Smart Materials as Intelligent Insulation

In order to provide a robust infrastructure for the transmission and distribution of electrical power, understanding and monitoring equipment ageing and failure is of paramount importance. Commonly, failure is associated with degradation of the dielectric material; therefore the introduction of a smart moiety into the material is a potentially attractive means of continual condition monitoring. It is important that any introduction of smart groups into the dielectric does not have any detrimental effect on the desirable electrical and mechanical properties of the bulk material. Initial work focussed on the introduction of fluorophores into a model dielectric system. Fluorescence is known to be a visible effect even at very low concentrations of active fluorophores and therefore was thought well suited to such an application. It was necessary both to optimise the active fluorophore itself and to determine the most appropriate manner in which to introduce the fluorophores into the insulating system. This presentation will describe the effect of introducing fluorophores into polymeric systems on the dielectric properties of the material and the findings thus far [1]. Alternative smart material systems will also be discussed along with the benefits and limitations of smart materials as electric field sensors

Digital lace:a collision of responsive technologies

Designing with properties such as colour-change and light using electronics and digital control brings new challenges within art and design, and a range of new possibilities for aesthetics, tactility and functionality. Heimtextil 2014 (accessed April 2014) promotes emerging materials and technologies as one of four trends which highlight the increasing demand for unique products utilizing novel material properties and digital making. However, there is still limited insight into the creative potential of these materials that are fundamental to the exploitation of 'smart' material properties, the development of new 'smart' surfaces and digital tools that facilitate designing with colour-change and light-emitting properties specific to textiles. This submission to the Fiber arts category presents new material concepts as Digital Lace: a novel, multifaceted textile which will be presented as an interactive table runner for a digitally manufactured console table. Digital Lace explicitly pools together the digital-craft skills base and disparate expertise of printed textile practitioner and thermochromic specialist, Sara Robertson (SR) and constructed textile practitioner and light-emitting optical fibre specialist, Sarah Taylor (ST). Within the context of 'smart', material development and experimentation, Digital lace exploits and amalgamates the responsive technologies of dye and fibre with digital-control

Transient Non-linear Thermal FEM Simulation of Smart Power Switches and Verification by Measurements

Thermal FEM (Finite Element Method) simulations can be used to predict the thermal behavior of power semiconductors in application. Most power semiconductors are made of silicon. Silicon thermal material properties are significantly temperature dependent. In this paper, validity of a common non-linear silicon material model is verified by transient non-linear thermal FEM simulations of Smart Power Switches and measurements. For verification, over-temperature protection behavior of Smart Power Switches is employed. This protection turns off the switch at a pre-defined temperature which is used as a temperature reference in the investigation. Power dissipation generated during a thermal overload event of two Smart Power devices is measured and used as an input stimulus to transient thermal FEM simulations. The duration time of the event together with the temperature reference is confronted with simulation results and thus the validity of the silicon model is proved. In addition, the impact of non-linear thermal properties of silicon on the thermal impedance of power semiconductors is shown.Comment: Submitted on behalf of TIMA Editions (http://irevues.inist.fr/tima-editions

Smart textiles to promote multidisciplinary stem training

Smart textiles consist of multi-disciplinary knowledge. Disciplines such as physics, mathematics, material science or electrics is needed in order to be able to design and manufacture a smart textiles product. This is why knowledge in smart textiles may be used to showcase high school and university students in basic years of preparation some applications of technical disciplines they are learning. The Erasmus+ project “Smart textiles for STEM training – Skills4Smartex” is a strategic partnership project for Vocational Education and Training aiming to promote additional knowledge and skills for trainees in technical fields, for a broader understanding of interconnections and application of STEM, via smart textiles. Skills4Smartex is an ongoing project within the period Oct. 2018-Sept. 2020, with a partnership of six research providers in textiles www.skills4smartex.eu. The project has three intellectual outputs: the Guide for smart practices (O1), the Course in smart textiles (O2) and the Dedicated e-learning Instrument (O3). The Guide for smart practices consists in the analysis of a survey with 63 textile companies on partnership level and interviews with 18 companies. Main aim of O1 is to transfer from source site to target sites technical and smart textile best practices and the profile of workforce needed for the future textile industry. The needs analysis achieved within O1will serve to conceive the Course for smart textiles with 42 modules (O2), to be accessed via the Dedicated e-learning Instrument (O3). All outputs are available with free access on the e-learning platform: www.adva2tex.eu/portal

Learning objects and learning designs: an integrated system for reusable, adaptive and shareable learning content

This paper proposes a system, the Smart Learning Design Framework, designed to support the development of pedagogically sound learning material within an integrated, platform-independent data structure. The system supports sharing, reuse and adaptation of learning material via a metadata-driven philosophy that enables the technicalities of the system to be imperceptible to the author and consumer. The system proposes the use of pedagogically focused metadata to support and guide the author and to adapt and deliver the content to the targeted consumer. A prototype of the proposed system, which provides proof of concept for the novel processes involved, has been developed. The paper describes the Smart Learning Design Framework and places it within the context of alternative learning object models and frameworks to highlight similarities, differences and advantages of the proposed system

Design of an instrumented smart cutting tool and its implementation and application perspectives

This paper presents an innovative design of a smart cutting tool, using two surface acoustic wave (SAW) strain sensors mounted onto the top and the side surface of the tool shank respectively, and its implementation and application perspectives. This surface acoustic wave-based smart cutting tool is capable of measuring the cutting force and the feed force in a real machining environment, after a calibration process under known cutting conditions. A hybrid dissimilar workpiece is then machined using the SAW-based smart cutting tool. The hybrid dissimilar material is made of two different materials, NiCu alloy (Monel) and steel, welded together to form a single bar; this can be used to simulate an abrupt change in material properties. The property transition zone is successfully detected by the tool; the sensor feedback can then be used to initiate a change in the machining parameters to compensate for the altered material properties.The UK Technology Strategy Board (TSB) for supporting this research (SEEM Project, contract No. BD266E

Probabilistic structural analysis of adaptive/smart/intelligent space structures

A three-bay, space, cantilever truss is probabilistically evaluated for adaptive/smart/intelligent behavior. For each behavior, the scatter (ranges) in buckling loads, vibration frequencies, and member axial forces are probabilistically determined. Sensitivities associated with uncertainties in the structure, material and load variables that describe the truss are determined for different probabilities. The relative magnitude for these sensitivities are used to identify significant truss variables that control/classify its behavior to respond as an adaptive/smart/intelligent structure. Results show that the probabilistic buckling loads and vibration frequencies increase for each truss classification, with a substantial increase for intelligent trusses. Similarly, the probabilistic member axial forces reduce for adaptive and intelligent trusses and increase for smart trusses

Adjustment of model parameters to estimate distribution transformers remaining lifespan

Currently, the electrical system in Argentina is working at its maximum capacity, decreasing the margin between the installed power and demanded consumption, and drastically reducing the service life of transformer substations due to overload (since the margin for summer peaks is small). The advent of the Smart Grids allows electricity distribution companies to apply data analysis techniques to manage resources more efficiently at different levels (avoiding damages, better contingency management, maintenance planning, etc.). The Smart Grids in Argentina progresses slowly due to the high costs involved. In this context, the estimation of the lifespan reduction of distribution transformers is a key tool to efficiently manage human and material resources, maximizing the lifetime of this equipment. Despite the current state of the smart grids, the electricity distribution companies can implement it using the available data. Thermal models provide guidelines for lifespan estimation, but the adjustment to particular conditions, brands, or material quality is done by adjusting parameters. In this work we propose a method to adjust the parameters of a thermal model using Genetic Algorithms, comparing the estimation values of top-oil temperature with measurements from 315 kVA distribution transformers, located in the province of Tucumán, Argentina. The results show that, despite limited data availability, the adjusted model is suitable to implement a transformer monitoring system.Fil: Jimenez, Victor Adrian. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Will, Adrian L. E.. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Gotay Sardiñas, Jorge. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; ArgentinaFil: Rodriguez, Sebastian Alberto. Universidad Tecnológica Nacional. Facultad Regional Tucumán. Centro de Investigación en Tecnologías Avanzadas de Tucumán; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentin

A smart material based approach to morphing

This presentation gives an overview of the Shape Memory Alloy (SMA) based approach to the research and13; development of adaptive/smart/morphing airframe structural technologies at the Advanced Composites13; Division, NAL. Central to this approach is the efficient integration of thermal NiTi SMA elements with13; polymeric carbon composites. The SMA elements could be either externally placed or embedded in the13; polymeric composite. The external connection could be in the form of mechanisms / devices