Search results for: optimized geometric
155 Biosorption of Nickel by Penicillium simplicissimum SAU203 Isolated from Indian Metalliferous Mining Overburden
Authors: Suchhanda Ghosh, A. K. Paul
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Nickel, an industrially important metal is not mined in India, due to the lack of its primary mining resources. But, the chromite deposits occurring in the Sukinda and Baula-Nuasahi region of Odhisa, India, is reported to contain around 0.99% of nickel entrapped in the goethite matrix of the lateritic iron rich ore. Weathering of the dumped chromite mining overburden often leads to the contamination of the ground as well as the surface water with toxic nickel. Microbes inherent to this metal contaminated environment are reported to be capable of removal as well as detoxification of various metals including nickel. Nickel resistant fungal isolates obtained in pure form from the metal rich overburden were evaluated for their potential to biosorb nickel by using their dried biomass. Penicillium simplicissimum SAU203 was the best nickel biosorbant among the 20 fungi tested and was capable to sorbing 16.85 mg Ni/g biomass from a solution containing 50 mg/l of Ni. The identity of the isolate was confirmed using 18S rRNA gene analysis. The sorption capacity of the isolate was further standardized following Langmuir and Freundlich adsorption isotherm models and the results reflected energy efficient sorption. Fourier-transform infrared spectroscopy studies of the nickel loaded and control biomass in a comparative basis revealed the involvement of hydroxyl, amine and carboxylic groups in Ni binding. The sorption process was also optimized for several standard parameters like initial metal ion concentration, initial sorbet concentration, incubation temperature and pH, presence of additional cations and pre-treatment of the biomass by different chemicals. Optimisation leads to significant improvements in the process of nickel biosorption on to the fungal biomass. P. simplicissimum SAU203 could sorb 54.73 mg Ni/g biomass with an initial Ni concentration of 200 mg/l in solution and 21.8 mg Ni/g biomass with an initial biomass concentration of 1g/l solution. Optimum temperature and pH for biosorption was recorded to be 30°C and pH 6.5 respectively. Presence of Zn and Fe ions improved the sorption of Ni(II), whereas, cobalt had a negative impact. Pre-treatment of biomass with various chemical and physical agents has affected the proficiency of Ni sorption by P. simplicissimum SAU203 biomass, autoclaving as well as treatment of biomass with 0.5 M sulfuric acid and acetic acid reduced the sorption as compared to the untreated biomass, whereas, NaOH and Na₂CO₃ and Twin 80 (0.5 M) treated biomass resulted in augmented metal sorption. Hence, on the basis of the present study, it can be concluded that P. simplicissimum SAU203 has the potential for the removal as well as detoxification of nickel from contaminated environments in general and particularly from the chromite mining areas of Odhisa, India.Keywords: nickel, fungal biosorption, Penicillium simplicissimum SAU203, Indian chromite mines, mining overburden
Procedia PDF Downloads 185154 Mapping Iron Content in the Brain with Magnetic Resonance Imaging and Machine Learning
Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher
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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping
Procedia PDF Downloads 126153 Management of Caverno-Venous Leakage: A Series of 133 Patients with Symptoms, Hemodynamic Workup, and Results of Surgery
Authors: Allaire Eric, Hauet Pascal, Floresco Jean, Beley Sebastien, Sussman Helene, Virag Ronald
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Background: Caverno-venous leakage (CVL) is devastating, although barely known disease, the first cause of major physical impairment in men under 25, and responsible for 50% of resistances to phosphodiesterase 5-inhibitors (PDE5-I), affecting 30 to 40% of users in this medication class. In this condition, too early blood drainage from corpora cavernosa prevents penile rigidity and penetration during sexual intercourse. The role of conservative surgery in this disease remains controversial. Aim: Assess complications and results of combined open surgery and embolization for CVL. Method: Between June 2016 and September 2021, 133 consecutive patients underwent surgery in our institution for CVL, causing severe erectile dysfunction (ED) resistance to oral medical treatment. Procedures combined vein embolization and ligation with microsurgical techniques. We performed a pre-and post-operative clinical (Erection Harness Scale: EHS) hemodynamic evaluation by duplex sonography in all patients. Before surgery, the CVL network was visualized by computed tomography cavernography. Penile EMG was performed in case of diabetes or suspected other neurological conditions. All patients were optimized for hormonal status—data we prospectively recorded. Results: Clinical signs suggesting CVL were ED since age lower than 25, loss of erection when changing position, penile rigidity varying according to the position. Main complications were minor pulmonary embolism in 2 patients, one after airline travel, one with Factor V Leiden heterozygote mutation, one infection and three hematomas requiring reoperation, one decreased gland sensitivity lasting for more than one year. Mean pre-operative pharmacologic EHS was 2.37+/-0.64, mean pharmacologic post-operative EHS was 3.21+/-0.60, p<0.0001 (paired t-test). The mean EHS variation was 0.87+/-0.74. After surgery, 81.5% of patients had a pharmacologic EHS equal to or over 3, allowing for intercourse with penetration. Three patients (2.2%) experienced lower post-operative EHS. The main cause of failure was leakage from the deep dorsal aspect of the corpus cavernosa. In a 14 months follow-up, 83.2% of patients had a clinical EHS equal to or over 3, allowing for sexual intercourse with penetration, one-third of them without any medication. 5 patients had a penile implant after unsuccessful conservative surgery. Conclusion: Open surgery combined with embolization for CVL is an efficient approach to CVL causing severe erectile dysfunction.Keywords: erectile dysfunction, cavernovenous leakage, surgery, embolization, treatment, result, complications, penile duplex sonography
Procedia PDF Downloads 142152 Radar on Bike: Coarse Classification based on Multi-Level Clustering for Cyclist Safety Enhancement
Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes
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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology
Procedia PDF Downloads 71151 A Systematic Analysis of Knowledge Development Trends in Industrial Maintenance Projects
Authors: Lilian Ogechi Iheukwumere-Esotu, Akilu Yunusa-Kaltungo, Paul Chan
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Industrial assets are prone to degradation and eventual failures due to repetitive loads and harsh environments in which they operate. These failures often lead to costly downtimes, which may involve loss of critical assets and/or human lives. The rising pressures from stakeholders for optimized systems’ outputs have further placed strains on business organizations. Traditional means of combating such failures are by adopting strategies capable of predicting, controlling, and/or reducing the likelihood of systems’ failures. Turnarounds, shutdowns, and outages (TSOs) projects are popular maintenance management activities conducted over a certain period of time. However, despite the critical and significant cost implications of TSOs, the management of the interface of knowledge between academia and industry to our best knowledge has not been fully explored in comparison to other aspects of industrial operations. This is perhaps one of the reasons for the limited knowledge transfer between academia and industry, which has affected the outcomes of most TSOs. Prior to now, the study of knowledge development trends as a failure analysis tool in the management of TSOs projects have not gained the required level of attention. Hence, this review provides useful references and their implications for future studies in this field. This study aims to harmonize the existing research trends of TSOs through a systematic review of more than 3,000 research articles published over 7 decades (1940- till date) which were extracted using very specific research criteria and later streamlined using nominated inclusion and exclusion parameters. The information obtained from the analysis were then synthesized and coded into 8 parameters, thereby allowing for a transformation into actionable outputs. The study revealed a variety of information, but the most critical findings can be classified into 4 folds: (1) Empirical validation of available conceptual frameworks and models is still a far cry in practice, (2) traditional project management views for managing uncertainties are still dominant, (3) Inconsistent approaches towards the adoption and promotion of knowledge management systems which supports creation, transfer and application of knowledge within and outside the project organization and, (4) exploration of social practices in industrial maintenance project environments are under-represented within the existing body of knowledge. Thus, the intention of this study is to depict the usefulness of a framework which incorporates fact findings emanating from careful analysis and illustrations of evidence based results as a suitable approach which can tackle reoccurring failures in industrial maintenance projects.Keywords: industrial maintenance, knowledge management, maintenance projects, systematic review, TSOs
Procedia PDF Downloads 113150 Functional Surfaces and Edges for Cutting and Forming Tools Created Using Directed Energy Deposition
Authors: Michal Brazda, Miroslav Urbanek, Martina Koukolikova
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This work focuses on the development of functional surfaces and edges for cutting and forming tools created through the Directed Energy Deposition (DED) technology. In the context of growing challenges in modern engineering, additive technologies, especially DED, present an innovative approach to manufacturing tools for forming and cutting. One of the key features of DED is its ability to precisely and efficiently deposit Fully dense metals from powder feedstock, enabling the creation of complex geometries and optimized designs. Gradually, it becomes an increasingly attractive choice for tool production due to its ability to achieve high precision while simultaneously minimizing waste and material costs. Tools created using DED technology gain significant durability through the utilization of high-performance materials such as nickel alloys and tool steels. For high-temperature applications, Nimonic 80A alloy is applied, while for cold applications, M2 tool steel is used. The addition of ceramic materials, such as tungsten carbide, can significantly increase the tool's resistance. The introduction of functionally graded materials is a significant contribution, opening up new possibilities for gradual changes in the mechanical properties of the tool and optimizing its performance in different sections according to specific requirements. In this work, you will find an overview of individual applications and their utilization in the industry. Microstructural analyses have been conducted, providing detailed insights into the structure of individual components alongside examinations of the mechanical properties and tool life. These analyses offer a deeper understanding of the efficiency and reliability of the created tools, which is a key element for successful development in the field of cutting and forming tools. The production of functional surfaces and edges using DED technology can result in financial savings, as the entire tool doesn't have to be manufactured from expensive special alloys. The tool can be made from common steel, onto which a functional surface from special materials can be applied. Additionally, it allows for tool repairs after wear and tear, eliminating the need for producing a new part and contributing to an overall cost while reducing the environmental footprint. Overall, the combination of DED technology, functionally graded materials, and verified technologies collectively set a new standard for innovative and efficient development of cutting and forming tools in the modern industrial environment.Keywords: additive manufacturing, directed energy deposition, DED, laser, cutting tools, forming tools, steel, nickel alloy
Procedia PDF Downloads 42149 Application of the Material Point Method as a New Fast Simulation Technique for Textile Composites Forming and Material Handling
Authors: Amir Nazemi, Milad Ramezankhani, Marian Kӧrber, Abbas S. Milani
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The excellent strength to weight ratio of woven fabric composites, along with their high formability, is one of the primary design parameters defining their increased use in modern manufacturing processes, including those in aerospace and automotive. However, for emerging automated preform processes under the smart manufacturing paradigm, complex geometries of finished components continue to bring several challenges to the designers to cope with manufacturing defects on site. Wrinklinge. g. is a common defectoccurring during the forming process and handling of semi-finished textile composites. One of the main reasons for this defect is the weak bending stiffness of fibers in unconsolidated state, causing excessive relative motion between them. Further challenges are represented by the automated handling of large-area fiber blanks with specialized gripper systems. For fabric composites forming simulations, the finite element (FE)method is a longstanding tool usedfor prediction and mitigation of manufacturing defects. Such simulations are predominately meant, not only to predict the onset, growth, and shape of wrinkles but also to determine the best processing condition that can yield optimized positioning of the fibers upon forming (or robot handling in the automated processes case). However, the need for use of small-time steps via explicit FE codes, facing numerical instabilities, as well as large computational time, are among notable drawbacks of the current FEtools, hindering their extensive use as fast and yet efficient digital twins in industry. This paper presents a novel woven fabric simulation technique through the application of the material point method (MPM), which enables the use of much larger time steps, facing less numerical instabilities, hence the ability to run significantly faster and efficient simulationsfor fabric materials handling and forming processes. Therefore, this method has the ability to enhance the development of automated fiber handling and preform processes by calculating the physical interactions with the MPM fiber models and rigid tool components. This enables the designers to virtually develop, test, and optimize their processes based on either algorithmicor Machine Learning applications. As a preliminary case study, forming of a hemispherical plain weave is shown, and the results are compared to theFE simulations, as well as experiments.Keywords: material point method, woven fabric composites, forming, material handling
Procedia PDF Downloads 177148 Dynamic Facades: A Literature Review on Double-Skin Façade with Lightweight Materials
Authors: Victor Mantilla, Romeu Vicente, António Figueiredo, Victor Ferreira, Sandra Sorte
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Integrating dynamic facades into contemporary building design is shaping a new era of energy efficiency and user comfort. These innovative facades, often constructed using lightweight construction systems and materials, offer an opportunity to have a responsive and adaptive nature to the dynamic behavior of the outdoor climate. Therefore, in regions characterized by high fluctuations in daily temperatures, the ability to adapt to environmental changes is of paramount importance and a challenge. This paper presents a thorough review of the state of the art on double-skin facades (DSF), focusing on lightweight solutions for the external envelope. Dynamic facades featuring elements like movable shading devices, phase change materials, and advanced control systems have revolutionized the built environment. They offer a promising path for reducing energy consumption while enhancing occupant well-being. Lightweight construction systems are increasingly becoming the choice for the constitution of these facade solutions, offering benefits such as reduced structural loads and reduced construction waste, improving overall sustainability. However, the performance of dynamic facades based on low thermal inertia solutions in climatic contexts with high thermal amplitude is still in need of research since their ability to adapt is traduced in variability/manipulation of the thermal transmittance coefficient (U-value). Emerging technologies can enable such a dynamic thermal behavior through innovative materials, changes in geometry and control to optimize the facade performance. These innovations will allow a facade system to respond to shifting outdoor temperature, relative humidity, wind, and solar radiation conditions, ensuring that energy efficiency and occupant comfort are both met/coupled. This review addresses the potential configuration of double-skin facades, particularly concerning their responsiveness to seasonal variations in temperature, with a specific focus on addressing the challenges posed by winter and summer conditions. Notably, the design of a dynamic facade is significantly shaped by several pivotal factors, including the choice of materials, geometric considerations, and the implementation of effective monitoring systems. Within the realm of double skin facades, various configurations are explored, encompassing exhaust air, supply air, and thermal buffering mechanisms. According to the review places a specific emphasis on the thermal dynamics at play, closely examining the impact of factors such as the color of the facade, the slat angle's dimensions, and the positioning and type of shading devices employed in these innovative architectural structures.This paper will synthesize the current research trends in this field, with the presentation of case studies and technological innovations with a comprehensive understanding of the cutting-edge solutions propelling the evolution of building envelopes in the face of climate change, namely focusing on double-skin lightweight solutions to create sustainable, adaptable, and responsive building envelopes. As indicated in the review, flexible and lightweight systems have broad applicability across all building sectors, and there is a growing recognition that retrofitting existing buildings may emerge as the predominant approach.Keywords: adaptive, control systems, dynamic facades, energy efficiency, responsive, thermal comfort, thermal transmittance
Procedia PDF Downloads 70147 Biostabilisation of Sediments for the Protection of Marine Infrastructure from Scour
Authors: Rob Schindler
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Industry-standard methods of mitigating erosion of seabed sediments rely on ‘hard engineering’ approaches which have numerous environmental shortcomings: (1) direct loss of habitat by smothering of benthic species, (2) disruption of sediment transport processes, damaging geomorphic and ecosystem functionality (3) generation of secondary erosion problems, (4) introduction of material that may propagate non-local species, and (5) provision of pathways for the spread of invasive species. Recent studies have also revealed the importance of biological cohesion, the result of naturally occurring extra-cellular polymeric substances (EPS), in stabilizing natural sediments. Mimicking the strong bonding kinetics through the deliberate addition of EPS to sediments – henceforth termed ‘biostabilisation’ - offers a means in which to mitigate against erosion induced by structures or episodic increases in hydrodynamic forcing (e.g. storms and floods) whilst avoiding, or reducing, hard engineering. Here we present unique experiments that systematically examine how biostabilisation reduces scour around a monopile in a current, a first step to realizing the potential of this new method of scouring reduction for a wide range of engineering purposes in aquatic substrates. Experiments were performed in Plymouth University’s recirculating sediment flume which includes a recessed scour pit. The model monopile was 0.048 m in diameter, D. Assuming a prototype monopile diameter of 2.0 m yields a geometric ratio of 41.67. When applied to a 10 m prototype water depth this yields a model depth, d, of 0.24 m. The sediment pit containing the monopile was filled with different biostabilised substrata prepared using a mixture of fine sand (D50 = 230 μm) and EPS (Xanthan gum). Nine sand-EPS mixtures were examined spanning EPS contents of 0.0% < b0 < 0.50%. Scour development was measured using a laser point gauge along a 530 mm centreline at 10 mm increments at regular periods over 5 h. Maximum scour depth and excavated area were determined at different time steps and plotted against time to yield equilibrium values. After 5 hours the current was stopped and a detailed scan of the final scour morphology was taken. Results show that increasing EPS content causes a progressive reduction in the equilibrium depth and lateral extent of scour, and hence excavated material. Very small amounts equating to natural communities (< 0.1% by mass) reduce scour rate, depth and extent of scour around monopiles. Furthermore, the strong linear relationships between EPS content, equilibrium scour depth, excavation area and timescales of scouring offer a simple index on which to modify existing scour prediction methods. We conclude that the biostabilisation of sediments with EPS may offer a simple, cost-effective and ecologically sensitive means of reducing scour in a range of contexts including OWFs, bridge piers, pipeline installation, and void filling in rock armour. Biostabilisation may also reduce economic costs through (1) Use of existing site sediments, or waste dredged sediments (2) Reduced fabrication of materials, (3) Lower transport costs, (4) Less dependence on specialist vessels and precise sub-sea assembly. Further, its potential environmental credentials may allow sensitive use of the seabed in marine protection zones across the globe.Keywords: biostabilisation, EPS, marine, scour
Procedia PDF Downloads 161146 Performance Analysis of Double Gate FinFET at Sub-10NM Node
Authors: Suruchi Saini, Hitender Kumar Tyagi
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With the rapid progress of the nanotechnology industry, it is becoming increasingly important to have compact semiconductor devices to function and offer the best results at various technology nodes. While performing the scaling of the device, several short-channel effects occur. To minimize these scaling limitations, some device architectures have been developed in the semiconductor industry. FinFET is one of the most promising structures. Also, the double-gate 2D Fin field effect transistor has the benefit of suppressing short channel effects (SCE) and functioning well for less than 14 nm technology nodes. In the present research, the MuGFET simulation tool is used to analyze and explain the electrical behaviour of a double-gate 2D Fin field effect transistor. The drift-diffusion and Poisson equations are solved self-consistently. Various models, such as Fermi-Dirac distribution, bandgap narrowing, carrier scattering, and concentration-dependent mobility models, are used for device simulation. The transfer and output characteristics of the double-gate 2D Fin field effect transistor are determined at 10 nm technology node. The performance parameters are extracted in terms of threshold voltage, trans-conductance, leakage current and current on-off ratio. In this paper, the device performance is analyzed at different structure parameters. The utilization of the Id-Vg curve is a robust technique that holds significant importance in the modeling of transistors, circuit design, optimization of performance, and quality control in electronic devices and integrated circuits for comprehending field-effect transistors. The FinFET structure is optimized to increase the current on-off ratio and transconductance. Through this analysis, the impact of different channel widths, source and drain lengths on the Id-Vg and transconductance is examined. Device performance was affected by the difficulty of maintaining effective gate control over the channel at decreasing feature sizes. For every set of simulations, the device's features are simulated at two different drain voltages, 50 mV and 0.7 V. In low-power and precision applications, the off-state current is a significant factor to consider. Therefore, it is crucial to minimize the off-state current to maximize circuit performance and efficiency. The findings demonstrate that the performance of the current on-off ratio is maximum with the channel width of 3 nm for a gate length of 10 nm, but there is no significant effect of source and drain length on the current on-off ratio. The transconductance value plays a pivotal role in various electronic applications and should be considered carefully. In this research, it is also concluded that the transconductance value of 340 S/m is achieved with the fin width of 3 nm at a gate length of 10 nm and 2380 S/m for the source and drain extension length of 5 nm, respectively.Keywords: current on-off ratio, FinFET, short-channel effects, transconductance
Procedia PDF Downloads 57145 Developing of Ecological Internal Insulation Composite Boards for Innovative Retrofitting of Heritage Buildings
Authors: J. N. Nackler, K. Saleh Pascha, W. Winter
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WHISCERS™ (Whole House In-Situ Carbon and Energy Reduction Solution) is an innovative process for Internal Wall Insulation (IWI) for energy-efficient retrofitting of heritage building, which uses laser measuring to determine the dimensions of a room, off-site insulation board cutting and rapid installation to complete the process. As part of a multinational investigation consortium the Austrian part adapted the WHISCERS system to local conditions of Vienna where most historical buildings have valuable stucco facades, precluding the application of an external insulation. The Austrian project contribution addresses the replacement of commonly used extruded polystyrene foam (XPS) with renewable materials such as wood and wood products to develop a more sustainable IWI system. As the timber industry is a major industry in Austria, a new innovative and more sustainable IWI solution could also open up new markets. The first approach of investigation was the Life Cycle Assessment (LCA) to define the performance of wood fibre board as insulation material in comparison to normally used XPS-boards. As one of the results the global-warming potential (GWP) of wood-fibre-board is 15 times less the equivalent to carbon dioxide while in the case of XPS it´s 72 times more. The hygrothermal simulation program WUFI was used to evaluate and simulate heat and moisture transport in multi-layer building components of the developed IWI solution. The results of the simulations prove in examined boundary conditions of selected representative brickwork constructions to be functional and usable without risk regarding vapour diffusion and liquid transport in proposed IWI. In a further stage three different solutions were developed and tested (1 - glued/mortared, 2 - with soft board, connected to wall with gypsum board as top layer, 3 - with soft board and clay board as top layer). All three solutions presents a flexible insulation layer out of wood fibre towards the existing wall, thus compensating irregularities of the wall surface. From first considerations at the beginning of the development phase, three different systems had been developed and optimized according to assembly technology and tested as small specimen in real object conditions. The built prototypes are monitored to detect performance and building physics problems and to validate the results of the computer simulation model. This paper illustrates the development and application of the Internal Wall Insulation system.Keywords: internal insulation, wood fibre, hygrothermal simulations, monitoring, clay, condensate
Procedia PDF Downloads 213144 Industrial Hemp Agronomy and Fibre Value Chain in Pakistan: Current Progress, Challenges, and Prospects
Authors: Saddam Hussain, Ghadeer Mohsen Albadrani
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Pakistan is one of the most vulnerable countries to climate change. Being a country where 23% of the country’s GDP relies on agriculture, this is a serious cause of concern. Introducing industrial hemp in Pakistan can help build climate resilience in the agricultural sector of the country, as hemp has recently emerged as a sustainable, eco-friendly, resource-efficient, and climate-resilient crop globally. Hemp has the potential to absorb huge amounts of CO₂, nourish the soil, and be used to create various biodegradable and eco-friendly products. Hemp is twice as effective as trees at absorbing and locking up carbon, with 1 hectare (2.5 acres) of hemp reckoned to absorb 8 to 22 tonnes of CO₂ a year, more than any woodland. Along with its high carbon-sequestration ability, it produces higher biomass and can be successfully grown as a cover crop. Hemp can grow in almost all soil conditions and does not require pesticides. It has fast-growing qualities and needs only 120 days to be ready for harvest. Compared with cotton, hemp requires 50% less water to grow and can produce three times higher fiber yield with a lower ecological footprint. Recently, the Government of Pakistan has allowed the cultivation of industrial hemp for industrial and medicinal purposes, making it possible for hemp to be reinserted into the country’s economy. Pakistan’s agro-climatic and edaphic conditions are well-suitable to produce industrial hemp, and its cultivation can bring economic benefits to the country. Pakistan can enter global markets as a new exporter of hemp products. The production of hemp in Pakistan can be most exciting to the workforce, especially for farmers participating in hemp markets. The minimum production cost of hemp makes it affordable to small holding farmers, especially those who need their cropping system to be as highly sustainable as possible. Dr. Saddam Hussain is leading the first pilot project of Industrial Hemp in Pakistan. In the past three years, he has been able to recruit high-impact research grants on industrial hemp as Principal Investigator. He has already screened the non-toxic hemp genotypes, tested the adaptability of exotic material in various agroecological conditions, formulated the production agronomy, and successfully developed the complete value chain. He has developed prototypes (fabric, denim, knitwear) using hemp fibre in collaboration with industrial partners and has optimized the indigenous fibre processing techniques. In this lecture, Dr. Hussain will talk on hemp agronomy and its complete fibre value chain. He will discuss the current progress, and will highlight the major challenges and future research direction on hemp research.Keywords: industrial hemp, agricultural sustainability, agronomic evaluation, hemp value chain
Procedia PDF Downloads 71143 Outcome-Based Education as Mediator of the Effect of Blended Learning on the Student Performance in Statistics
Authors: Restituto I. Rodelas
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The higher education has adopted the outcomes-based education from K-12. In this approach, the teacher uses any teaching and learning strategies that enable the students to achieve the learning outcomes. The students may be required to exert more effort and figure things out on their own. Hence, outcomes-based students are assumed to be more responsible and more capable of applying the knowledge learned. Another approach that the higher education in the Philippines is starting to adopt from other countries is blended learning. This combination of classroom and fully online instruction and learning is expected to be more effective. Participating in the online sessions, however, is entirely up to the students. Thus, the effect of blended learning on the performance of students in Statistics may be mediated by outcomes-based education. If there is a significant positive mediating effect, then blended learning can be optimized by integrating outcomes-based education. In this study, the sample will consist of four blended learning Statistics classes at Jose Rizal University in the second semester of AY 2015–2016. Two of these classes will be assigned randomly to the experimental group that will be handled using outcomes-based education. The two classes in the control group will be handled using the traditional lecture approach. Prior to the discussion of the first topic, a pre-test will be administered. The same test will be given as posttest after the last topic is covered. In order to establish equality of the groups’ initial knowledge, single factor ANOVA of the pretest scores will be performed. Single factor ANOVA of the posttest-pretest score differences will also be conducted to compare the performance of the experimental and control groups. When a significant difference is obtained in any of these ANOVAs, post hoc analysis will be done using Tukey's honestly significant difference test (HSD). Mediating effect will be evaluated using correlation and regression analyses. The groups’ initial knowledge are equal when the result of pretest scores ANOVA is not significant. If the result of score differences ANOVA is significant and the post hoc test indicates that the classes in the experimental group have significantly different scores from those in the control group, then outcomes-based education has a positive effect. Let blended learning be the independent variable (IV), outcomes-based education be the mediating variable (MV), and score difference be the dependent variable (DV). There is mediating effect when the following requirements are satisfied: significant correlation of IV to DV, significant correlation of IV to MV, significant relationship of MV to DV when both IV and MV are predictors in a regression model, and the absolute value of the coefficient of IV as sole predictor is larger than that when both IV and MV are predictors. With a positive mediating effect of outcomes-base education on the effect of blended learning on student performance, it will be recommended to integrate outcomes-based education into blended learning. This will yield the best learning results.Keywords: outcome-based teaching, blended learning, face-to-face, student-centered
Procedia PDF Downloads 285142 Cardiac Arrest after Cardiac Surgery
Authors: Ravshan A. Ibadov, Sardor Kh. Ibragimov
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Objective. The aim of the study was to optimize the protocol of cardiopulmonary resuscitation (CPR) after cardiovascular surgical interventions. Methods. The experience of CPR conducted on patients after cardiovascular surgical interventions in the Department of Intensive Care and Resuscitation (DIR) of the Republican Specialized Scientific-Practical Medical Center of Surgery named after Academician V. Vakhidov is presented. The key to the new approach is the rapid elimination of reversible causes of cardiac arrest, followed by either defibrillation or electrical cardioversion (depending on the situation) before external heart compression, which may damage sternotomy. Careful use of adrenaline is emphasized due to the potential recurrence of hypertension, and timely resternotomy (within 5 minutes) is performed to ensure optimal cerebral perfusion through direct massage. Out of 32 patients, cardiac arrest in the form of asystole was observed in 16 (50%), with hypoxemia as the cause, while the remaining 16 (50%) experienced ventricular fibrillation caused by arrhythmogenic reactions. The age of the patients ranged from 6 to 60 years. All patients were evaluated before the operation using the ASA and EuroSCORE scales, falling into the moderate-risk group (3-5 points). CPR was conducted for cardiac activity restoration according to the American Heart Association and European Resuscitation Council guidelines (Ley SJ. Standards for Resuscitation After Cardiac Surgery. Critical Care Nurse. 2015;35(2):30-38). The duration of CPR ranged from 8 to 50 minutes. The ARASNE II scale was used to assess the severity of patients' conditions after CPR, and the Glasgow Coma Scale was employed to evaluate patients' consciousness after the restoration of cardiac activity and sedation withdrawal. Results. In all patients, immediate chest compressions of the necessary depth (4-5 cm) at a frequency of 100-120 compressions per minute were initiated upon detection of cardiac arrest. Regardless of the type of cardiac arrest, defibrillation with a manual defibrillator was performed 3-5 minutes later, and adrenaline was administered in doses ranging from 100 to 300 mcg. Persistent ventricular fibrillation was also treated with antiarrhythmic therapy (amiodarone, lidocaine). If necessary, infusion of inotropes and vasopressors was used, and for the prevention of brain edema and the restoration of adequate neurostatus within 1-3 days, sedation, a magnesium-lidocaine mixture, mechanical intranasal cooling of the brain stem, and neuroprotective drugs were employed. A coordinated effort by the resuscitation team and proper role allocation within the team were essential for effective cardiopulmonary resuscitation (CPR). All these measures contributed to the improvement of CPR outcomes. Conclusion. Successful CPR following cardiac surgical interventions involves interdisciplinary collaboration. The application of an optimized CPR standard leads to a reduction in mortality rates and favorable neurological outcomes.Keywords: cardiac surgery, cardiac arrest, resuscitation, critically ill patients
Procedia PDF Downloads 48141 Intelligent Control of Agricultural Farms, Gardens, Greenhouses, Livestock
Authors: Vahid Bairami Rad
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The intelligentization of agricultural fields can control the temperature, humidity, and variables affecting the growth of agricultural products online and on a mobile phone or computer. Smarting agricultural fields and gardens is one of the best and best ways to optimize agricultural equipment and has a 100 percent direct effect on the growth of plants and agricultural products and farms. Smart farms are the topic that we are going to discuss today, the Internet of Things and artificial intelligence. Agriculture is becoming smarter every day. From large industrial operations to individuals growing organic produce locally, technology is at the forefront of reducing costs, improving results and ensuring optimal delivery to market. A key element to having a smart agriculture is the use of useful data. Modern farmers have more tools to collect intelligent data than in previous years. Data related to soil chemistry also allows people to make informed decisions about fertilizing farmland. Moisture meter sensors and accurate irrigation controllers have made the irrigation processes to be optimized and at the same time reduce the cost of water consumption. Drones can apply pesticides precisely on the desired point. Automated harvesting machines navigate crop fields based on position and capacity sensors. The list goes on. Almost any process related to agriculture can use sensors that collect data to optimize existing processes and make informed decisions. The Internet of Things (IoT) is at the center of this great transformation. Internet of Things hardware has grown and developed rapidly to provide low-cost sensors for people's needs. These sensors are embedded in IoT devices with a battery and can be evaluated over the years and have access to a low-power and cost-effective mobile network. IoT device management platforms have also evolved rapidly and can now be used securely and manage existing devices at scale. IoT cloud services also provide a set of application enablement services that can be easily used by developers and allow them to build application business logic. Focus on yourself. These development processes have created powerful and new applications in the field of Internet of Things, and these programs can be used in various industries such as agriculture and building smart farms. But the question is, what makes today's farms truly smart farms? Let us put this question in another way. When will the technologies associated with smart farms reach the point where the range of intelligence they provide can exceed the intelligence of experienced and professional farmers?Keywords: food security, IoT automation, wireless communication, hybrid lifestyle, arduino Uno
Procedia PDF Downloads 47140 Biorefinery as Extension to Sugar Mills: Sustainability and Social Upliftment in the Green Economy
Authors: Asfaw Gezae Daful, Mohsen Alimandagari, Kathleen Haigh, Somayeh Farzad, Eugene Van Rensburg, Johann F. Görgens
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The sugar industry has to 're-invent' itself to ensure long-term economic survival and opportunities for job creation and enhanced community-level impacts, given increasing pressure from fluctuating and low global sugar prices, increasing energy prices and sustainability demands. We propose biorefineries for re-vitalisation of the sugar industry using low value lignocellulosic biomass (sugarcane bagasse, leaves, and tops) annexed to existing sugar mills, producing a spectrum of high value platform chemicals along with biofuel, bioenergy, and electricity. Opportunity is presented for greener products, to mitigate climate change and overcome economic challenges. Xylose from labile hemicellulose remains largely underutilized and the conversion to value-add products a major challenge. Insight is required on pretreatment and/or extraction to optimize production of cellulosic ethanol together with lactic acid, furfural or biopolymers from sugarcane bagasse, leaves, and tops. Experimental conditions for alkaline and pressurized hot water extraction dilute acid and steam explosion pretreatment of sugarcane bagasse and harvest residues were investigated to serve as a basis for developing various process scenarios under a sugarcane biorefinery scheme. Dilute acid and steam explosion pretreatment were optimized for maximum hemicellulose recovery, combined sugar yield and solids digestibility. An optimal range of conditions for alkaline and liquid hot water extraction of hemicellulosic biopolymers, as well as conditions for acceptable enzymatic digestibility of the solid residue, after such extraction was established. Using data from the above, a series of energy efficient biorefinery scenarios are under development and modeled using Aspen Plus® software, to simulate potential factories to better understand the biorefinery processes and estimate the CAPEX and OPEX, environmental impacts, and overall viability. Rigorous and detailed sustainability assessment methodology was formulated to address all pillars of sustainability. This work is ongoing and to date, models have been developed for some of the processes which can ultimately be combined into biorefinery scenarios. This will allow systematic comparison of a series of biorefinery scenarios to assess the potential to reduce negative impacts on and maximize the benefits of social, economic, and environmental factors on a lifecycle basis.Keywords: biomass, biorefinery, green economy, sustainability
Procedia PDF Downloads 503139 Evaluating the Benefits of Intelligent Acoustic Technology in Classrooms: A Case Study
Authors: Megan Burfoot, Ali GhaffarianHoseini, Nicola Naismith, Amirhosein GhaffarianHoseini
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Intelligent Acoustic Technology (IAT) is a novel architectural device used in buildings to automatically vary the acoustic conditions of space. IAT is realized by integrating two components: Variable Acoustic Technology (VAT) and an intelligent system. The VAT passively alters the RT by changing the total sound absorption in a room. In doing so, the Reverberation Time (RT) is changed and thus, the sound strength and clarity are altered. The intelligent system detects sound waves in real-time to identify the aural situation, and the RT is adjusted accordingly based on pre-programmed algorithms. IAT - the synthesis of these two components - can dramatically improve acoustic comfort, as the acoustic condition is automatically optimized for any detected aural situation. This paper presents an evaluation of the improvements of acoustic comfort in an existing tertiary classroom located at Auckland University of Technology in New Zealand. This is a pilot case study, the first of its’ kind attempting to quantify the benefits of IAT. Naturally, the potential acoustic improvements from IAT can be actualized by only installing the VAT component of IAT and by manually adjusting it rather than utilizing an intelligent system. Such a simplified methodology is adopted for this case study to understand the potential significance of IAT without adopting a time and cost-intensive strategy. For this study, the VAT is built by overlaying reflective, rotating louvers over sound absorption panels. RT's are measured according to international standards before and after installing VAT in the classroom. The louvers are manually rotated in increments by the experimenter and further RT measurements are recorded. The results are compared with recommended guidelines and reference values from national standards for spaces intended for speech and communication. The results obtained from the measurements are used to quantify the potential improvements in classroom acoustic comfort, where IAT to be used. This evaluation reveals the current existence of poor acoustic conditions in the classroom caused by high RT's. The poor acoustics are also largely attributed to the classrooms’ inability to vary acoustic parameters for changing aural situations. The classroom experiences one static acoustic state, neglecting to recognize the nature of classrooms as flexible, dynamic spaces. Evidently, when using VAT the classroom is prescribed with a wide range of RTs it can achieve. Namely, acoustic requirements for varying teaching approaches are satisfied, and acoustic comfort is improved. By quantifying the benefits of using VAT, it can confidently suggest these same benefits are achieved with IAT. Nevertheless, it is encouraged that future studies continue this line of research toward the eventual development of IAT and its’ acceptance into mainstream architecture.Keywords: acoustic comfort, classroom acoustics, intelligent acoustics, variable acoustics
Procedia PDF Downloads 181138 Predicting Growth of Eucalyptus Marginata in a Mediterranean Climate Using an Individual-Based Modelling Approach
Authors: S.K. Bhandari, E. Veneklaas, L. McCaw, R. Mazanec, K. Whitford, M. Renton
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Eucalyptus marginata, E. diversicolor and Corymbia calophylla form widespread forests in south-west Western Australia (SWWA). These forests have economic and ecological importance, and therefore, tree growth and sustainable management are of high priority. This paper aimed to analyse and model the growth of these species at both stand and individual levels, but this presentation will focus on predicting the growth of E. Marginata at the individual tree level. More specifically, the study wanted to investigate how well individual E. marginata tree growth could be predicted by considering the diameter and height of the tree at the start of the growth period, and whether this prediction could be improved by also accounting for the competition from neighbouring trees in different ways. The study also wanted to investigate how many neighbouring trees or what neighbourhood distance needed to be considered when accounting for competition. To achieve this aim, the Pearson correlation coefficient was examined among competition indices (CIs), between CIs and dbh growth, and selected the competition index that can best predict the diameter growth of individual trees of E. marginata forest managed under different thinning regimes at Inglehope in SWWA. Furthermore, individual tree growth models were developed using simple linear regression, multiple linear regression, and linear mixed effect modelling approaches. Individual tree growth models were developed for thinned and unthinned stand separately. The developed models were validated using two approaches. In the first approach, models were validated using a subset of data that was not used in model fitting. In the second approach, the model of the one growth period was validated with the data of another growth period. Tree size (diameter and height) was a significant predictor of growth. This prediction was improved when the competition was included in the model. The fit statistic (coefficient of determination) of the model ranged from 0.31 to 0.68. The model with spatial competition indices validated as being more accurate than with non-spatial indices. The model prediction can be optimized if 10 to 15 competitors (by number) or competitors within ~10 m (by distance) from the base of the subject tree are included in the model, which can reduce the time and cost of collecting the information about the competitors. As competition from neighbours was a significant predictor with a negative effect on growth, it is recommended including neighbourhood competition when predicting growth and considering thinning treatments to minimize the effect of competition on growth. These model approaches are likely to be useful tools for the conservations and sustainable management of forests of E. marginata in SWWA. As a next step in optimizing the number and distance of competitors, further studies in larger size plots and with a larger number of plots than those used in the present study are recommended.Keywords: competition, growth, model, thinning
Procedia PDF Downloads 118137 Electronic Raman Scattering Calibration for Quantitative Surface-Enhanced Raman Spectroscopy and Improved Biostatistical Analysis
Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou
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Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration
Procedia PDF Downloads 133136 Optimization Principles of Eddy Current Separator for Mixtures with Different Particle Sizes
Authors: Cao Bin, Yuan Yi, Wang Qiang, Amor Abdelkader, Ali Reza Kamali, Diogo Montalvão
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The study of the electrodynamic behavior of non-ferrous particles in time-varying magnetic fields is a promising area of research with wide applications, including recycling of non-ferrous metals, mechanical transmission, and space debris. The key technology for recovering non-ferrous metals is eddy current separation (ECS), which utilizes the eddy current force and torque to separate non-ferrous metals. ECS has several advantages, such as low energy consumption, large processing capacity, and no secondary pollution, making it suitable for processing various mixtures like electronic scrap, auto shredder residue, aluminum scrap, and incineration bottom ash. Improving the separation efficiency of mixtures with different particle sizes in ECS can create significant social and economic benefits. Our previous study investigated the influence of particle size on separation efficiency by combining numerical simulations and separation experiments. Pearson correlation analysis found a strong correlation between the eddy current force in simulations and the repulsion distance in experiments, which confirmed the effectiveness of our simulation model. The interaction effects between particle size and material type, rotational speed, and magnetic pole arrangement were examined. It offer valuable insights for the design and optimization of eddy current separators. The underlying mechanism behind the effect of particle size on separation efficiency was discovered by analyzing eddy current and field gradient. The results showed that the magnitude and distribution heterogeneity of eddy current and magnetic field gradient increased with particle size in eddy current separation. Based on this, we further found that increasing the curvature of magnetic field lines within particles could also increase the eddy current force, providing a optimized method to improving the separation efficiency of fine particles. By combining the results of the studies, a more systematic and comprehensive set of optimization guidelines can be proposed for mixtures with different particle size ranges. The separation efficiency of fine particles could be improved by increasing the rotational speed, curvature of magnetic field lines, and electrical conductivity/density of materials, as well as utilizing the eddy current torque. When designing an ECS, the particle size range of the target mixture should be investigated in advance, and the suitable parameters for separating the mixture can be fixed accordingly. In summary, these results can guide the design and optimization of ECS, and also expand the application areas for ECS.Keywords: eddy current separation, particle size, numerical simulation, metal recovery
Procedia PDF Downloads 79135 Mesoporous BiVO4 Thin Films as Efficient Visible Light Driven Photocatalyst
Authors: Karolina Ordon, Sandrine Coste, Malgorzata Makowska-Janusik, Abdelhadi Kassiba
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Photocatalytic processes play key role in the production of a new source of energy (as hydrogen), design of self-cleaning surfaces or for the environment preservation. The most challenging task deals with the purification of water distinguished by high efficiency. In the mentioned process, organic pollutants in solutions are decomposed to the simple, non-toxic compounds as H2O and CO2. The most known photocatalytic materials are ZnO, CdS and TiO2 semiconductors with a particular involvement of TiO2 as an efficient photocatalysts even with a high band gap equal to 3.2 eV which exploit only UV radiation from solar emitted spectrum. However, promising material with visible light induced photoactivity was searched through the monoclinic polytype of BiVO4 which has energy gap about 2.4 eV. As required in heterogeneous photocatalysis, the high contact surface is required. Also, BiVO4 as photocatalyst can be optimized by increasing its surface area by achieving the mesoporous structure synthesize. The main goal of the present work consists in the synthesis and characterization of BiVO4 mesoporous thin film. The synthesis method based on sol-gel was carried out using a standard surfactants such as P123 and F127. The thin film was deposited by spin and dip coating method. Then, the structural analysis of the obtained material was performed thanks to X-ray diffraction (XRD) and Raman spectroscopy. The surface of resulting structure was investigated using a scanning electron microscopy (SEM). The computer simulations based on modeling the optical and electronic properties of bulk BiVO4 by using DFT (density functional theory) methodology were carried out. The semiempirical parameterized method PM6 was used to compute the physical properties of BiVO4 nanostructures. The Raman and IR absorption spectra were also measured for synthesized mesoporous material, and the results were compared with the theoretical predictions. The simulations of nanostructured BiVO4 have pointed out the occurrence of quantum confinement for nanosized clusters leading to widening of the band gap. This result overcame the relevance of nanosized objects to harvest wide part of the solar spectrum. Also, a balance was searched experimentally through the mesoporous nature of the films devoted to enhancing the contact surface as required for heterogeneous catalysis without to lower the nanocrystallite size under some critical sizes inducing an increased band gap. The present contribution will discuss the relevant features of the mesoporous films with respect to their photocatalytic responses.Keywords: bismuth vanadate, photocatalysis, thin film, quantum-chemical calculations
Procedia PDF Downloads 318134 Modification of Magneto-Transport Properties of Ferrimagnetic Mn₄N Thin Films by Ni Substitution and Their Magnetic Compensation
Authors: Taro Komori, Toshiki Gushi, Akihito Anzai, Taku Hirose, Kaoru Toko, Shinji Isogami, Takashi Suemasu
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Ferrimagnetic antiperovskite Mn₄₋ₓNiₓN thin film exhibits both small saturation magnetization and rather large perpendicular magnetic anisotropy (PMA) when x is small. Both of them are suitable features for application to current induced domain wall motion devices using spin transfer torque (STT). In this work, we successfully grew antiperovskite 30-nm-thick Mn₄₋ₓNiₓN epitaxial thin films on MgO(001) and STO(001) substrates by MBE in order to investigate their crystalline qualities and magnetic and magneto-transport properties. Crystalline qualities were investigated by X-ray diffraction (XRD). The magnetic properties were measured by vibrating sample magnetometer (VSM) at room temperature. Anomalous Hall effect was measured by physical properties measurement system. Both measurements were performed at room temperature. Temperature dependence of magnetization was measured by VSM-Superconducting quantum interference device. XRD patterns indicate epitaxial growth of Mn₄₋ₓNiₓN thin films on both substrates, ones on STO(001) especially have higher c-axis orientation thanks to greater lattice matching. According to VSM measurement, PMA was observed in Mn₄₋ₓNiₓN on MgO(001) when x ≤ 0.25 and on STO(001) when x ≤ 0.5, and MS decreased drastically with x. For example, MS of Mn₃.₉Ni₀.₁N on STO(001) was 47.4 emu/cm³. From the anomalous Hall resistivity (ρAH) of Mn₄₋ₓNiₓN thin films on STO(001) with the magnetic field perpendicular to the plane, we found out Mr/MS was about 1 when x ≤ 0.25, which suggests large magnetic domains in samples and suitable features for DW motion device application. In contrast, such square curves were not observed for Mn₄₋ₓNiₓN on MgO(001), which we attribute to difference in lattice matching. Furthermore, it’s notable that although the sign of ρAH was negative when x = 0 and 0.1, it reversed positive when x = 0.25 and 0.5. The similar reversal occurred for temperature dependence of magnetization. The magnetization of Mn₄₋ₓNiₓN on STO(001) increases with decreasing temperature when x = 0 and 0.1, while it decreases when x = 0.25. We considered that these reversals were caused by magnetic compensation which occurred in Mn₄₋ₓNiₓN between x = 0.1 and 0.25. We expect Mn atoms of Mn₄₋ₓNiₓN crystal have larger magnetic moments than Ni atoms do. The temperature dependence stated above can be explained if we assume that Ni atoms preferentially occupy the corner sites, and their magnetic moments have different temperature dependence from Mn atoms at the face-centered sites. At the compensation point, Mn₄₋ₓNiₓN is expected to show very efficient STT and ultrafast DW motion with small current density. What’s more, if angular momentum compensation is found, the efficiency will be best optimized. In order to prove the magnetic compensation, X-ray magnetic circular dichroism will be performed. Energy dispersive X-ray spectrometry is a candidate method to analyze the accurate composition ratio of samples.Keywords: compensation, ferrimagnetism, Mn₄N, PMA
Procedia PDF Downloads 129133 Thermoplastic-Intensive Battery Trays for Optimum Electric Vehicle Battery Pack Performance
Authors: Dinesh Munjurulimana, Anil Tiwari, Tingwen Li, Carlos Pereira, Sreekanth Pannala, John Waters
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With the rapid transition to electric vehicles (EVs) across the globe, car manufacturers are in need of integrated and lightweight solutions for the battery packs of these vehicles. An integral part of a battery pack is the battery tray, which constitutes a significant portion of the pack’s overall weight. Based on the functional requirements, cost targets, and packaging space available, a range of materials –from metals, composites, and plastics– are often used to develop these battery trays. This paper considers the design and development of integrated thermoplastic-intensive battery trays, using the available packaging space from a representative EV battery pack. Presented as a proposed alternative are multiple concepts to integrate several connected systems such as cooling plates and underbody impact protection parts of a multi-piece incumbent battery pack. The resulting digital prototype was evaluated for several mechanical performance measures such as mechanical shock, drop, crush resistance, modal analysis, and torsional stiffness. The performance of this alternative design is then compared with the incumbent solution. In addition, insights are gleaned into how these novel approaches can be optimized to meet or exceed the performance of incumbent designs. Preliminary manufacturing feasibility of the optimal solution using injection molding and other commonly used manufacturing methods for thermoplastics is briefly explained. Then numerical and analytical evaluations are performed to show a representative Pareto front of cost vs. volume of the production parts. The proposed solution is observed to offer weight savings of up to 40% on a component level and part elimination of up to two systems in the battery pack of a typical battery EV while offering the potential to meet the required performance measures highlighted above. These conceptual solutions are also observed to potentially offer secondary benefits such as improved thermal and electrical isolations and be able to achieve complex geometrical features, thus demonstrating the ability to use the complete packaging space available in the vehicle platform considered. The detailed study presented in this paper serves as a valuable reference for researches across the globe working on the development of EV battery packs – especially those with an interest in the potential of employing alternate solutions as part of a mixed-material system to help capture untapped opportunities to optimize performance and meet critical application requirements.Keywords: thermoplastics, lightweighting, part integration, electric vehicle battery packs
Procedia PDF Downloads 201132 Tool Development for Assessing Antineoplastic Drugs Surface Contamination in Healthcare Services and Other Workplaces
Authors: Benoit Atge, Alice Dhersin, Oscar Da Silva Cacao, Beatrice Martinez, Dominique Ducint, Catherine Verdun-Esquer, Isabelle Baldi, Mathieu Molimard, Antoine Villa, Mireille Canal-Raffin
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Introduction: Healthcare workers' exposure to antineoplastic drugs (AD) is a burning issue for occupational medicine practitioners. Biological monitoring of occupational exposure (BMOE) is an essential tool for assessing AD contamination of healthcare workers. In addition to BMOE, surface sampling is a useful tool in order to understand how workers get contaminated, to identify sources of environmental contamination, to verify the effectiveness of surface decontamination way and to ensure monitoring of these surfaces. The objective of this work was to develop a complete tool including a kit for surface sampling and a quantification analytical method for AD traces detection. The development was realized with the three following criteria: the kit capacity to sample in every professional environment (healthcare services, veterinaries, etc.), the detection of very low AD traces with a validated analytical method and the easiness of the sampling kit use regardless of the person in charge of sampling. Material and method: AD mostly used in term of quantity and frequency have been identified by an analysis of the literature and consumptions of different hospitals, veterinary services, and home care settings. The kind of adsorbent device, surface moistening solution and mix of solvents for the extraction of AD from the adsorbent device have been tested for a maximal yield. The AD quantification was achieved by an ultra high-performance liquid chromatography method coupled with tandem mass spectrometry (UHPLC-MS/MS). Results: With their high frequencies of use and their good reflect of the diverse activities through healthcare, 15 AD (cyclophosphamide, ifosfamide, doxorubicin, daunorubicin, epirubicin, 5-FU, dacarbazin, etoposide, pemetrexed, vincristine, cytarabine, methothrexate, paclitaxel, gemcitabine, mitomycin C) were selected. The analytical method was optimized and adapted to obtain high sensitivity with very low limits of quantification (25 to 5000ng/mL), equivalent or lowest that those previously published (for 13/15 AD). The sampling kit is easy to use, provided with a didactic support (online video and protocol paper). It showed its effectiveness without inter-individual variation (n=5/person; n= 5 persons; p=0,85; ANOVA) regardless of the person in charge of sampling. Conclusion: This validated tool (sampling kit + analytical method) is very sensitive, easy to use and very didactic in order to control the chemical risk brought by AD. Moreover, BMOE permits a focal prevention. Used in routine, this tool is available for every intervention of occupational health.Keywords: surface contamination, sampling kit, analytical method, sensitivity
Procedia PDF Downloads 125131 Classification Using Worldview-2 Imagery of Giant Panda Habitat in Wolong, Sichuan Province, China
Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding
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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2
Procedia PDF Downloads 308130 Utilization of Process Mapping Tool to Enhance Production Drilling in Underground Metal Mining Operations
Authors: Sidharth Talan, Sanjay Kumar Sharma, Eoin Joseph Wallace, Nikita Agrawal
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Underground mining is at the core of rapidly evolving metals and minerals sector due to the increasing mineral consumption globally. Even though the surface mines are still more abundant on earth, the scales of industry are slowly tipping towards underground mining due to rising depth and complexities of orebodies. Thus, the efficient and productive functioning of underground operations depends significantly on the synchronized performance of key elements such as operating site, mining equipment, manpower and mine services. Production drilling is the process of conducting long hole drilling for the purpose of charging and blasting these holes for the production of ore in underground metal mines. Thus, production drilling is the crucial segment in the underground metal mining value chain. This paper presents the process mapping tool to evaluate the production drilling process in the underground metal mining operation by dividing the given process into three segments namely Input, Process and Output. The three segments are further segregated into factors and sub-factors. As per the study, the major input factors crucial for the efficient functioning of production drilling process are power, drilling water, geotechnical support of the drilling site, skilled drilling operators, services installation crew, oils and drill accessories for drilling machine, survey markings at drill site, proper housekeeping, regular maintenance of drill machine, suitable transportation for reaching the drilling site and finally proper ventilation. The major outputs for the production drilling process are ore, waste as a result of dilution, timely reporting and investigation of unsafe practices, optimized process time and finally well fragmented blasted material within specifications set by the mining company. The paper also exhibits the drilling loss matrix, which is utilized to appraise the loss in planned production meters per day in a mine on account of availability loss in the machine due to breakdowns, underutilization of the machine and productivity loss in the machine measured in drilling meters per unit of percussion hour with respect to its planned productivity for the day. The given three losses would be essential to detect the bottlenecks in the process map of production drilling operation so as to instigate the action plan to suppress or prevent the causes leading to the operational performance deficiency. The given tool is beneficial to mine management to focus on the critical factors negatively impacting the production drilling operation and design necessary operational and maintenance strategies to mitigate them.Keywords: process map, drilling loss matrix, SIPOC, productivity, percussion rate
Procedia PDF Downloads 208129 Impact of Transitioning to Renewable Energy Sources on Key Performance Indicators and Artificial Intelligence Modules of Data Center
Authors: Ahmed Hossam ElMolla, Mohamed Hatem Saleh, Hamza Mostafa, Lara Mamdouh, Yassin Wael
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Artificial intelligence (AI) is reshaping industries, and its potential to revolutionize renewable energy and data center operations is immense. By harnessing AI's capabilities, we can optimize energy consumption, predict fluctuations in renewable energy generation, and improve the efficiency of data center infrastructure. This convergence of technologies promises a future where energy is managed more intelligently, sustainably, and cost-effectively. The integration of AI into renewable energy systems unlocks a wealth of opportunities. Machine learning algorithms can analyze vast amounts of data to forecast weather patterns, solar irradiance, and wind speeds, enabling more accurate energy production planning. AI-powered systems can optimize energy storage and grid management, ensuring a stable power supply even during intermittent renewable generation. Moreover, AI can identify maintenance needs for renewable energy infrastructure, preventing costly breakdowns and maximizing system lifespan. Data centers, which consume substantial amounts of energy, are prime candidates for AI-driven optimization. AI can analyze energy consumption patterns, identify inefficiencies, and recommend adjustments to cooling systems, server utilization, and power distribution. Predictive maintenance using AI can prevent equipment failures, reducing energy waste and downtime. Additionally, AI can optimize data placement and retrieval, minimizing energy consumption associated with data transfer. As AI transforms renewable energy and data center operations, modified Key Performance Indicators (KPIs) will emerge. Traditional metrics like energy efficiency and cost-per-megawatt-hour will continue to be relevant, but additional KPIs focused on AI's impact will be essential. These might include AI-driven cost savings, predictive accuracy of energy generation and consumption, and the reduction of carbon emissions attributed to AI-optimized operations. By tracking these KPIs, organizations can measure the success of their AI initiatives and identify areas for improvement. Ultimately, the synergy between AI, renewable energy, and data centers holds the potential to create a more sustainable and resilient future. By embracing these technologies, we can build smarter, greener, and more efficient systems that benefit both the environment and the economy.Keywords: data center, artificial intelligence, renewable energy, energy efficiency, sustainability, optimization, predictive analytics, energy consumption, energy storage, grid management, data center optimization, key performance indicators, carbon emissions, resiliency
Procedia PDF Downloads 14128 Accuracy of Computed Tomography Dose Monitor Values: A Multicentric Study in India
Authors: Adhimoolam Saravana Kumar, K. N. Govindarajan, B. Devanand, R. Rajakumar
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The quality of Computed Tomography (CT) procedures has improved in recent years due to technological developments and increased diagnostic ability of CT scanners. Due to the fact that CT doses are the peak among diagnostic radiology practices, it is of great significance to be aware of patient’s CT radiation dose whenever a CT examination is preferred. CT radiation dose delivered to patients in the form of volume CT dose index (CTDIvol) values, is displayed on scanner monitors at the end of each examination and it is an important fact to assure that this information is accurate. The objective of this study was to estimate the CTDIvol values for great number of patients during the most frequent CT examinations, to study the comparison between CT dose monitor values and measured ones, as well as to highlight the fluctuation of CTDIvol values for the same CT examination at different centres and scanner models. The output CT dose indices measurements were carried out on single and multislice scanners for available kV, 5 mm slice thickness, 100 mA and FOV combination used. The 100 CT scanners were involved in this study. Data with regard to 15,000 examinations in patients, who underwent routine head, chest and abdomen CT were collected using a questionnaire sent to a large number of hospitals. Out of the 15,000 examinations, 5000 were head CT examinations, 5000 were chest CT examinations and 5000 were abdominal CT examinations. Comprehensive quality assurance (QA) was performed for all the machines involved in this work. Followed by QA, CT phantom dose measurements were carried out in South India using actual scanning parameters used clinically by the hospitals. From this study, we have measured the mean divergence between the measured and displayed CTDIvol values were 5.2, 8.4, and -5.7 for selected head, chest and abdomen procedures for protocols as mentioned above, respectively. Thus, this investigation revealed an observable change in CT practices, with a much wider range of studies being performed currently in South India. This reflects the improved capacity of CT scanners to scan longer scan lengths and at finer resolutions as permitted by helical and multislice technology. Also, some of the CT scanners have used smaller slice thickness for routine CT procedures to achieve better resolution and image quality. It leads to an increase in the patient radiation dose as well as the measured CTDIv, so it is suggested that such CT scanners should select appropriate slice thickness and scanning parameters in order to reduce the patient dose. If these routine scan parameters for head, chest and abdomen procedures are optimized than the dose indices would be optimal and lead to the lowering of the CT doses. In South Indian region all the CT machines were routinely tested for QA once in a year as per AERB requirements.Keywords: CT dose index, weighted CTDI, volumetric CTDI, radiation dose
Procedia PDF Downloads 252127 Metalorganic Chemical Vapor Deposition Overgrowth on the Bragg Grating for Gallium Nitride Based Distributed Feedback Laser
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Laser diodes fabricated from the III-nitride material system are emerging solutions for the next generation telecommunication systems and optical clocks based on Ca at 397nm, Rb at 420.2nm and Yb at 398.9nm combined 556 nm. Most of the applications require single longitudinal optical mode lasers, with very narrow linewidth and compact size, such as communication systems and laser cooling. In this case, the GaN based distributed feedback (DFB) laser diode is one of the most effective candidates with gratings are known to operate with narrow spectra as well as high power and efficiency. Given the wavelength range, the period of the first-order diffraction grating is under 100 nm, and the realization of such gratings is technically difficult due to the narrow line width and the high quality nitride overgrowth based on the Bragg grating. Some groups have reported GaN DFB lasers with high order distributed feedback surface gratings, which avoids the overgrowth. However, generally the strength of coupling is lower than that with Bragg grating embedded into the waveguide within the GaN laser structure by two-step-epitaxy. Therefore, the overgrowth on the grating technology need to be studied and optimized. Here we propose to fabricate the fine step shape structure of first-order grating by the nanoimprint combined inductively coupled plasma (ICP) dry etching, then carry out overgrowth high quality AlGaN film by metalorganic chemical vapor deposition (MOCVD). Then a series of gratings with different period, depths and duty ratios are designed and fabricated to study the influence of grating structure to the nano-heteroepitaxy. Moreover, we observe the nucleation and growth process by step-by-step growth to study the growth mode for nitride overgrowth on grating, under the condition that the grating period is larger than the mental migration length on the surface. The AFM images demonstrate that a smooth surface of AlGaN film is achieved with an average roughness of 0.20 nm over 3 × 3 μm2. The full width at half maximums (FWHMs) of the (002) reflections in the XRD rocking curves are 278 arcsec for the AlGaN film, and the component of the Al within the film is 8% according to the XRD mapping measurement, which is in accordance with design values. By observing the samples with growth time changing from 200s, 400s to 600s, the growth model is summarized as the follow steps: initially, the nucleation is evenly distributed on the grating structure, as the migration length of Al atoms is low; then, AlGaN growth alone with the grating top surface; finally, the AlGaN film formed by lateral growth. This work contributed to carrying out GaN DFB laser by fabricating grating and overgrowth on the nano-grating patterned substrate by wafer scale, moreover, growth dynamics had been analyzed as well.Keywords: DFB laser, MOCVD, nanoepitaxy, III-niitride
Procedia PDF Downloads 178126 Comparative Analysis of Simulation-Based and Mixed-Integer Linear Programming Approaches for Optimizing Building Modernization Pathways Towards Decarbonization
Authors: Nico Fuchs, Fabian Wüllhorst, Laura Maier, Dirk Müller
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The decarbonization of building stocks necessitates the modernization of existing buildings. Key measures for this include reducing energy demands through insulation of the building envelope, replacing heat generators, and installing solar systems. Given limited financial resources, it is impractical to modernize all buildings in a portfolio simultaneously; instead, prioritization of buildings and modernization measures for a given planning horizon is essential. Optimization models for modernization pathways can assist portfolio managers in this prioritization. However, modeling and solving these large-scale optimization problems, often represented as mixed-integer problems (MIP), necessitates simplifying the operation of building energy systems particularly with respect to system dynamics and transient behavior. This raises the question of which level of simplification remains sufficient to accurately account for realistic costs and emissions of building energy systems, ensuring a fair comparison of different modernization measures. This study addresses this issue by comparing a two-stage simulation-based optimization approach with a single-stage mathematical optimization in a mixed-integer linear programming (MILP) formulation. The simulation-based approach serves as a benchmark for realistic energy system operation but requires a restriction of the solution space to discrete choices of modernization measures, such as the sizing of heating systems. After calculating the operation of different energy systems in terms of the resulting final energy demands in simulation models on a first stage, the results serve as input for a second stage MILP optimization, where the design of each building in the portfolio is optimized. In contrast to the simulation-based approach, the MILP-based approach can capture a broader variety of modernization measures due to the efficiency of MILP solvers but necessitates simplifying the building energy system operation. Both approaches are employed to determine the cost-optimal design and dimensioning of several buildings in a portfolio to meet climate targets within limited yearly budgets, resulting in a modernization pathway for the entire portfolio. The comparison reveals that the MILP formulation successfully captures design decisions of building energy systems, such as the selection of heating systems and the modernization of building envelopes. However, the results regarding the optimal dimensioning of heating technologies differ from the results of the two-stage simulation-based approach, as the MILP model tends to overestimate operational efficiency, highlighting the limitations of the MILP approach.Keywords: building energy system optimization, model accuracy in optimization, modernization pathways, building stock decarbonization
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