Renewable Energy Global Innovations features: Impact of flow field of hydrothermal jet drilling for geothermal wells in a confined cooling environment

Significance Statement

Geothermal energy is a resource potential with low carbo emission as well as widespread distribution. Geothermal resources are divided into hot dry rock and hydrothermal sources consistent with their naturally occurring states. Hydrothermal sources are exploited by extracting water, steam and gases contained in the reservoir. However, the hot dry rock is geothermal energy stored in underground hot and low permeable crystalline rocks generally located 3-10km deep.

The hot dry rock presents a potential indigenous resource that can provide heat and electric power. However, a feasible exploitation of geothermal energy counts on smooth drilling. The typical rotary drilling methods use bottom on the drill bit to crush rocks and a jointed drill string to elongate to the required depth. Unfortunately, in considerable deep hard rock formations, the contact between the rock and the bit, continuous tripping and making strong connections has resulted to drill bit abrasion, and consequently time consuming and costly drilling.

High-pressure water jet method uses water destructive energy to enhance rock removal rates. It has been adopted for assisting mechanical action to improve the rate of penetration in mining and petroleum recovery. However, the method is insufficient in breaking hard rock formations such as granite. Thermal spallation drilling on the other hand uses high temperature air or flame via combustion to heat rock surfaces causing high thermal stresses, which in turn induce fragmentation.

For deep wells drilling via a number of complicated formations, many rock assemblages do not spall, therefore impeding advancement in the course of thermal spallation drilling. To offset this shortcoming, researchers led by Professor Xianzhi Song from China University of Petroleum, China, proposed a new high temperature, high velocity jet drilling method based on high-pressure water jet drilling as well as thermal spallation approach. The approach is a contact-free technology, which implements a coiled tubing for continuous penetration. Their work is published in peer-reviewed journal, Geothermics.

In a bid to simplify the numerical simulation of the axisymmetric circular drilling model, the authors adopted 2-dimensional cross sections to represent the actual 3-dimensional setup. Consistent with the cooling configurations, the overall geometry model was divided into two regions. They included the well bottom along with the annulus.

The researchers set the wellbore length at 300mm in order to make sure the outcomes reflected the distribution regularities of the hydrothermal jet. The borehole and coiled tubing diameter were 50.8mm and 25.4mm respectively. Cooling water exit diameter was 10mm.

The authors analyzed the effects of jet velocity, cooling water velocity, jet temperature and standoff distance. They observed that impacting flow field of the jet on the bottom of the well was divided into the jet zone, return zone, and the eddy zone. Each of these zones had varying flow patterns. The temperature at the jet zone remained constant, but dropped in return and eddy zones. Temperature at wellbore was higher as compared to that around the tubing owing to return flow of water-cooling.

Jet velocity, standoff distance, and cooling water velocity posed significant effects on the bottom hole temperature and pressure. The researchers observed that the length of the potential core was correlated to the value of maximum axial velocity. Increasing jet velocity caused great pressure and temperature drop at the bottom of the well. Increasing cooling water velocity moderated bottom hole pressure drop. For this reason, the cooling water velocity needs to be designed in keeping with the optimal bottom hole pressure distribution requirements.

Reference

Xianzhi Song, Zehao Lv, Gensheng Li, Xiaodong Hu, Yu Shi. Numerical analysis on the impact of the flow field of hydrothermal jet drilling for geothermal wells in a confined cooling environment. Geothermics, volume 66 (2017), pages 39–49.

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Renewable Energy Global Innovations features: Probing the whole ore chalcopyrite–bacteria interactions and jarosite biosynthesis

Significance Statement

Chalcopyrite is considered the most abundant ore of copper sulfide. The ore has received significant attention owing to its vast ores with exploitation potential. Bioleaching that is environment friendly can be implemented for leaching copper ores employing sulfur and mesophilic oxidizing bacteria including Acidithiobacillus thiooxidans. The major oxidation product of chalcopyrite leaching has been found to be chalcocite that is further oxidized to yield covellite.

Chalcopyrite bioleaching initiates iron hydrosulfates precipitation coupled with metal-deficient layers that tend to minimize the entry of leaching components and bacteria to mineral surfaces. This in turn makes bioleaching inefficient. For this reason, finding a clarification of the approaches is necessary for optimizing chalcopyrite leaching and lessening the formation of jarosite passivation layers. Above all, researchers are yet to reach a consensus on the appropriate control procedures that must be followed in the bioleaching process.

Researchers led by professor Constantinos Varotsis from Cyprus University of Technology, Cyprus in collaboration with scientists at Hellenic Copper Mines, studied, for the first time, the formation of covellite from the bioleached surface of chalcopyrite, potassium, ammonia, ammonium ions, jarosites, and extracellular polymeric substances. They did the study in the microbial setting of the mines of copper. They applied FTIR micro-spectroscopies and Raman methods in a bid to establish a simple approach for assessing the formation of secondary minerals. Their work is published in peer-reviewed journal, Bioresource Technology.

The authors collected specimens from the copper mines of Hellenic and analyzed them by microscopy. They did bioleaching experiments in compact columns that were filled with solutions from the copper mines. The solutions contained microorganisms including Acidithiobacillus thiooxidans and Leptospirillum ferriphilum. They attached heating tapes around the testing columns in a bid to maintain the experiment at 35⁰C and this was done for four months. The authors performed infrared microscopies tests and collected Raman data.

The authors observed that the Raman spectra of chalcopyrite grain had a weak band of approximately 292cm^-1. In the spectra, this zone was obscured by light scattering because of focusing of the laser beam on the mineral surface, therefore, the authors were unable to detect this weak band. After one month of bioleaching, the authors recorded new bands of 469 and 226 cm^-1, which they assigned to Cu-S of covellite and FeO of K⁺ jarosite respectively.

At the end of two months of bioleaching, the authors recorded six more bands. However, by the end of the third month, they observed a drop in the intensity of the 469 cm^-1 band. This indicated that there was a drop in covellite concentration. However, at the fourth month, this band had disappeared altogether, and there was the formation of new marker bands.

From Raman data, the authors observed the formation of K⁺ Jarosite, which was then followed by NH₄⁺. They observed a color variation in the FTIR data, which indicated that microorganisms were attached on the surface of the mineral. A change in the intensity of the bands in the frequency range of 900-1140 cm^-1 confirmed the presence of biofilm conformations.

By analyzing the FTIR maker bands, the authors were able to understand the purpose of the extracellular polymeric substances to copper bioleaching.

Reference

Anastasia Adamou, Giorgos Manos, Nicholas Messios, Lazaros Georgiou, Constantinos Xydas, and Constantinos Varotsis. Probing the whole ore chalcopyrite–bacteria interactions and jarosite biosynthesis by Raman and FTIR micro spectroscopies. Bioresource Technology, volume 214 (2016), pages 852–855.

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Renewable Energy Global Innovations features: Copper yttrium selenide: A potential photovoltaic absorption material for solar cells

Significance Statement

The unique structural and photoelectric characteristics of copper based ternary and quaternary semiconductor compounds favors their wide applicability as absorption materials in thin film solar cells. Most research on this type of materials has focused mainly on group IIIA compounds of the periodic table. The polycrystalline compound Cu(In,Ga)Se₂ has yielded the highest conversion efficiency to date. However, indium and gallium are expensive due to their scarcity, thereby increasing the cost of production of solar cells and limiting their wide-scale applicability. Researchers have thus been coerced to seek for alternatives where the advantages of doping semiconductors such as copper yttrium selenide with rare earth elements has attracted their attention and presented an alternative. Yttrium is cheaper, more abundant and less toxic than both indium and gallium. So far, no report on the optoelectronic properties of the Copper yttrium selenide as an absorption material for solar cells has been presented.

 A team of researchers led by Professor Ruixin Ma at the University of Science and Technology in China proposed a study on the optoelectronic properties of copper yttrium selenide. They successfully synthesized the Copper yttrium selenide using self-propagating high temperature synthesis technique and measure its optoelectronic properties. Their work is now published in Materials and Design.

First, the research team synthesized the novel photovoltaic material: copper yttrium selenide, using a self-propagating high temperature synthesis method. The process had three stages and the optimum temperature of the copper yttrium selenide synthesis was 1016.2°C. The authors of this paper then characterized the crystalline morphology of the copper yttrium selenide using X-ray diffraction and field emission scanning electron microscopy. They then estimated the band gap of the copper yttrium selenide material based on the ultraviolet-visible spectroscopy spectrum of the material. A thin film of the copper yttrium selenide was prepared and used to determine the current-voltage properties.

The team noticed that the newly synthesized copper yttrium selenide exhibited outstanding absorption property in the visible light region. They also recorded the band gap to be 1.53 eV which is close to the optimal value for use in the solar cells. Most important of all, the copper yttrium selenide film used exhibited an exceptional photo-electron responsive behavior of a I_light/ I_dark  ratio of 2.81. This showed that the copper yttrium selenide was very suitable for use as an absorption material of thin film solar cells.

The work described herein presents and illustrates the novel copper yttrium selenide as a promising candidate for use as an absorption material in low cost and mass production fabrication of thin film solar cells. The success of copper yttrium selenide lengthens the list of available species of materials for use in low cost solar cells. 

Reference

Shina Li, Ruixin Ma, Xiaoyong Zhang, Xiang Li, Weishuang Zhao, Hongmin Zhu. Copper yttrium selenide: A potential photovoltaic absorption material for solar cellsMaterials and Design, volume 118 (2017) pages 163–167.

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Renewable Energy Global Innovations features: Low-Voltage Thermoelectric Energy Harvesting System for Wireless Sensor Nodes

Significance Statement

Thermal electric generators are solid state gadgets that are usually applied to convert heat flux directly into electrical energy through a phenomenon known as Seedbeck effect.  Among their applications include: in geothermal, power station, vehicle exhaust recovery and woodstoves. However, their relatively low efficiency when compared with typical conversion systems restrict their applications in large scale. Regardless, promising applications of the thermal electric generators have been found to be in small-scale applications, like the “self-powered” wireless sensor networks. In recent times, these wireless sensor networks have found wide scale applications but their power supply issue inhibit their usage. Herein, a thermoelectric energy harvesting system designed to harvest tens of microwatts to several miliwatts from low-voltage thermoelectric generators, based on a two-stage boost system with self-startup ability, has been proposed.

Researchers from Xiamen University and The Chinese University of Hong Kong led by Professor Wei-Hsin Liao proposed a study for a low-voltage thermoelectric energy harvesting and management system for powering wireless sensor nodes. The researchers aimed at developing a high efficiency boost converter system with self-startup ability for low-voltage thermoelectric generators for evaluation and comparison. Their research work is now published in the peer-reviewed journal, Energy Conversion and Management.

To begin with, the researchers combined a high-efficiency two-stage energy harvesting scheme working under normal working mode and a self-startup scheme working during self-startup in the energy harvesting system. They then applied the DCM mode and maximum power point tracking algorithm technique in the low-voltage converter for high efficiency. The maximum power point tracking technique intelligently adjusts the on/off times of the switches according to the open-circuit voltage of the thermal electric generators. The expressions of the optimal switching on/off times of the first-stage converter were derived. The research team then applied the low-power designs in switching mechanisms between the two energy harvesting schemes so as to reduce the quiescent power dissipation. Eventually, low power designs were applied to the MCU so as to reduce its power consumption and enhance the whole system’s efficiency.

From the experiments undertaken, the authors of this paper were able to observe that the first stage converter could achieve a high efficiency ranging 72% to approximately 87% for the thermal electric generators with open circuit voltage range of 62–400 mV to 1.255 V. For the low voltage starter, the energy harvesting system was observed to self-start from a low input voltage, as low as 20mV. Experimental results showed that with a 6.8 ohm thermal electric generators and an input voltage of 62 mV, the self-startup scheme would take 196.05 s to switch to two-stage harvesting scheme.

The empirical results obtained in their study suggest that when the wireless sensor network node sends signals every three minutes, the lowest open-circuit voltage for the energy harvesting system and wireless sensor network node to be self-powered is 62 mV, which is much lower than for the other converter used in the test. All in all, the whole system’s efficiency is much higher than the BQ25504 chip converter.

About The Author

Wei-Hsin Liao received his Ph.D. in Mechanical Engineering from The Pennsylvania State University, University Park, USA. Since August 1997, Dr. Liao has been with the Department of Mechanical and Automation Engineering at The Chinese University of Hong Kong (CUHK), where he is also the founding director of the Smart Materials and Structures Laboratory. Dr. Liao currently serves as the Associate Dean (Student Affairs), Faculty of Engineering. His research interests include smart materials and structures, energy harvesting, vibration control, mechatronics, and robotic exoskeleton.

Since 2000, he has been a member of the International Organizing Committee of the International Conference on Adaptive Structures and Technologies (ICAST). He was the Conference Chair for the 20th ICAST held in Hong Kong in 2009. He was also the Conference Chair of the Active and Passive Smart Structures and Integrated Systems, in the SPIE Smart Structures/NDE in 2014 and 2015. Dr. Liao has been a Principal Investigator of projects supported by the Hong Kong Research Grants Council and Innovation and Technology Commission, Hong Kong Special Administrative Region.

His research has led to publications of 200 technical papers in international journals and conference proceedings, 16 patents in US, China, Hong Kong, Taiwan, Japan, and Korea. He received the T A Stewart-Dyer/F H Trevithick Prize 2005, awarded by the Institution of Mechanical Engineers (IMechE). He is a recipient of the Best Paper Award in Structures (2008) and the Best Paper Award in Mechanics and Material Systems (2017) from the American Society of Mechanical Engineers (ASME). He also received the four Best Paper Awards in IEEE conferences. At CUHK, Prof. Liao was awarded the Research Excellence Award (2011) and Outstanding Fellow of the Faculty of Engineering (2014). As the Chair of Joint Chapter of Robotics, Automation and Control Systems Society (RACS), IEEE Hong Kong Section, Dr. Liao received 2012 Chapter of the Year Award from the IEEE Robotics and Automation Society.

He currently serves as an Associate Editor for Mechatronics, Journal of Intelligent Material Systems and Structures, as well as Smart Materials and Structures. Dr. Liao is a Fellow of ASME, HKIE, and IOP. 

Reference

Mingjie Guan, Kunpeng Wang, Dazheng Xu, Wei-Hsin Liao. Design and experimental investigation of a low-voltage thermoelectric energy harvesting system for wireless sensor nodes. Energy Conversion and Management, volume 138 (2017) pages 30–37.

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Renewable Energy Global Innovations features: Synthesis of inorganic-organic hybrid membranes consisting of organotrisiloxane linkages and their fuel cell properties

Significance Statement

Perfluorosulfonic polymers, for instance, Naflon, are preferable candidates for membranes used in polymer electrolyte fuel cells owing to their high proton conductivity, excellent mechanical strength, and chemical stability for temperatures below 100°C.  Nevertheless, the operating conditions need to be optimized to maintain 100% relative humidity at about 80 °C as well as low carbon-monoxide concentration in hydrogen gas. The functioning of polymer electrolyte fuel cells at higher temperatures raises the tolerance concentration of carbon monoxide poisoning for the platinum catalysts.

The increased operation temperature enhances the cell efficiency and simplifies the management system. For this reason, there is an urgent need for membrane electrolytes exhibiting high proton conductivities as well as intermediate temperatures. Inorganic-organic hybrid membranes possess the advantages of inorganic as well as organic phases. This is in the sense that functionality and flexibility of organics are blended with the thermal, mechanical, and chemical stability of inorganics. Therefore, the inorganic-organic hybrid membrane is preferable for implementation at intermediate temperatures.

Copolymerization of suitable monomers is a clear-cut approach for the formation of covalent bonds in the hybrid membranes. Researchers led by Professor Toshinobu Yogo at Nagoya University in Japan, demonstrated the one-pot synthesis of inorganic-organic hybrid membranes through copolymerization of N-vinylbenzotriazole, 1,5-divinyl-3-phenylpentamethyltrisiloxane, and 2-hydroxyethyl methacrylate acid phosphate. The research team did not require any hydrolysis-condensation for the preparation of the silicon-oxygen-silicon linkages reference to the fact that trisiloxane linkage was used for the inorganic backbone of the hybrid membrane. Their research work is published in Polymer.

The authors adopted the ac impedance method to measure proton conductivity of the hybrid membranes. They did this at various temperatures and relative humidity in a sealed vessel. They equilibrated the measurement cell at a desired relative humidity for one night at about 40 °C before measurement.

The Toshinobu Yogo and his team constructed inorganic-organic membranes from trisiloxane as well as aliphatic polymer chains bond with phosphonic acid groups, which were later copolymerized through one-pot method. The authors observed that the membranes were self-standing, possessed high thermal stability, high formability, and were homogeneous. The trisiloxane linkage in the hybrid membrane enhanced the thermal and oxidation stability of the membrane.

The hybrid membrane in the ratio 1:9:5 was found to have a high elastic modulus as compared to that of membranes with 2:8:5 and 3:7:5. The proton conductivity of the hybrid membranes was observed to rise with increasing temperature and relative humidity up to 130 °C. 1:9:5-ratio membrane was operated at 140 °C, 30% relative humidity for about 30 hours and indicated a peak power of about 7.8mWcm^-2 at 10 hours. Reference to chemical design, one-pot synthesis of the hybrid membranes is presented as a versatile synthetic process for the polymer electrolyte fuel cells used at low relative humidity as well as intermediate temperatures.

About The Author

Masaya Takemoto received his B. Eng. (2013) and M. Eng. (2015) degrees in crystalline materials chemistry from Nagoya University. His research interests include processing and characterization of energy and energy-saving materials. Currently, he is working for an energy-related company.

About The Author

Koichiro Hayashi received the B. Eng. (2005), M. Eng. (2007), and Dr. Eng. (2010) degrees in materials chemistry from Nagoya University. He worked as an assistant professor at the Tokushima University (2010-2014) and Nagoya University (2014-2017). Currently, he is an assistant professor at Kyushu University.

His interests include the development of multifunctional organic-inorganic nanomaterials and their applications to medical and dental fields.

About The Author

Shin-ichi Yamaura is an Associate Professor at The Polytechnic University of Japan since 2015. He received his PhD degree from Tohoku University, Sendai, Japan in 1999. He worked as an assistant professor and as an associate professor in the Institute for Materials Research, Tohoku University from 2000 to 2015.

His research interests include the preparation, process, characterization and functional property of amorphous/nanostructured alloys for hydrogen-related applications and also grain boundary engineering focused on grain boundary character that can be described as CSL Σ-value.

About The Author

Wei Zhang is a Professor in School of Materials Science and Engineering at Dalian University of Technology, China. He received his PhD degree from Tohoku University (Japan) in 1998. He has been a Lecturer at Dalian University of Technology, a research fellow at Japan Science and Technology Agency, and an associate professor in Institute for Materials Research, Tohoku University.

His research interests include the preparation, processes, characterization, and properties of amorphous and nanostructured alloys. He has published more than 290 articles including 7 book chapters.

About The Author

Wataru Sakamoto is an associate professor at Institute of Materials and Systems for Sustainability, Nagoya University. He received B.S. and M.S. degrees in applied chemistry from Nagoya University in 1989 and 1991, respectively. He worked from 1991 to 1994 at Matushita Electric Industrial (now Panasonic) Co., Ltd. He earned his Doctorate of Engineering from Nagoya University in 2000. He was appointed an associate professor in the Center for Integrated Research in Science and Engineering (now named Institute of Materials and Systems for Sustainability), Nagoya University, in February 2002. His research interests are novel processing and properties evaluation of electroceramics and functional nanostructured materials.

About The Author

Toshinobu Yogo is a professor at Institute of Materials and Systems for Sustainability, Nagoya University. He received B.S. and M.S. degrees in synthetic chemistry from Nagoya University.  He received his PhD degree from Hokkaido University (Japan) in 1980.

His research interests include the synthesis and characterization of functional nanomaterials and nano-structured hybrid materials.

Reference

Masaya Takemoto, Koichiro Hayashi, Shin-ichi Yamaura, Wei Zhang, Wataru Sakamoto, and Toshinobu Yogo. Synthesis of inorganic-organic hybrid membranes consisting of organotrisiloxane linkages and their fuel cell properties at intermediate temperatures. Polymer, volume 120 (2017), pages 264-271.

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Renewable Energy Global Innovations features: Big data framework for analytics in smart grids

Significance Statement

Recent technological advancements have led to a deluge of data originating from several domains, for instance, smart cities, the internet, scientific sensors, and social networks. Big data is a term that was incepted to cope with the ever-rising volume, velocity and variety of data. Big data are becoming the focus of many engineering and scientific domains. Big data systems include a number of tools and methods to acquire, store, and process data while leveraging the parallel processing power to undertake complex transformations as well as analysis.

The design and implementation of big data framework systems for a particular application is not a clear-cut mission. This is due to the fact that data is in multiple, autonomous and heterogeneous sources with complex and evolving relationships, and steadily grows. Above all, the rise of big data applications in cases where data collection has grown is beyond the capacity of the existing software and hardware platforms to manage, store, and process within an acceptable time.

Many utilities are adopting smart grid technology to form the basis of long range planning in a bid to improve power supply reliability, incorporate distributed generation resources, use power farms effectively, and enable users to engage in controlling how they use energy. To satisfy this, smart meters are being employed in many utilities as an initial step. This incorporation of smart meters results in significant increase in data which can be overwhelming if not managed appropriately. If this data is managed effectively, it can lead to a better understanding of customer behavior and help in promoting the stability of the smart grid.

Amr Munshi and Yasser Mohamed at The University of Alberta presented a new framework that could be used as a start for innovative research and take smart grids to the next level. They presented an implementation of the framework on a secure cloud-based platform. The framework was also applied on two scenarios in a bid to visualize the energy, for a single-house and a smart grid containing 6000 smart meters. Their research work is published in Electric Power Systems Research.

The authors implemented the framework on a secure IaaS cloud-based platform and presented relevant configurations as well as source codes. In addition, the authors presented interfaces between a number of component combinations that were able to communicate together. The framework was hosted on an IaaS Google cloud platform that presented an improved accessibility, and scalable infrastructure. They authors established a secure link between the framework’s cluster nodes through the Secure Shell protocol.

The implementation of the framework was applied to two scenarios: single-house with micro generators and a real smart metering electricity behavior data set for 6000 houses and businesses. However, the authors realized that the practical implementation of the framework together with the required configuration and coding, and application, could be helpful in the development of big data frameworks for other disciplines that could be profitable to businesses, promote the development of science and technology and enable sound decision making for government sectors.

About The Author

Amr A. Munshi received the B.Sc. degree in computer engineering from Umm Al-Qura University, Makkah, Saudi Arabia, in 2008, and the M.Sc. degree in computer engineering from the University of Alberta, Edmonton, AB, Canada, in 2014, where he is currently working towards the Ph.D. degree in electrical and computer engineering. His research interests include machine learning, data mining and big data analytics. Mr. Munshi is a Member of the Golden Key International Honor Society and serves as an Editor of the Alberta Academic Review Journal.

Reference

Amr A. Munshi and Yasser A.-R. I. Mohamed. Big data framework for analytics in smart grids. Electric Power Systems Research, volume 151 (2017), pages 369–380.

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Renewable Energy Global Innovations features: Hydrogen Production Methods in Accordance with Green Chemistry Principles

Significance Statement

The design of chemical products and adoption of processes that are more environmentally friendly, “Green Chemistry”, has gained considerable interest in recent years. Scholars opt to describe this as the application of the twelve principles of green chemistry in the design of chemical products and processes that reduce or eliminate the use or generation of hazardous substances. These principles include: waste prevention, atom economy, renewable feedstock’s, safer synthesis, safer products, atom economy, safer auxiliaries, pollution prevention, energy efficiency, renewable feedstock’s, safer synthesis, derivative reduction, catalysis, degradability, pollution prevention and accident prevention. Not only is the environmental concern discouraging the use of coal, natural gas and petroleum as the primary sources of energy, but also the increase in energy demand is inclining researchers to develop novel and current techniques that seek new energy sources.

Hydrogen is a promising future energy carrier since it is very important and environmentally friendly alternative to fossil fuels. It is also carbon free and henceforth carbon dioxide emission free. However, it can be generated from a wide array of fossil fuel and sustainable energy sources which consequently determine the type of emission that will occur. Various production methods such as: gasification, electrolysis and biological routes upon which some are not carbon dioxide free, others consume extreme chemicals, some use non-renewable resources while others have unknown life cycles are used in its production.

Researchers Dicle Celik and Meltem Yıldız at Kocaeli University in Turkey proposed a study that focused on terminating the dependency on non-renewable resources, waste reduction and increasing efficiency in hydrogen production processes and systems. Their main objective was to associate hydrogen production methods with the twelve principles of green chemistry. The purpose of their study was to determine which of the hydrogen production techniques provided the principles of green chemistry since the technique that provides the most of those principles has been deemed to be greener. Their research work is now published in International Journal of Hydrogen Energy.

Researchers begun the study of the fifteen different hydrogen production methods by grouping them into four main sub groups with respect to their input energy sources. The groups were electrical, thermal, hybrid and biological methods. The researchers then evaluated each of these techniques for the twelve principles of green chemistry.

Celik and Yıldız observed that among the electrical methods, electrolysis was a greener alternative to plasma arc dissociation. Also the comparison of the thermal methods showed that the best choice for the environment was the thermal decomposition method if only one clean energy was to be used. Such high temperatures in thermal decomposition could only be achieved using nuclear energy resources which is a contradictive topic. Therefore, biomass steam reforming or gasification could be an alternative. The two researchers also noted that among the hybrid systems, the best environmentally alternative method was the photo-electrochemical water splitting. Eventually, all biological methods were seen to be environmentally friendly since they use or mimic a natural pathway.

In an overview of the main hydrogen production processes, the work presented in their study show that water electrolysis among electrical methods, biomass gasification is carbon dioxide neutral among thermal methods, photo-electrochemical production among the hybrid methods and bio-photolysis and photo-fermentation among biological methods makes hydrogen production “green”. Therefore, in the near future, society should be able to produce hydrogen in agreement with the principles of green chemistry.

About The Author

Dr. Meltem YILDIZ  has completed her undergraduate  at Osmangazi University and received her PhD in 1999 from the Kocaeli University of Turkey. Her scientific interest is focused on renewable energy technologies, heterogeneous catalysts, green chemistry, clean production technologies. She is now Assistant Professor in Chemical Engineering Department, Kocaeli University, Turkey. She believes that the theme of “Green Chemistry” will be the most important work of humanity in the future.

About The Author

Dicle CELIK has completed her undergraduate study at Middle East Technical University and accredited as Chemical Engineer. After 5 years of work life, she missed being a part of university and started her graduate study at Kocaeli University Chemical Engineering Department. During her  graduate study, she introduced with the concept of Green Chemistry. She is now concentrated on catalysis, which is one of the principles of Green Chemistry. She heartily believes that putting positive contribution to the environment is a personal duty and applying principles of Green Chemistry is a great tool in this manner.

Reference

Dicle Celik, Meltem Yıldız. Investigation of hydrogen production methods in accordance with green chemistry principles. International journal of hydrogen energy, volume 42(2017) pages 23395-23401.

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Renewable Energy Global Innovations features: Analysis of rain-induced erosion in wind turbine blades

Significance Statement

In conjunction with the increasing interest in renewable energy as an alternative to fossil fuels, researchers have continually focused on wind energy industry in a bid to increase the power output of wind turbines. This has prompted production of more wind turbines with higher power output. Increasing the blade size is a primary method for enhancing the turbine’s power output which has resulted in blade tip velocities of up to 120m/s.

With the high blade tip velocities, high susceptibility to erosion comes in, particularly in harsh environments such as regions with heavy rain and hail. Rain erosion of the blades initiates with a consistent rise in the blade’s surface roughness until small pits form close to the leading edge. With time, the density of the resulting pits increase until gouges form. An increase in surface roughness of the blades translates to a rise in aerodynamic drag coefficient that consequently leads to low performance as well as energy loss.

University of Massachusetts Dartmouth researchers, led by Dr. Mazdak Tootkaboni from the department of civil engineering,  have recently published a two-part research paper on predicting rain erosion  in wind turbine blades. The aim of the research was to integrate well-established theories as well as computational models to come up with a framework that could approximate the expected erosion lifetime of a selected blade, given rainfall history at a particular region, blade shell attributes, and operational conditions of the wind turbine. These papers are published in the Journal of Wind Engineering and Industrial Aerodynamics.

As a first step, the research team developed a stochastic model of rain texture that was capable of relating the integral attributes of rain, for instance, rain intensity and average volume of water per unit volume of air to its micro-structural attributes including raindrop sizes as well as their spatial distribution. The model allowed for the reproduction of three-dimensional fields of raindrops.

Temporal and spatial variations of the impact pressure developed in  droplet-surface collision were then computed using a GPU accelerated CFD model of free surface flows. The authors proposed a multiresolution method in a bid to minimize computational cost and an interpolation scheme to compute the impact pressure profile for any drop size efficiently and accurately.

The final component of the proposed framework  entailed the computation of fatigue damage for every raindrop by undertaking a stress analysis of its collision with the coating surface and probabilistically integrating these fatigue damages to estimate the “expected” erosion life time of the coating. The authors computed the stresses through a finite element modeling of the drop impact, where the droplet impact pressure, already calculated from CFD analysis of rain drop impact on the coating surface, was applied on the surface as a spatially varying time dependent external load.

Ingredients of Computational Framework

About The Author

Dr. Mazdak Tootkaboni is an associate professor in the in the Department of Civil and Environmental Engineering at the University of Massachusetts Dartmouth. He holds a Ph.D. and a M.Sc. in Engineering Mechanics from the Johns Hopkins University. Dr Tootkaboni’s research interests include uncertainty quantification, stochastic computational mechanics, topology optimization, design under uncertainty, and design of multifunctional architected materials. Dr. Tootkaboni is also interested in the application of stochastic analysis, data Analytics, and machine learning techniques in predictive modeling in solid and structural mechanics.

About The Author

Behrooz Amirzadeh holds a M.Sc. degree in Mechanical Engineering from University of Massachusetts Dartmouth and a B.Sc. degree in Materials Science and Engineering from Sharif University of Technology in Tehran. During his time at UMass Dartmouth, his research was primarily focused on stochastic modeling and high performance computational simulation of fluid-structure interaction. He is currently working at RAID Inc in Andover, MA as a Senior HPC Solutions Architect helping scientists in national labs and universities design and deploy HPC clusters for next generation simulations research.

About The Author

Dr. Arghavan Louhghalam is an assistant professor in the Department of Civil and Environmental Engineering at the University of Massachusetts Dartmouth. Dr. Louhghalam holds a Ph.D. and a M.Sc. in Engineering Mechanics from the Johns Hopkins University and  prior to joining  University of Massachusetts, she was a postdoctoral research associate at Massachusetts Institute of Technology’s Concrete Sustainability Hub (CSHub@MIT). Dr. Louhghalam’s research interests are mainly focused on interconnected areas of solid mechanics, material modeling and applied statistics with applications to sustainability, durability and resilience of civil infrastructure as well as high-performance structures such as light weight high speed trains and wind-turbine blades.

About The Author

Dr. Mehdi Raessi is an associate professor in the Mechanical Engineering Department at the University of Massachusetts Dartmouth. His research interests include advanced computational simulations of multiphase flows with applications in energy systems (renewable and conventional), material processing, and microscale transport phenomena. Raessi has a PhD in mechanical engineering from the University of Toronto and was a Postdoctoral Fellow at NASA-Stanford University’s Center for Turbulence Research before joining UMASS-Dartmouth.

Reference

Amirzadeh, A. Louhghalam, M. Raessi, M. Tootkaboni. A computational framework for the analysis of rain-induced erosion in wind turbine blades, part I: Stochastic rain texture model and drop impact simulations. Journal of Wind Engineering & Industrial Aerodynamics, volume 163 (2017), pages 33–43.

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Amirzadeh, A. Louhghalam, M. Raessi, M. Tootkaboni. A computational framework for the analysis of rain-induced erosion in wind turbine blades, part II: Drop impact-induced stresses and blade coating fatigue life. Journal of Wind Engineering and Industrial Aerodynamics, Volume 163, (2017), Pages 44–54.

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Renewable Energy Global Innovations features: Ageing Assessment of a Wind Turbine Over Time by Interpreting Wind Farm SCADA Data

Significance Statement

The quest for green energy has motivated the world over to see the potential of wind as an important source of energy. The wind power industry is rapidly developing and therefore there is an increasing need to lower the Cost of Energy. Wind farms are being put up each day around the world in places of high wind energy potential so as to harness the renewable power of the wind. However, ageing of wind turbines and their components is inevitable. Over time, ageing will affect the reliability and power generation efficiency of the turbine. Therefore, performing an ageing assessment of the wind turbines is of significance so as to not only optimize the operation and maintenance strategy of the turbine, but also improve the management of the wind farm. Little has so far been done on this ageing led performance degradation concern of the turbine since most of the existing turbine monitoring techniques are mainly focused on condition monitoring for fault detection purposes.

An Innovative research was organized by Newcastle University in the UK, in collaboration with Hunan University of Science and Technology, Hunan Institute of Engineering, and XEMC Windpower Co. Ltd in China, to investigate the ageing issue of onshore wind turbines over time through interpreting the data collected by the wind farm Supervisory Control and Data Acquisition (SCADA) system. The research aimed at assessing the decline in performance of the turbines that could be directly attributed to their ageing. This research work is now published in the peer-reviewed journal, Renewable Energy.

The research team started by discussing the SCADA parameters that potentially could be used for the ageing assessment. The team then developed four ageing assessment criteria so as to describe the ageing issues of wind turbines from various viewpoints. From these, they were able to develop an innovative information fusion based ageing assessment method. Eventually, the effectiveness of the proposed method was verified using real SCADA data collected from an onshore wind farm.

The team observed that the values of the four ageing criteria deviated from 1. Since it is clear that during the turbines’ service life ageing will inevitably happen, the separate analysis of the individual ageing assessment criterion could not lead to reliable results regarding a turbines’ ageing effect. Therefore, the conventional individual assessment technique failed to yield reliable assessment results. However, the team noted that when the information fusion-based method was applied using the four ageing criteria, more realistic and acceptable results were obtained. The value of the information fusion based criterion was noted to deviate well from 1 in presence of ageing over time.

Herein, the conventional individual-based turbine age assessment method and the comprehensive information fusion-based method have been applied hand in hand. The latter technique exhibits reliability and robustness in assessing a turbines performance decline with age. It can therefore be recommended for use in such related works as its estimates from computations are quite reliable.

About The Author

Wenxian Yang has completed his PhD in 1999 from Xi’an Jiaotong University, China. Currently, He is the Lecturer of Offshore Renewable Energy of Newcastle University, United Kingdom. He has over 100 publications in top journals and peer-reviewed conferences. According to the statistics of Google Scholar, his publications have been cited over 1400 times since 2012, and his publication H-index is 20 and has been serving as an associate editor of IET Journal of Renewable Power Generation and the editorial board member of a number of reputed Journals.

Email: wenxian.yang@newcastle.ac.uk, Contact Number: +44 191-208-6171.

About The Author

Juchuan Dai received his PhD from Central South University (China) in 2011 and is a visiting scholar in Newcastle University (UK) in 2016. He is currently an associate professor in Hunan university of Science and Technology (China). He is the person in charge of the project of the National Natural Science Foundation of People’s Republic of China. His main research interest is wind power technology and equipment, also is reviewer for many international academic journals.

Email: daijuchuan@163.com

About The Author

Deshun Liu received his PhD from Central South University (China) in 1996 and is a visiting scholar in University of Missouri-Rolla in 2004. He is currently a professor in Hunan university of Science and Technology (China). He is the person in charge of the project of the National Natural Science Foundation of People’s Republic of China. He has over 100 publications in journals and peer-reviewed conferences.  His main research interest is wind power technology and equipment, also is reviewer for many international academic journals.

Email: deshunliu@hnust.edu.cn

About The Author

Xin Long is currently the chief expert of XEMC Wind Power Cooperation. He has been the person in charge of the project of the National High Technology Research and Development Program  (“863” Program) of China. He has long been engaged in the design and R & D of large wind turbines, and has rich experience in actual product research and development.

Email: lx@xemc-wind.cn

About The Author

Junwei Cao received his master’s degree from Hunan University of Science and Technology (China) in 2016. He works as an engineer in XEMC Wind Power Cooperation after graduation. His main research interest is wind power technology and currently engaged in data analysis work.

Email: caojunwei@xemc-wind.cn

Reference

Juchuan Dai, Wenxian Yang, Junwei Cao, Deshun Liu, Xing Long. Ageing assessment of a wind turbine over time by interpreting wind farm SCADA data. Renewable Energy, Available online 31 March 2017.

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