Diseño de máquina para ensayos de Creep, Creep-Fatiga y falla por carga sostenida.

El objetivo del presente trabajo es el diseño de una máquina para ensayos de Creep, con capacidad de aplicar carga variable. Se busca una máquina liviana, desmontable y fácilmente transportable entre laboratorios. El diseño de la máquina parte de una ingeniería básica, pasando por una etapa de detalle y finalizando en la fabricación y montaje de la misma. Se incluye en el diseño un sistema de adquisición y control de carga. Se diseñó y construyó una máquina accionada por resorte capaz de aplicar 5 kN. Se evalúa su respuesta ante distintos programas de carga. El control de carga es capaz de seguir referencias con evolución suave en el tiempo sin mayores dificultades y mantener la carga constante durante intervalos largos de tiempo. La adquisición de datos se realiza mediante un módulo QuantumX y transductores de desplazamiento y carga HBM.

Diseño de máquina para ensayos de Creep, Creep-Fatiga y falla por carga sostenida.

El objetivo del presente trabajo es el diseño de una máquina para ensayos de Creep, con capacidad de aplicar carga variable. Se busca una máquina liviana, desmontable y fácilmente transportable entre laboratorios. El diseño de la máquina parte de una ingeniería básica, pasando por una etapa de detalle y finalizando en la fabricación y montaje de la misma. Se incluye en el diseño un sistema de adquisición y control de carga. Se diseñó y construyó una máquina accionada por resorte capaz de aplicar 5 kN. Se evalúa su respuesta ante distintos programas de carga. El control de carga es capaz de seguir referencias con evolución suave en el tiempo sin mayores dificultades y mantener la carga constante durante intervalos largos de tiempo. La adquisición de datos se realiza mediante un módulo QuantumX y transductores de desplazamiento y carga HBM.

Development, implementation, and assessment of a distance module in endocrine physiology

Rangel EM, Mendes IA, Carnio EC, Marchi Alves LM, Godoy S, Crispim JA. Development, implementation, and assessment of a distance module in endocrine physiology. Adv Physiol Educ 34: 70-74, 2010; doi: 10.1152/advan.00070.2009.-This study aimed to develop, implement, and assess a distance module in endocrine physiology in TelEduc for undergraduate nursing students from a public university in Brazil, with a sample size of 44 students. Stage 1 consisted of the development of the module, through the process of creating a distance course by means of the Web. Stage 2 was the planning of the module's practical functioning, and stage 3 was the planning of student evaluations. In the experts' assessment, the module complied with pedagogical and technical requirements most of the time. In the practical functioning stage, 10 h were dedicated for on-site activities and 10 h for distance activities. Most students (93.2%) were women between 19 and 23 yr of age (75%). The internet was the most used means to remain updated for 23 students (59.0%), and 30 students (68.2%) accessed it from the teaching institution. A personal computer was used by 23 students (56.1%), and most of them (58.1%) learned to use it alone. Access to a forum was more dispersed (variation coefficient: 86.80%) than access to chat (variation coefficient: 65.14%). Average participation was 30 students in forums and 22 students in the chat. Students' final grades in the module averaged 8.5 (SD: 1.2). TelEduc was shown to be efficient in supporting the teaching- learning process of endocrine physiology.

A Ku-band active transmit-array module with a horn or patch array as a signal launching/receiving device

This paper is concerned with the design of a Ku-band active transmit-array module of transistor amplifiers excited by either a pyramidal horn or a patch array Optimal distances between the active transmit array and the signal-launching:receiving device, which is either a passive corporate-fed array or a horn, are determined to maximise the power gain at a design frequency: Having established these conditions, the complete structure is investigated in terms of operational bandwidth and near-field and far-field distributions measured at the output side of the transmit array, The experimental results show that the use of a corporate-fed array as an illuminating/receiving device gives higher gain and significantly larger operational bandwidth, An explanation for this behavior is sought.

Self-optimization module for scheduling using case-based reasoning

Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.