Automated Detection of Exposed Reinforcement in Post-Earthquake Safety and Structural Evaluations

The world is at the threshold of emerging technologies, where new systems in construction, materials, and civil and architectural design are poised to make the world better from a structural and construction perspective. Exciting developments, that are too many to name individually, take place yearly, affecting design considerations and construction practices. This edited book brings together modern methods and advances in structural engineering and construction, fulfilling the mission of ISEC Conferences, which is to enhance communication and understanding between structural and construction engineers for successful design and construction of engineering projects. The articles in this book are those accepted for publication and presentation at the 6th International Structural Engineering and Construction Conference in Zurich. The 6th ISEC Conference in Zurich, Switzerland, follows the overwhelming reception and success of previous ISEC conference in Las Vegas, USA in 2009; Melbourne, Australia in 2007; Shunan, Japan in 2005; Rome, Italy in 2003; and Honolulu, USA in 2001. Many topics are covered in this book, ranging from legal affairs and contracting, to innovations and risk analysis in infrastructure projects, analysis and design of structural systems, materials, architecture, and construction. The articles here are a lasting testimony to the excellent research being undertaken around the world. These articles provide a platform for the exchange of ideas, research efforts and networking in the structural engineering and construction communities. We congratulate and thank the authors for these articles that were selected after intensive peer-review, and our gratitude extends to all reviewers and members of the International Technical Committee. It is their combined contributions that have made this book a reality.

Graphene field-effect transistors as room-temperature terahertz detectors

The unique optoelectronic properties of graphene make it an ideal platform for a variety of photonic applications, including fast photodetectors, transparent electrodes in displays and photovoltaic modules, optical modulators, plasmonic devices, microcavities, and ultra-fast lasers. Owing to its high carrier mobility, gapless spectrum and frequency-independent absorption, graphene is a very promising material for the development of detectors and modulators operating in the terahertz region of the electromagnetic spectrum (wavelengths in the hundreds of micrometres), still severely lacking in terms of solid-state devices. Here we demonstrate terahertz detectors based on antenna-coupled graphene field-effect transistors. These exploit the nonlinear response to the oscillating radiation field at the gate electrode, with contributions of thermoelectric and photoconductive origin. We demonstrate room temperature operation at 0.3 THz, showing that our devices can already be used in realistic settings, enabling large-area, fast imaging of macroscopic samples. © 2012 Macmillan Publishers Limited. All rights reserved.

The effect of floor heat source area on the induced airflow in a room

We examine the role of heat source geometry in determining rates of airflow and thermal stratification in natural displacement ventilation flows. We modify existing models to account for heat sources of finite (non-zero) area, such as formed by a sun patch warming the floor of a room. Our model allows for predictions of the steady stratification and ventilation flow rates that develop in a room due to a circular heat source at floor level. We compare our theoretical predictions with predictions for the limiting cases of a point source of heat (yielding a stratified interior), and a uniformly heated floor (yielding a mixed interior). Our theory shows a smooth transition between these two limits, which themselves result in extremes of ventilation, as the ratio of the heat source radius to the room height increases. Our model for the transition from displacement to mixing ventilation is compared to previous work and demonstrates that the transition can occur for smaller sources than previously thought, particularly for rooms with large floor area compared to ceiling height. © 2009 Elsevier Ltd.

Room temperature all-silicon photonic crystal nanocavity light emitting diode at sub-bandgap wavelengths

Silicon is now firmly established as a high performance photonic material. Its only weakness is the lack of a native electrically driven light emitter that operates CW at room temperature, exhibits a narrow linewidth in the technologically important 1300-1600 nm wavelength window, is small and operates with low power consumption. Here, an electrically pumped all-silicon nano light source around 1300-1600 nm range is demonstrated at room temperature. Using hydrogen plasma treatment, nano-scale optically active defects are introduced into silicon, which then feed the photonic crystal nanocavity to enhance the electrically driven emission in a device via Purcell effect. A narrow (Δλ=0.5 nm) emission line at 1515 nm wavelength with a power density of 0.4mW/cm2 is observed, which represents the highest spectral power density ever reported from any silicon emitter. A number of possible improvements are also discussed, that make this scheme a very promising light source for optical interconnects and other important silicon photonics applications. © 2012 by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Enhancement of room temperature sub-bandgap light emission from silicon photonic crystal nanocavity by Purcell effect

We report the enhancement of sub-bandgap photoluminescence from silicon via the Purcell effect. We couple the defect emission from silicon, which is believed to be due to hydrogen incorporation into the lattice, to a photonic crystal (PhC) nanocavity. We observe an up to 300-fold enhancement of the emission at room temperature at 1550 nm, as compared to an unpatterned sample, which is then comparable to the silicon band-edge emission. We discuss the possibility of enhancing this emission even further by introducing additional defects by ion implantation, or by treating the silicon PhC nanocavity with hydrogen plasma. © 2011 Elsevier B.V.

Subbandgap photoluminescence of Si photonic crystal nanocavity at room temperature

Using a photonic crystal cavity and a hydrogen plasma treatment, we enhance the photoluminescence (PL) from optically active defects in silicon by a factor of 3000 compared to the as-bought material at room temperature. © 2011 IEEE.

Room-temperature emission at telecom wavelengths from silicon photonic crystal nanocavities

Strongly enhanced light emission at wavelengths between 1.3 and 1.6 μm is reported at room temperature in silicon photonic crystal (PhC) nanocavities with optimized out-coupling efficiency. Sharp peaks corresponding to the resonant modes of PhC nanocavities dominate the broad sub-bandgap emission from optically active defects in the crystalline Si membrane. We measure a 300-fold enhancement of the emission from the PhC nanocavity due to a combination of far-field enhancement and the Purcell effect. The cavity enhanced emission has a very weak temperature dependence, namely less than a factor of 2 reduction between 10 K and room temperature, which makes this approach suitable for the realization of efficient light sources as well as providing a quick and easy tool for the broadband optical characterization of silicon-on-insulator nanostructures. © 2011 American Institute of Physics.

Nanowire and graphene architectures for room temperature THz detection

Antenna-coupled field effect transistors have been developed as plasma-wave THz detectors in both InAs nanowire and graphene channel material. Room temperature operation has been achieved up to frequencies of 1.5 THz, with noise equivalent powers as low as a few 10-11 W/Hz1/2, and high-speed response. © 2012 IEEE.

Dopamine and performance in a reinforcement learning task: evidence from Parkinson's disease.

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning.

Dopamine and performance in a reinforcement learning task: Evidence from Parkinson's disease

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning. © 2012 The Author.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Thermogravimetric study on the hydration of reactive magnesia and silica mixture at room temperature

The synthesis of magnesium silicate hydrate (MSH), which has wide applications in both construction and environmental fields, has been studied for decades. However, it is known that the characteristics of magnesia (MgO) vary significantly depending on their calcination conditions, which is expected to affect their performance in the MgO-SiO2-H2O system. This paper investigated the effect of different MgO and silica sources on the formation of magnesium silicate hydrate (MSH) at room temperature. The hydration process was studied by mixing commercial reactive MgO and silica powders with water and curing for 1, 7 and 28 days. The hydration products were analysed with the help of X-ray diffraction (XRD) and thermogravimatric analysis (TGA). The results showed the continuous consumption of MgO and the existence of MSH and brucite and other minor phases such as magnesite and calcite. It is found that the Mg and Si sources have significant effect on the hydration process of MgO-SiO2-H2O system. The reaction degree is controlled by the availability of dissolved Mg and Si in the solution. The former is determined by the reactivity of MgO and the latter is related to the reactivity of the silica as well as the pH of the system. © 2013 Elsevier B.V. All rights reserved.

The influence of room geometry on the overturning of smoke owing to a floor fire

The present paper explores the influence of room geometry on the overturning of smoke owing to a centrally located floor fire, and examines the implications on smoke filling times. The focus is on presenting practical design guidelines based on the theoretical predictions of the model of Kaye and Hunt. An engineering platform is developed for the prediction of smoke filling times, and a rational basis is provided by way of which smoke behaviour can be specified for simple room designs. The time taken for smoke to fill a room to a given height is critically affected by the room aspect ratio and the characteristic size of the buoyancy source. At large times, taller (small aspect ratio) rooms are shown to fill with smoke at a faster rate than wide (large aspect ratio) rooms owing to large-scale overturning and engulfing of ambient air during the initial transients. Larger area sources of buoyancy also decrease significantly the smoke filling times, with important implications for fire and smoke safety design. Simplified design curves incorporating the main findings have been developed for use as a tool by practising fire-safety engineers.