The Experts below are selected from a list of 55341 Experts worldwide ranked by ideXlab platform
R Sakthivel - One of the best experts on this subject based on the ideXlab platform.
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multi attribute decision making approach for aegle marmelos pyrolysis process using topsis and grey relational analysis assessment of engine emissions through novel infrared thermography
Journal of Cleaner Production, 2019Co-Authors: P Baranitharan, K Ramesh, R SakthivelAbstract:Abstract This research focuses on the selection of the optimum process parameters for Aegel marmelos (AM) pyrolysis experiment based on multi-objective decision-making techniques. This investigation presents the Optimization Report for obtaining maximum pyrolysis oil from AM de-oiled seed cake through thermochemical conversion (pyrolysis) process. The pyrolysis process has been conducted according to L27 orthogonal array with chosen input control factors such as pyrolysis temperature (°C), heating rate (°C/min) and biomass particle size (mm). The output response parameters measured are the bio-oil yield, bio-char yield and biogas yield. The multi-objective decision-making approach namely Technique for order preference by similarity to ideal solution (TOPSIS) and Grey relational analysis (GRA) techniques are employed to determine the optimum pyrolysis process parameters to maximize the yield of AM bio-oil. The optimized values of pyrolysis temperature (PT), heating rate (HR) and feedstock particle size (PS) are 600 °C, 10 °C/min and 0.6 mm. At peak engine loading condition, 20% AM bio-oil + 80% diesel fuel blend (AM20) emit lower carbon dioxide (CO2 = 8.68%) and oxides of nitrogen (NOx = 1401 ppm) emissions as compared with diesel (D) CO2 (10.33%) and NOx (1511 ppm) emissions. The association between exhaust gas temperature and NOx emission was inferred using a novel approach of thermal imager by sensing the infrared rays from the hot surface of the exhaust port. Infrared thermal images are captured during the engine operations fuelled with bio-oil at the optimum pyrolysis conditions concluded by TOPSIS and GRA results (PT = 600 °C, HR = 10 °C/min and PS = 0.6 mm). According to the thermal imaging result, AM20 blend produces the lower amount of NOx emissions compared with neat diesel and it is suggested that AM bio-oil can be used as engine fuel instead in order to preserve the eco-system stability and biodiversity.
Olis D. - One of the best experts on this subject based on the ideXlab platform.
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Renewable Energy Optimization Report for Naval Station Newport
National Renewable Energy Laboratory (U.S.), 2012Co-Authors: Robichaud R., Mosey G., Olis D.Abstract:In 2008, the U.S. Environmental Protection Agency (EPA) launched the RE-Powering America's Land initiative to encourage the development of renewable energy (RE) on potentially contaminated land and mine sites. As part of this effort, EPA is collaborating with the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) to evaluate RE options at Naval Station (NAVSTA) Newport in Newport, Rhode Island. NREL's Renewable Energy Optimization (REO) tool was utilized to identify RE technologies that present the best opportunity for life-cycle cost-effective implementation while also serving to reduce energy-related carbon dioxide emissions and increase the percentage of RE used at NAVSTA Newport. The technologies included in REO are daylighting, wind, solar ventilation preheating (SVP), solar water heating, photovoltaics (PV), solar thermal (heating and electric), and biomass (gasification and cogeneration). The optimal mix of RE technologies depends on several factors including RE resources; technology cost and performance; state, utility, and federal incentives; and economic parameters (discount and inflation rates). Each of these factors was considered in this analysis. Technologies not included in REO that were investigated separately per NAVSTA Newport request include biofuels from algae, tidal power, and ground source heat pumps (GSHP)
Joaquim R. R. A. Martins - One of the best experts on this subject based on the ideXlab platform.
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Advancing the Design of Complex Engineered Systems through Multidisciplinary Design Optimization: Report from an NSF Workshop
53rd AIAA ASME ASCE AHS ASC Structures Structural Dynamics and Materials Conference<BR>20th AIAA ASME AHS Adaptive Structures Conference<BR&g, 2012Co-Authors: Timothy W. Simpson, Joaquim R. R. A. MartinsAbstract:Multidisciplinary design Optimization (MDO) has evolved remarkably since its inception 25 years ago. Despite these advances, the design of complex engineered systems remains a challenge, and many large-scale engineering projects are routinely plagued by exorbitant cost overruns and delays. To gain insight into these challenges, we organized a workshop that gathered 48 people from industry, academia, and government agencies to examine MDO’s current and future role in designing complex engineered systems. This presentation summarizes the views of five distinguished speakers on the state of the research along with the discussions from an industry panel of representatives from Boeing, Caterpillar, Ford, NASA Glenn Research Center, and United Technologies Research Center on the state of the practice. This presentation also summarizes the future research topics identified by breakout groups in five key areas: (1) modeling and the design space; (2) metrics, objectives, and requirements; (3) coupling in complex engineered systems; (4) dealing with uncertainty; and (5) people and workflow. Finally, five over-arching themes are offered to advance MDO. First, we need to engage more disciplines outside of engineering and look for opportunities to use MDO outside of its traditional areas. Second, MDO problem formulations must evolve to encompass a wider range of design criteria. Third, we need effective strategies for putting designers “back in the loop” during MDO. Fourth, we need to do a better job of publicizing the successful examples of MDO so that we can improve the “buy in” that is needed to advance MDO in academia, industry, and government agencies. Fifth, we need to better educate our students and practitioners on systems design, Optimization and MDO, along with its benefits and drawbacks.
P Baranitharan - One of the best experts on this subject based on the ideXlab platform.
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multi attribute decision making approach for aegle marmelos pyrolysis process using topsis and grey relational analysis assessment of engine emissions through novel infrared thermography
Journal of Cleaner Production, 2019Co-Authors: P Baranitharan, K Ramesh, R SakthivelAbstract:Abstract This research focuses on the selection of the optimum process parameters for Aegel marmelos (AM) pyrolysis experiment based on multi-objective decision-making techniques. This investigation presents the Optimization Report for obtaining maximum pyrolysis oil from AM de-oiled seed cake through thermochemical conversion (pyrolysis) process. The pyrolysis process has been conducted according to L27 orthogonal array with chosen input control factors such as pyrolysis temperature (°C), heating rate (°C/min) and biomass particle size (mm). The output response parameters measured are the bio-oil yield, bio-char yield and biogas yield. The multi-objective decision-making approach namely Technique for order preference by similarity to ideal solution (TOPSIS) and Grey relational analysis (GRA) techniques are employed to determine the optimum pyrolysis process parameters to maximize the yield of AM bio-oil. The optimized values of pyrolysis temperature (PT), heating rate (HR) and feedstock particle size (PS) are 600 °C, 10 °C/min and 0.6 mm. At peak engine loading condition, 20% AM bio-oil + 80% diesel fuel blend (AM20) emit lower carbon dioxide (CO2 = 8.68%) and oxides of nitrogen (NOx = 1401 ppm) emissions as compared with diesel (D) CO2 (10.33%) and NOx (1511 ppm) emissions. The association between exhaust gas temperature and NOx emission was inferred using a novel approach of thermal imager by sensing the infrared rays from the hot surface of the exhaust port. Infrared thermal images are captured during the engine operations fuelled with bio-oil at the optimum pyrolysis conditions concluded by TOPSIS and GRA results (PT = 600 °C, HR = 10 °C/min and PS = 0.6 mm). According to the thermal imaging result, AM20 blend produces the lower amount of NOx emissions compared with neat diesel and it is suggested that AM bio-oil can be used as engine fuel instead in order to preserve the eco-system stability and biodiversity.
Robichaud R. - One of the best experts on this subject based on the ideXlab platform.
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Renewable Energy Optimization Report for Naval Station Newport
National Renewable Energy Laboratory (U.S.), 2012Co-Authors: Robichaud R., Mosey G., Olis D.Abstract:In 2008, the U.S. Environmental Protection Agency (EPA) launched the RE-Powering America's Land initiative to encourage the development of renewable energy (RE) on potentially contaminated land and mine sites. As part of this effort, EPA is collaborating with the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) to evaluate RE options at Naval Station (NAVSTA) Newport in Newport, Rhode Island. NREL's Renewable Energy Optimization (REO) tool was utilized to identify RE technologies that present the best opportunity for life-cycle cost-effective implementation while also serving to reduce energy-related carbon dioxide emissions and increase the percentage of RE used at NAVSTA Newport. The technologies included in REO are daylighting, wind, solar ventilation preheating (SVP), solar water heating, photovoltaics (PV), solar thermal (heating and electric), and biomass (gasification and cogeneration). The optimal mix of RE technologies depends on several factors including RE resources; technology cost and performance; state, utility, and federal incentives; and economic parameters (discount and inflation rates). Each of these factors was considered in this analysis. Technologies not included in REO that were investigated separately per NAVSTA Newport request include biofuels from algae, tidal power, and ground source heat pumps (GSHP)