Active flow control systems architectures for civil transport aircraft

Copyright @ 2010 American Institute of Aeronautics and AstronauticsThis paper considers the effect of choice of actuator technology and associated power systems architecture on the mass cost and power consumption of implementing active flow control systems on civil transport aircraft. The research method is based on the use of a mass model that includes a mass due to systems hardware and a mass due to the system energy usage. An Airbus A320 aircraft wing is used as a case-study application. The mass model parameters are based on first-principle physical analysis of electric and pneumatic power systems combined with empirical data on system hardware from existing equipment suppliers. Flow control methods include direct fluidic, electromechanical-fluidic, and electrofluidic actuator technologies. The mass cost of electrical power distribution is shown to be considerably less than that for pneumatic systems; however, this advantage is reduced by the requirement for relatively heavy electrical power management and conversion systems. A tradeoff exists between system power efficiency and the system hardware mass required to achieve this efficiency. For short-duration operation the flow control solution is driven toward lighter but less power-efficient systems, whereas for long-duration operation there is benefit in considering heavier but more efficient systems. It is estimated that a practical electromechanical-fluidic system for flow separation control may have a mass up to 40% of the slat mass for a leading-edge application and 5% of flap mass for a trailing-edge application.This work is funded by the Sixth European Union Framework Programme as part of the AVERT project (Contract No. AST5-CT-2006-030914

Analyzing the Potential of Hybrid and Electric Off-Road Equipment in Reducing Carbon Emissions from Construction Industries

This report quantifies the likely impact recent improvements in emissions technology in the heavy construction equipment fleet will have on national and state-level carbon emissions from construction industries. Specific technologies examined in this report include hybrid and electric-powered off-road equipment. Innovation in the equipment manufacturing industry, and adoption of innovative technology by construction firms, is driven by a wide range of factors, some of which can be influenced by public policy. Therefore, this paper describes policies available to public decision makers at the local, state and national levels that impact equipment use and development decisions, including those that encourage the use of green equipment in government procurement, local level job site emissions regulations, and state and nationally mandated emissions standards, fuel taxes, and direct research subsidies

Can the U.S. Get There from Here?

Climate change impacts in the United States are increasingly evident and come with steep economic and social costs. The frequency and intensity of extreme weather events has increased in recent years, bringing record-breaking heat, heavy precipitation, coastal flooding, severe droughts, and damaging wildfires.According to the National Oceanic and Atmospheric Administration (NOAA), weather-related damages in the United States were $60 billion in 2011, and are expected to be significantly greater in 2012.The mounting costs convey an unmistakable urgency to address climate change by reducing greenhouse gas emissions (GHGs). This report examines pathways for GHG reductions in the United States through actions taken at the federal and state levels without the need for new legislation from the U.S. Congress

PEER Testbed Study on a Laboratory Building: Exercising Seismic Performance Assessment

From 2002 to 2004 (years five and six of a ten-year funding cycle), the PEER Center organized the majority of its research around six testbeds. Two buildings and two bridges, a campus, and a transportation network were selected as case studies to “exercise” the PEER performance-based earthquake engineering methodology. All projects involved interdisciplinary teams of researchers, each producing data to be used by other colleagues in their research. The testbeds demonstrated that it is possible to create the data necessary to populate the PEER performancebased framing equation, linking the hazard analysis, the structural analysis, the development of damage measures, loss analysis, and decision variables. This report describes one of the building testbeds—the UC Science Building. The project was chosen to focus attention on the consequences of losses of laboratory contents, particularly downtime. The UC Science testbed evaluated the earthquake hazard and the structural performance of a well-designed recently built reinforced concrete laboratory building using the OpenSees platform. Researchers conducted shake table tests on samples of critical laboratory contents in order to develop fragility curves used to analyze the probability of losses based on equipment failure. The UC Science testbed undertook an extreme case in performance assessment—linking performance of contents to operational failure. The research shows the interdependence of building structure, systems, and contents in performance assessment, and highlights where further research is needed. The Executive Summary provides a short description of the overall testbed research program, while the main body of the report includes summary chapters from individual researchers. More extensive research reports are cited in the reference section of each chapter

Inventory model with preservation technology and exponential holding cost in fuzzy scenario

Inventories are ubiquitous in the business sector. Since inventory is most frequently incurring expense, stock control is critical for an organization and it must be scrimping and saving in contemplation of function the merchandising fruitfully.  In this paper, an inventory model for a deteriorating item under exponential holding cost with collaborative preservation technology investment under carbon policy is considered.  Also, this study is developed in a fuzzy scenario by employing triangular fuzzy numbers.  Signed distance method is utilized to enhance decision making and optimization. Further the convexity of the total cost function for both the crisp and the fuzzy case is established.  The objective is to determine the optimal investment in preservation technology and the optimal cycle length so as to minimize the total cost. Moreover, some managerial results are obtained by using sensitivity analysis and graphical representation is also carried out.  The applications of the proposed model is used in the fields of constructing machinery or heavy duty construction equipment, specific chemicals and processed food

Modelling rail track deterioration and maintenance: current practices and future needs

As commercialisation and privatisation of railway systems reach the political agendas in a number of countries, including Australia, the separation of infrastructure from operating business dictates that track costs need to be shared on an equitable basis. There is also a world-wide trend towards increased pressures on rail track infrastructure through increases in axle loads and train speeds. Such productivity and customer service driven pressures inevitably lead to reductions in the life of track components and increases in track maintenance costs. This paper provides a state-of-the-art review of track degradation modeling, as well as an overview of track maintenance decision support systems currently in use in North America and Europe. The essential elements of a maintenance optimisation model currently under development are also highlighted

Techno-economic performance analysis of biofuel production and miniature electric power generation from biomass fast pyrolysis and bio-oil upgrading

The techno-economic performance analysis of biofuel production and electric power generation from biomass fast pyrolysis and bio-oil hydroprocessing is explored through process simulation. In this work, a process model of 72 MT/day pine wood fast pyrolysis and bio-oil hydroprocessing plant was developed with rate based chemical reactions using Aspen Plus® process simulator. It was observed from simulation results that 1 kg s−1 pine wooddb generate 0.64 kg s−1 bio-oil, 0.22 kg s−1 gas and 0.14 kg s−1 char. Simulation results also show that the energy required for drying and fast pyrolysis operations can be provided from the combustion of pyrolysis by-products, mainly, char and non-condensable gas with sufficient residual energy for miniature electric power generation. The intermediate bio-oil product from the fast pyrolysis process is upgraded into gasoline and diesel via a two-stage hydrotreating process, which was implemented by a pseudo-first order reaction of lumped bio-oil species followed by the hydrocracking process in this work. Simulation results indicate that about 0.24 kg s−1 of gasoline and diesel range products and 96 W of electric power can be produced from 1 kg s−1 pine wooddb. The effect of initial biomass moisture content on the amount of electric power generated and the effect of biomass feed composition on product yields were also reported in this study. Aspen Process Economic Analyser® was used for equipment sizing and cost estimation for an nth plant and the product value was estimated from discounted cash flow analysis assuming the plant operates for 20 years at a 10% annual discount rate. Economic analysis indicates that the plant will require £16.6 million of capital investment and product value is estimated at £6.25/GGE. Furthermore, the effect of key process and economic parameters on product value and the impact of electric power generation equipment on capital cost and energy efficiency were also discussed in this study

Automated Measurement of Heavy Equipment Greenhouse Gas Emission: The case of Road/Bridge Construction and Maintenance

Road/bridge construction and maintenance projects are major contributors to greenhouse gas (GHG) emissions such as carbon dioxide (CO2), mainly due to extensive use of heavy-duty diesel construction equipment and large-scale earthworks and earthmoving operations. Heavy equipment is a costly resource and its underutilization could result in significant budget overruns. A practical way to cut emissions is to reduce the time equipment spends doing non-value-added activities and/or idling. Recent research into the monitoring of automated equipment using sensors and Internet-of-Things (IoT) frameworks have leveraged machine learning algorithms to predict the behavior of tracked entities. In this project, end-to-end deep learning models were developed that can learn to accurately classify the activities of construction equipment based on vibration patterns picked up by accelerometers attached to the equipment. Data was collected from two types of real-world construction equipment, both used extensively in road/bridge construction and maintenance projects: excavators and vibratory rollers. The validation accuracies of the developed models were tested of three different deep learning models: a baseline convolutional neural network (CNN); a hybrid convolutional and recurrent long shortterm memory neural network (LSTM); and a temporal convolutional network (TCN). Results indicated that the TCN model had the best performance, the LSTM model had the second-best performance, and the CNN model had the worst performance. The TCN model had over 83% validation accuracy in recognizing activities. Using deep learning methodologies can significantly increase emission estimation accuracy for heavy equipment and help decision-makers to reliably evaluate the environmental impact of heavy civil and infrastructure projects. Reducing the carbon footprint and fuel use of heavy equipment in road/bridge projects have direct and indirect impacts on health and the economy. Public infrastructure projects can leverage the proposed system to reduce the environmental cost of infrastructure project

Internal report cluster 1: Urban freight innovations and solutions for sustainable deliveries (2/4)

Technical report about sustainable urban freight solutions, part 2 of