Although the cells are designed for operation at this concentration, peak efficiency is observed near 300 suns (eta = 25.1 percent). To our knowledge, this is the highest reported solar cell efficiency for space applications. The improvement in efficiency over that reported at the previous SPRAT conference is attributed primarily to lower series resistance and improved grid-line plating procedures. Using previously measured temperature coefficients, researchers estimate that the n-p GaAs cells should deliver approximately 22.5 percent efficiency at the operating conditions of 100 suns and T = 80 C. This performance exceeds the NASA program goal of 22 percent for the Cassegrainian cell. One hundred Cassegrainian cells have been sent to NASA as deliverables, sixty-eight in the n-p configuration and thirty-two in the p-n configuration