Bond Characteristics of Strengthened and Retrofitted Steel by Smart CFRP Technique

Usage of new smart materials in retrofitting of structures has become popular within last decade. Carbon fiber reinforced polymer (CFRP) has been widely used in retrofitting and strengthening of concrete structures and its usage in metallic structures is still in the developing stage. The variation of mechanical properties of CFRP and the consequent effects on strengthening and retrofitting CFRP systems are yet to be investigated under different loading and environmental conditions. This paper presents the results of CFRP strengthened and retrofitted corroded steel plate double strap joints under tension. An accelerated corrosion cell has been developed to accelerate the corrosion of the steel samples and CFRP strengthened samples. The results show a direct comparison of bond characteristics of CFRP strengthened and retrofitted steel double strap joints.

Smart sorbers - value adding spent litter fertiliser. A pilot trial

Currently spent litter is not a balanced fertiliser. This project is a first step in improving the ability to reduce environmental contamination and to more fully realise the full fertilizer and soil amendment value of this material.

Smart technologies for peanut industry

Commercialisation and adoption of remote sensing and GIS technologies for improved production forecasting, productivity, quality and paddock- to- plate tracking within the Australian Peanut Industry.

From mundane to smart: Exploring interactions with ‘smart' design objects

In addition to functional and technological features, the role of augmented objects should also be seen in terms of how effectively they fit into the everyday practices of users and how they enhance users' experiences. In this article, the authors introduce a low-tech, internet-of-things technology called CAM (Cooperative Artefact Memory) that is used as a collaborative tool in design studio environments. CAM works as an object memory technology and allows industrial and product designers to collaboratively store relevant information onto their physical design objects, such as sketches, collages, storyboards, and physical mock-ups in the form of messages, annotations and external web links. In the context of this study, CAM serves as an important probing device to understand designers' interaction and experiences with augmented design objects, in their natural environment. The authors carried out a small-scale field trial of CAM in an academic design studio, over three student design projects. In this article, they discuss the findings of their field trial and show how CAM was used by the participants, how it was integrated into the design process and how it was appropriated for different purposes. The authors also found that CAM supported coordination and awareness within the design teams, yet its serendipitous and asynchronous nature facilitated creative and playful interactions between team members. In general, the results show how CAM transformed mundane design objects into “smart” objects that made the creative and playful side of cooperative design visible.

Why we should design smart cities for getting lost

If smart cities run on big data and algorithms that channel only 'relevant' information and opinions to us, how do we maintain the diversity of ideas and possibilities that drives truly smart cities?

Smart applications for energy harvested WSNs

A Wireless Sensor Network (WSN) powered using harvested energies is limited in its operation by instantaneous power. Since energy availability can be different across nodes in the network, network setup and collaboration is a non trivial task. At the same time, in the event of excess energy, exciting node collaboration possibilities exist; often not feasible with battery driven sensor networks. Operations such as sensing, computation, storage and communication are required to achieve the common goal for any sensor network. In this paper, we design and implement a smart application that uses a Decision Engine, and morphs itself into an energy matched application. The results are based on measurements using IRIS motes running on solar energy. We have done away with batteries; instead used low leakage super capacitors to store harvested energy. The Decision Engine utilizes two pieces of data to provide its recommendations. Firstly, a history based energy prediction model assists the engine with information about in-coming energy. The second input is the energy cost database for operations. The energy driven Decision Engine calculates the energy budgets and recommends the best possible set of operations. Under excess energy condition, the Decision Engine, promiscuously sniffs the neighborhood looking for all possible data from neighbors. This data includes neighbor's energy level and sensor data. Equipped with this data, nodes establish detailed data correlation and thus enhance collaboration such as filling up data gaps on behalf of nodes hibernating under low energy conditions. The results are encouraging. Node and network life time of the sensor nodes running the smart application is found to be significantly higher compared to the base application.

A smart approach to precision attitude maneuvers of spacecrafts

A nonlinear adaptive approach is presented to achieve rest-to-rest attitude maneuvers for spacecrafts in the presence of parameter uncertainties and unknown disturbances. A nonlinear controller, designed on the principle of dynamic inversion achieves the goals for the nominal model but suffers performance degradation in the presence of off-nominal parameter values and unwanted inputs. To address this issue, a model-following neuro-adaptive control design is carried out by taking the help of neural networks. Due to the structured approach followed here, the adaptation is restricted to the momentum level equations.The adaptive technique presented is computationally nonintensive and hence can be implemented in real-time. Because of these features, this new approach is named as structured model-following adaptive real-time technique (SMART). From simulation studies, this SMART approach is found to be very effective in achieving precision attitude maneuvers in the presence of parameter uncertainties and unknown disturbances.

Smart polymer mediated purification and recovery of active proteins from inclusion bodies

Obtaining correctly folded proteins from inclusion bodies of recombinant proteins expressed in bacterial hosts requires solubilization with denaturants and a refolding step. Aggregation competes with the second step. Refolding of eight different proteins was carried out by precipitation with smart polymers. These proteins have different molecular weights, different number of disulfide bridges and some of these are known to be highly prone to aggregation. A high throughput refolding screen based upon fluorescence emission maximum around 340 nm (for correctly folded proteins) was developed to identify the suitable smart polymer. The proteins could be dissociated and recovered after the refolding step. The refolding could be scaled up and high refolding yields in the range of 8 mg L-1 (for CD4D12, the first two domains of human CD4) to 58 mg L-1 (for malETrx, thioredoxin fused with signal peptide of maltose binding protein) were obtained. Dynamic light scattering (DLS) showed that polymer if chosen correctly acted as a pseuclochaperonin and bound to the proteins. It also showed that the time for maximum binding was about 50 min which coincided with the time required for incubation (with the polymer) before precipitation for maximum recovery of folded proteins. The refolded proteins were characterized by fluorescence emission spectra, circular dichroism (CD) spectroscopy, melting temperature (T-m), and surface hydrophobicity measurement by ANS (8-anilinol-naphthalene sulfonic acid) fluorescence. Biological activity assay for thioredoxin and fluorescence based assay in case of maltose binding protein (MBP) were also carried out to confirm correct refolding. (C) 2012 Elsevier B.V. All rights reserved.

Smart Network Interface Selection for E-DTNs

We implement two energy models that accurately and comprehensively estimates the system energy cost and communication energy cost for using Bluetooth and Wi-Fi interfaces. The energy models running on a system is used to smartly pick the most energy optimal network interface so that data transfer between two end points is maximized.

Material uncertainty effect on vibration control of smart composite plate using polynomial chaos expansion

Polynomial Chaos Expansion with Latin Hypercube sampling is used to study the effect of material uncertainty on vibration control of a smart composite plate with piezoelectric sensors/actuators. Composite material properties and piezoelectric coefficients are considered as independent and normally distributed random variables. Numerical results show substantial variation in structural dynamic response due to material uncertainty of active vibration control system. This change in response due to material uncertainty can be compensated by actively tuning the feedback control system. Numerical results also show variation in dispersion of dynamic characteristics and control parameters with respect to ply angle and stacking sequence.