scholarly journals STOCHASTIC CARBON EMISSION ESTIMATION METHOD FOR CONSTRUCTION OPERATION

2016 ◽  
Vol 23 (1) ◽  
pp. 137-149 ◽  
Author(s):  
Chang-Yong YI ◽  
Han-Seong GWAK ◽  
Dong-Eun LEE
Keyword(s):  
Carbon Emission ◽  
Performance Metrics ◽  
Ghg Emissions ◽  
Estimation Method ◽  
Operating Conditions ◽  
Analysis Tool ◽  
Micro Scale ◽  
Work Tasks ◽  
Emission Estimation ◽  
Construction Operation

Low carbon construction is an important operation management goal because greenhouse gas (GHG) reduc­tion has become a global concern. Major construction resources that contribute GHG, such as equipment and labour, are being targeted to achieve this goal. The GHG emissions produced by the resources vary with their operating conditions. It is commendable to provide a statistical GHG emission estimation method that models the transitory nature of resource states at micro-scale of construction operations. This paper proposes a computational method called Stochastic Carbon Emission Estimation (SCE2) that measures the variability of GHG emissions. It creates construction operation models consisting of atomic work tasks, utilizes hourly equipment fuel consumption and hourly labourer respiratory rates that change according to their operating conditions classified into five categories, and identifies an optimal resource combi­nation by trading off eco-economic performance metrics such as the amount of GHG emissions, operation completion time, operation completion cost, and productivity. The study is of value to researchers because SCE2 fill in a gap to eco-economic operation modelling and analysis tool which considers operating conditions at micro-scale of construction operation having many stochastic work tasks. This study is also relevance to practitioners because it allows project man­agers to achieve eco-economic goals while honouring predefined constraints associated with time and cost.

Integrated carbon emission estimation method for construction operation and project scheduling

2015 ◽  
Vol 20 (4) ◽  
pp. 1211-1220 ◽  
Author(s):  
Tae-Kyung Lim ◽  
Han-Seong Gwak ◽  
Byung-Soo Kim ◽  
Dong-Eun Lee
Keyword(s):  
Project Scheduling ◽  
Carbon Emission ◽  
Estimation Method ◽  
Emission Estimation ◽  
Construction Operation

scholarly journals Component-Oriented Modeling of a Micro-Scale Organic Rankine Cycle System for Waste Heat Recovery Applications

2021 ◽  
Vol 11 (5) ◽  
pp. 1984
Author(s):  
Ramin Moradi ◽  
Emanuele Habib ◽  
Enrico Bocci ◽  
Luca Cioccolanti
Keyword(s):  
Electric Power ◽  
Heat Recovery ◽  
Waste Heat Recovery ◽  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Operating Conditions ◽  
Working Fluid ◽  
Pump Efficiency ◽  
Micro Scale

Organic Rankine cycle (ORC) systems are some of the most suitable technologies to produce electricity from low-temperature waste heat. In this study, a non-regenerative, micro-scale ORC system was tested in off-design conditions using R134a as the working fluid. The experimental data were then used to tune the semi-empirical models of the main components of the system. Eventually, the models were used in a component-oriented system solver to map the system electric performance at varying operating conditions. The analysis highlighted the non-negligible impact of the plunger pump on the system performance Indeed, the experimental results showed that the low pump efficiency in the investigated operating range can lead to negative net electric power in some working conditions. For most data points, the expander and the pump isentropic efficiencies are found in the approximate ranges of 35% to 55% and 17% to 34%, respectively. Furthermore, the maximum net electric power was about 200 W with a net electric efficiency of about 1.2%, thus also stressing the importance of a proper selection of the pump for waste heat recovery applications.

scholarly journals There is a silver lining: carbon footprint reduction by holding Preventive Cardiology conference 2020 virtually

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
T Batool ◽  
A Neven ◽  
Y Vanrompay ◽  
M Adnan ◽  
P Dendale
Keyword(s):  
Climate Change ◽  
Co2 Emissions ◽  
Carbon Footprint ◽  
Carbon Emission ◽  
Ghg Emissions ◽  
Air Travel ◽  
Co2 Production ◽  
Scientific Conference ◽  
Preventive Cardiology ◽  
Transport Modes

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): Special Research Fund (BOF), Hasselt University Introduction The transportation sector is one of the major sectors influencing climate change, contributing around 16% of total Greenhouse gases (GHG) emissions. Aviation contributes to 12% of the transport related emissions. Among other climate change impacts, elevated heat exposure is associated with increased cardiac events and exposure to air pollution caused by GHG emissions has also well-known association with increased cardiovascular related morbidity and mortality. The global temperature rise should be restricted to less than 2 °C which requires keeping carbon emission (CO2) less than 2900 billion tonnes by the end of the 21st century. Assuming air travel a major contributing source to GHG, this study aims to raise the awareness about potential carbon emissions reduction due to air travel of international events like a scientific conference. Purpose Due to the global pandemic of COVID-19, the Preventive cardiology conference 2020 which was planned to be held at Malaga Spain, instead was held in virtual online way. This study aims to calculate the contribution of reduced CO2  emissions in tons due to ESC preventive cardiology conference 2020, which was then held online and air travel of the registered participants was avoided. Methods Anonymized participant registration information was used to determine the country and city of the 949 registered participants of the Preventive Cardiology conference 2020. It is assumed that participants would have travelled from the closest airports from their reported city locations to Malaga airport, Spain. At first, the closest city airports were determined using Google maps and flights information, then the flight emissions (direct and indirect CO2-equivalent emissions) per passenger for the given flight distances were calculated. The CO2 emissions (tons) were calculated for round trips in economy class from the participants of 68 nationalities (excluding 60 participants from Spain as they are assumed to take other modes of transport than airplane). Results In total, 1156.51 tons of CO2  emissions were saved by turning the physical conference into a virtual event. This emission amount is equivalent to the annual CO2 production of 108 people living in high-income countries. Conclusion The pandemic situation has forced us to rethink the necessity of trips by air and has shown us the feasibility of digitally organized events. The information from this study can add to the awareness about reduced amount of carbon emission due to air travel by organizing events in a virtual way when possible. Apart from only digitally organized events there are others options to reduce the carbon footprint of conferences such as limiting the number of physical attendees, encouraging the use of relatively sustainable transport modes for participants from nearby countries (e.g. international trains and use of active transport modes at conference venue etc.) and including CO2 emission offsetting costs.

scholarly journals On the Two-Scale Modelling of Elastohydrodynamic Lubrication in Tilted-Pad Bearings

Lubricants ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 78 ◽  
Author(s):  
Gregory de Boer ◽  
Andreas Almqvist
Keyword(s):  
Surface Topography ◽  
Load Capacity ◽  
Three Dimensional ◽  
Elastohydrodynamic Lubrication ◽  
Multiscale Methods ◽  
Operating Conditions ◽  
Real Surface ◽  
Micro Scale ◽  
Macro Scale ◽  
Heterogeneous Multiscale

A two-scale method for modelling the Elastohydrodynamic Lubrication (EHL) of tilted-pad bearings is derived and a range of solutions are presented. The method is developed from previous publications and is based on the Heterogeneous Multiscale Methods (HMM). It facilitates, by means of homogenization, incorporating the effects of surface topography in the analysis of tilted-pad bearings. New to this article is the investigation of three-dimensional bearings, including the effects of both ideal and real surface topographies, micro-cavitation, and the metamodeling procedure used in coupling the problem scales. Solutions for smooth bearing surfaces, and under pure hydrodynamic operating conditions, obtained with the present two-scale EHL model, demonstrate equivalence to those obtained from well-established homogenization methods. Solutions obtained for elastohydrodynamic operating conditions, show a dependency of the solution to the pad thickness and load capacity of the bearing. More precisely, the response for the real surface topography was found to be stiffer in comparison to the ideal. Micro-scale results demonstrate periodicity of the flow and surface topography and this is consistent with the requirements of the HMM. The means of selecting micro-scale simulations based on intermediate macro-scale solutions, in the metamodeling approach, was developed for larger dimensionality and subsequent calibration. An analysis of the present metamodeling approach indicates improved performance in comparison to previous studies.

scholarly journals A Study on Sustainable Consumption of Fuel—An Estimation Method of Aircraft

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7559
Author(s):  
Lisha Li ◽  
Shuming Yuan ◽  
Yue Teng ◽  
Jing Shao
Keyword(s):  
Neural Network ◽  
Fuel Consumption ◽  
Influencing Factors ◽  
Carbon Emission ◽  
Estimation Method ◽  
Civil Aviation ◽  
Accurate Estimation ◽  
Low Carbon ◽  
Fuel Price ◽  
Aircraft Fuel

Though the development of China’s civil aviation and the improvement of control ability have strengthened the safety operation and support ability effectively, the airlines are under the pressure of operation costs due to the increase of aircraft fuel price. With the development of optimization controlling methods in flight management systems, it becomes increasingly challenging to cut down flight fuel consumption by control the flight status of the aircraft. Therefore, the airlines both at home and abroad mainly rely on the accurate estimation of aircraft fuel to reduce fuel consumption, and further reduce its carbon emission. The airlines have to take various potential factors into consideration and load more fuel to cope with possible negative situation during the flight. Therefore, the fuel for emergency use is called PBCF (Performance-Based Contingency Fuel). The existing PBCF forecasting method used by China Airlines is not accurate, which fails to take into account various influencing factors. This paper aims to find a method that could predict PBCF more accurately than the existing methods for China Airlines.This paper takes China Eastern Airlines as an example. The experimental data of flight fuel of China Eastern Airlines Co, Ltd. were collected to find out the relevant parameters affecting the fuel consumption, which is followed by the establishment of the LSTM neural network through the parameters and collected data. Finally, through the established neural network model, the PBCF addition required by the airline with different influencing factors is output. It can be seen from the results that the all the four models are available for the accurate prediction of fuel consumption. The amount of data of A319 is much larger than that of A320 and A330, which leads to higher accuracy of the model trained by A319. The study contributes to the calculation methods in the fuel-saving project, and helps the practitioners to learn about a particular fuel calculation method. The study brought insights for practitioners to achieve the goal of low carbon emission and further contributed to their progress towards circular economy.

scholarly journals Roadmapping the Transition to Water Resource Recovery Facilities: The Two Demonstration Case Studies of Corleone and Marineo (Italy)

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 156
Author(s):  
Giorgio Mannina ◽  
Luigi Badalucco ◽  
Lorenzo Barbara ◽  
Alida Cosenza ◽  
Daniele Di Trapani ◽  
...  
Keyword(s):  
Case Studies ◽  
Water Resource ◽  
Wastewater Treatment Plants ◽  
Ghg Emissions ◽  
Transition Process ◽  
Resource Recovery ◽  
Critical Issue ◽  
Pollutant Removal ◽  
Analysis Tool ◽  
Great Chance

The current exploitation of freshwater, as well as the significant increase in sewage sludge production from wastewater treatment plants (WWTPs), represent nowadays a critical issue for the implementation of sustainable development consistent with the circular economy concept. There is an urgent need to rethink the concept of WWTPs from the conventional approach consisting in pollutant removal plants to water resource recovery facilities (WRRFs). The aim of this paper is to provide an overview of the demonstration case studies at the Marineo and Corleone WRRFs in Sicily (IT), with the final aim showing the effectiveness of the resources recovery systems, as well as the importance of plant optimization to reduce greenhouse gas (GHG) emissions from WRRFs. This study is part of the H2020 European Project “Achieving wider uptake of water-smart solutions—Wider-Uptake”, which final aim is to demonstrate the water-smart solution feasibility in the wastewater sector. The main project goal is to overcome the existing barriers that hamper the transition to circularity through the implementation of a governance analysis tool. The preliminary actions in the two demonstration cases are first presented, while, subsequently, the water-smart solutions to be implemented are thoroughly described, highlighting their roles in the transition process. The achieved preliminary results underlined the significant potential of WRRF application, a great chance to demonstrate the feasibility of innovative solutions in the wastewater sector to overcome the existing social, administrative and technical barriers.

scholarly journals A Comparison of Life Cycle Energy and Carbon Impacts for Passive Detached Accessory Dwelling Units and Their Design Implications

2021 ◽  
Author(s):  
Deva Siva Veylan
Keyword(s):  
Life Cycle ◽  
Energy Use ◽  
Performance Metrics ◽  
Ghg Emissions ◽  
Energy Performance ◽  
Design Standards ◽  
Passive House ◽  
Accessory Dwelling Units ◽  
Passive Design ◽  
House Size

Detached accessory dwelling units are a building typology that, when built to passive design standards, can help reduce GHG emissions while addressing the socioeconomic pressures facing many housing markets. Energy performance metrics like those used in passive design standards are based on per unit of floor area and lead to a size-bias against smaller housing typologies. A life cycle assessment of cost-optimal passive house sizes ranging from 230 m² (2,500 ft²) to 30 m² (300 ft²) is performed to understand their total life cycle energy use and GHG emissions implications. Additionally, an analysis using BEopt examines operational energy use for 10 cost-optimal passive house sizes ranging from 230 m² (2,500 ft²) to 30 m² (300 ft²) across all 17 climate zones and examines how cost-optimal passive design changes with house size. The results show that per-occupant energy use and GHG emissions are similar or better for small house sizes and that cost-optimal passive design does not change significantly with house size.

scholarly journals An extended Kalman-filter for regional scale inverse emission estimation

2011 ◽  
Vol 11 (10) ◽  
pp. 29195-29249 ◽  
Author(s):  
D. Brunner ◽  
S. Henne ◽  
C. A. Keller ◽  
S. Reimann ◽  
M. K. Vollmer ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Dispersion Model ◽  
Regional Scale ◽  
Estimation Method ◽  
Particle Dispersion ◽  
Montreal Protocol ◽  
Correlated Noise ◽  
Temporal Correlations ◽  
Emission Estimation ◽  
Hfc 152A

Abstract. A Kalman-filter based inverse emission estimation method for long-lived trace gases is presented for use in conjunction with a Lagrangian particle dispersion model like FLEXPART. The sequential nature of the approach allows tracing slow seasonal and interannual changes rather than estimating a single period-mean emission field. Other important features include the estimation of a slowly varying concentration background at each measurement station, the possibility to constrain the solution to non-negative emissions, the quantification of uncertainties, the consideration of temporal correlations in the residuals, and the applicability to potentially large inversion problems. The method is first demonstrated for a set of synthetic observations created from a prescribed emission field with different levels of (correlated) noise, which closely mimics true observations. It is then applied to real observations of the three halocarbons HFC-125, HFC-152a and HCFC-141b at the remote research stations Jungfraujoch and Mace Head for the quantification of emissions in Western European countries from 2006 to 2010. Estimated HFC-125 emissions are mostly consistent with national totals reported to the Kyoto protocol and show a generally increasing trend over the considered period. Results for HFC-152a are much more variable with estimated emissions being both higher and lower in different countries. The highest emissions of the order of 1000 Mg yr−1 are estimated for Italy which so far does not report HFC-152a emissions. Emissions of HCFC-141b show a continuing strong decrease as expected due to its ban under the Montreal Protocol. Emissions from France, however, were still rather large (near 1000 Mg yr−1) in the years 2006 and 2007 but strongly declined thereafter.

Combined Trajectory Planning and Tracking for Autonomous Vehicles on Deformable Terrains

2020 ◽  
Author(s):  
James Dallas ◽  
Yifan Weng ◽  
Tulga Ersal
Keyword(s):  
Neural Network ◽  
Trajectory Planning ◽  
Autonomous Vehicles ◽  
Performance Metrics ◽  
Soft Soil ◽  
Computation Time ◽  
Operating Conditions ◽  
The Neural Network ◽  
Vehicle Response ◽  
The Impact

Abstract In this work, a novel combined trajectory planner and tracking controller is developed for autonomous vehicles operating on off-road deformable terrains. Common approaches to trajectory planning and tracking often rely on model-dependent schemes, which utilize a simplified model to predict the impact of control inputs to future vehicle response. However, in an off-road context and especially on deformable terrains, accurately modeling the vehicle response for predictive purposes can be challenging due to the complexity of the tire-terrain interaction and limitations of state-of-the-art terramechanics models in terms of operating conditions, computation time, and continuous differentiability. To address this challenge and improve vehicle safety and performance through more accurate prediction of the plant response, in this paper, a nonlinear model predictive control framework is presented that accounts for terrain deformability explicitly using a neural network terramechanics model for deformable terrains. The utility of the proposed scheme is demonstrated on high fidelity simulations for a notional lightweight military vehicle on soft soil. It is shown that the neural network based controller can outperform a baseline Pacejka model based scheme by improving on performance metrics associated with the cost function. In more severe maneuvers, the neural network based controller can achieve sufficient fidelity as compared to the plant to complete maneuvers that lead to failure for the Pacejka based controller. Finally, it is demonstrated that the proposed framework is conducive to real-time implementability.

Sign in / Sign up

Export Citation Format

Share Document