Achievements and Challenges in Recognizing and Reconstructing Civil Infrastructure

The US National Academy of Engineering recently identified restoring and improving urban infrastructure as one of the grand challenges of engineering. Part of this challenge stems from the lack of viable methods to map/label existing infrastructure. For computer vision, this challenge becomes “How can we automate the process of extracting geometric, object oriented models of infrastructure from visual data?” Object recognition and reconstruction methods have been successfully devised and/or adapted to answer this question for small or linear objects (e.g. columns). However, many infrastructure objects are large and/or planar without significant and distinctive features, such as walls, floor slabs, and bridge decks. How can we recognize and reconstruct them in a 3D model? In this paper, strategies for infrastructure object recognition and reconstruction are presented, to set the stage for posing the question above and discuss future research in featureless, large/planar object recognition and modeling.

Global civil aviation black carbon emissions.

Aircraft black carbon (BC) emissions contribute to climate forcing, but few estimates of BC emitted by aircraft at cruise exist. For the majority of aircraft engines the only BC-related measurement available is smoke number (SN)-a filter based optical method designed to measure near-ground plume visibility, not mass. While the first order approximation (FOA3) technique has been developed to estimate BC mass emissions normalized by fuel burn [EI(BC)] from SN, it is shown that it underestimates EI(BC) by >90% in 35% of directly measured cases (R(2) = -0.10). As there are no plans to measure BC emissions from all existing certified engines-which will be in service for several decades-it is necessary to estimate EI(BC) for existing aircraft on the ground and at cruise. An alternative method, called FOX, that is independent of the SN is developed to estimate BC emissions. Estimates of EI(BC) at ground level are significantly improved (R(2) = 0.68), whereas estimates at cruise are within 30% of measurements. Implementing this approach for global civil aviation estimated aircraft BC emissions are revised upward by a factor of ~3. Direct radiative forcing (RF) due to aviation BC emissions is estimated to be ~9.5 mW/m(2), equivalent to ~1/3 of the current RF due to aviation CO2 emissions.

A numerical study into the effects of Bio-synthetic Paraffinic Kerosine blends with Jet-A fuel for civil aircraft engine

Growing concerns regarding fluctuating fuel costs and pollution targets for gas emissions, have led the aviation industry to seek alternative technologies to reduce its dependency on crude oil, and its net emissions. Recently blends of bio-fuel with kerosine, have become an alternative solution as they offer "greener" aircraft and reduce demand on crude oil. Interestingly, this technique is able to be implemented in current aircraft as it does not require any modification to the engine. Therefore, the present study investigates the effect of blends of bio-synthetic paraffinic kerosine with Jet-A in a civil aircraft engine, focusing on its performance and exhaust emissions. Two bio-fuels are considered: Jatropha Bio-synthetic Paraffinic Kerosine (JSPK) and Camelina Bio-synthetic Paraffinic Kerosine (CSPK); there are evaluated as pure fuels, and as 10% and 50% blend with Jet-A. Results obtained show improvement in thrust, fuel flow and SFC as composition of bio-fuel in the blend increases. At design point condition, results on engine emissions show reduction in NO x, and CO, but increases of CO is observed at fixed fuel condition, as the composition of bio-fuel in the mixture increases. Copyright © 2012 by ASME.

Risk-based approaches to sustainability in civil engineering

Infrastructure project sustainability assessment typically entails the use of specialised assessment tools to measure and rate project performance against a set of criteria. This paper looks beyond the prevailing approaches to sustainability assessments and explores sustainability principles in terms of project risks and opportunities. Taking a risk management approach to applying sustainability concepts to projects has the potential to reconceptualise decision structures for sustainability from bespoke assessments to becoming a standard part of the project decisionmaking process. By integrating issues of sustainability into project risk management for project planning, design and construction, sustainability is considered within a more traditional business and engineering language. Currently, there is no widely practised approach for objectively considering the environmental and social context of projects alongside the more traditional project risk assessments of time, cost and quality. A risk-based approach would not solve all the issues associated with existing sustainability assessments but it would place sustainability concerns alongside other key risks and opportunities, integrating sustainability with other project decisions.

Weighted least squares with expectation-maximization algorithm for burst detection in U.K. water distribution systems

Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.