Life cycle analysis of a steel building

The present study tries to couple structural optimization problems for building frames, with that of energy efficiency optimization. The objective function of the problem takes into account the following parameters: heat capacity, wall and window insulation pro-file, window sizes, losses due to ventilation, boiler and air conditioning system sizing, sizing of steel cross-sections as well as parameters related to the life cycle of the building. Modeling is based on acceptable from national and European regulations procedures. Optimization is solved us-ing evolutionary algorithms. The optimization problem is implemented on a steel building (10x15 m), in Chania, Greece. This is a first attempt to combine Life Cycle Cost and Optimization with classical Structural Optimization for steel structures. Depending on the requirements from the users of the building further evaluation using building energy management system (BEMS) for the intelligent op-eration and management of heating, ventilation and air-conditioning (HVAC) may be performed

Electrical resistivity measurements in steel fibre reinforced cementitious materials

This paper reports results from experiments aimed at better understanding the influence of fibre dosage and fibre geometry on the AC frequency needed to determine the DC resistivity of cementitious materials containing steel fibres. Impedance spectroscopy and DC galvanodynamic measurements were performed on mortar prisms with varying fibre reinforcement to determine the matrix resistivity (related to ionic current within the pore solution) and composite resistivity (accounting for both ionic current and electronic current through the fibres). The results showed that adding steel fibres did not significantly affect the DC nor the AC matrix resistivity of the mortar prisms. However, the steel fibres yielded a drastic reduction of the frequency associated to the AC matrix resistivity from ∼1 kHz in plain mortar to ∼1 Hz in steel fibre reinforced mortar. These findings revealed the need to adequately adjust the frequency in AC resistivity measurements of steel fibre reinforced cementitious materials

Ανάπτυξη καινοτόμων μεθόδων αυτό-διάγνωσης και αυτό-ίασης της υποβάθμισης σε σύνθετα υλικά πολυμερικής μήτρας

Fibre reinforced polymer (FRP) composites are becoming excellent candidates to address significant weight reductions in several industrial sectors such as the aerospace, automotive, naval and renewable energy. The Achilles' heel of advanced FRP composites centers around the poor interlaminar fracture toughness that may lead to undetected damage within the microstructure deteriorating the mechanical performance. The purpose of the present work unfolds in two axes, (i) to develop a novel Non- Destructive Evaluation technique based on Impedance Spectroscopy for the damage assessment of nanomodified FRP composites. This study aims to providing an insight in the damage mechanisms that occur in FRPs during their active lifetime under different loading scenarios (mechanical or environmental loading), (ii) to develop and employ three “tailor-on-demand” self-healing strategies to counterbalance the aforementioned damage mechanisms and restore specific functionalities in the composite. The healing performance of all the adopted self-healing concepts showed remarkable results both at polymer and composite level

Study of the Effect of Damage on the Electrical Impedance of Carbon Nanotube Reinforced Epoxy Nanocomposites

Within the scope of this work is the study of the effect of damage on the electrical hysteretic behaviour of carbon nanotube (CNT) reinforced epoxy nanocomposites. For that purpose CNT reinforced epoxy nanocomposites were subjected to different levels of damage and their response to an AC voltage excitation was monitored. The correlation between frequency dependent impedance properties and level of damage was extensively studied. The AC frequency response of the interrogated specimens from 10 Hz up to 0.5 MHz revealed a strong correlation between the level of damage and the hysteresis of the studied materials

Study of the Effect of Damage on the Electrical Impedance of Carbon Nanotube Reinforced Epoxy Nanocomposites

Within the scope of this work is the study of the effect of damage on the electrical hysteretic behaviour of carbon nanotube (CNT) reinforced epoxy nanocomposites. For that purpose CNT reinforced epoxy nanocomposites were subjected to different levels of damage and their response to an AC voltage excitation was monitored. The correlation between frequency dependent impedance properties and level of damage was extensively studied. The AC frequency response of the interrogated specimens from 10 Hz up to 0.5 MHz revealed a strong correlation between the level of damage and the hysteresis of the studied materials

Mechanical Properties Assessment of Low-Content Capsule-Based Self-Healing Structural Composites

Microcapsule-based carbon fiber reinforced composites were manufactured by wet layup, in order to assess their mechanical properties and determine their healing efficiency. Microcapsules at 10%wt. containing bisphenol-A epoxy, encapsulated in a urea formaldehyde (UF) shell, were employed with Scandium (III) Triflate (Sc (OTf)3) as the catalyst. The investigation was deployed with two main directions. The first monitored changes to the mechanical performance due to the presence of the healing agent within the composite. More precisely, a minor decrease in interlaminar fracture toughness (GIIC) (−14%), flexural strength (−12%) and modulus (−4%) compared to the reference material was reported. The second direction evaluated the healing efficiency. The experimental results showed significant recovery in fracture toughness up to 84% after the healing process, while flexural strength and modulus healing rates reached up to 14% and 23%, respectively. The Acoustic Emission technique was used to support the experimental results by the onsite monitoring

TAPAS: Train-less Accuracy Predictor for Architecture Search

In recent years an increasing number of researchers and practitioners have been suggesting algorithms for large-scale neural network architecture search: genetic algorithms, reinforcement learning, learning curve extrapolation, and accuracy predictors. None of them, however, demonstrated highperformance without training new experiments in the presence of unseen datasets. We propose a new deep neural network accuracy predictor, that estimates in fractions of a second classification performance for unseen input datasets, without training. In contrast to previously proposed approaches, our prediction is not only calibrated on the topological network information, but also on the characterization of the dataset-difficulty which allows us to re-tune the prediction without any training. Our predictor achieves a performance which exceeds 100 networks per second on a single GPU, thus creating the opportunity to perform large-scale architecture search within a few minutes. We present results of two searches performed in 400 seconds on a single GPU. Our best discovered networks reach 93.67% accuracy for CIFAR-10 and 81.01% for CIFAR-100, verified by training. These networks are performance competitive with other automatically discovered state-of-the-art networks however we only needed a small fraction of the time to solution and computational resources

Development of self-contained microcapsules for optimised catalyst position in self-healing materials

Self-contained microcapsules for use in self-healing epoxy resin are successfully synthesized by suspension polymerization process. The microencapsulation of an epoxy resin using Polymethylmethacrylate (PMMA) as a shell material and the location of scandium triflate (Sc(OTf)3) as the catalyst into microcapsules shell during the microencapsulation processes is presented (PMMA/Sc(OTf)3-walled microcapsules). Spherical microcapsules of 80 μm in diameter with a liquid core content of 30 wt% (determined by HPLC) are produced. Catalyst location on microcapsules are assessed qualitatively by SEM-EADS and quantitatively by TGA showing high yields (⁓70 wt%). The evaluation of the healing efficiency was assessed in terms of fracture toughness recovery. PMMA/Sc(OTf)3-walled microcapsules showed an increased healing efficiency than that of conventional PMMA-walled capsule. The healing efficiency of the PMMA-walled capsules was 46.7 and 55.1% when the system healed at 80 and 120 °C, respectively. However, in the case of PMMA/Sc(OTf)3-walled microcapsules healing efficiency increased to 57.5 and 79.1% for the same healing temperatures.European Commission, FP7, 605412, HIPOCRATE