Search results for: irrigationaxial flux machines

Authors: Jasim Uddin, Rod Smith, Malcolm Gillies

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Surface irrigation is the most popular irrigation method all over the world. However, two issues: low efficiency and huge labour involvement concern irrigators due to scarcity in recent years. To address these issues, a smart automated furrow is conceptualised that can be operated using digital devices like smartphone, iPad or computer and a preliminary evaluation was conducted in this study. The smart automated system is the integration of commercially available software and hardware. It includes real-time surface irrigation optimisation software (SISCO) and Rubicon Water’s surface irrigation automation hardware and software. The automated system consists of automatic water delivery system with 300 mm flexible pipes attached to both sides of a remotely controlled valve to operate the irrigation. A water level sensor to obtain the real-time inflow rate from the measured head in the channel, advance sensors to measure the advance time to particular points of an irrigated field, a solar-powered telemetry system including a base station to communicate all the field sensors with the main server. On the basis of field data, the software (SISCO) is optimised the ongoing irrigation and determine the optimum cut-off for particular irrigation and send this information to the control valve to stop the irrigation in a particular (cut-off) time. The preliminary evaluation shows that the automated surface irrigation worked reasonably well without manual intervention. The evaluation of farmers managed irrigation events show the potentials to save a significant amount of water and labour. A substantial amount of economic and social benefits are expected in rural industries by adopting this system. The future outcome of this work would be a fully tested commercial adaptive real-time furrow irrigation system able to compete with the pressurised alternative of centre pivot or lateral move machines on capital cost, water and labour savings but without the massive energy costs.

Keywords: furrow irrigation, smart automation, infiltration, SISCO, real-time irrigation, adoptive control

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Authors: You-Kai Jhang, Yang-Cheng Lu

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Major contributions of this study are threefold: designing a new model of planar-membrane humidifier for Proton Exchange Membrane Fuel Cell (PEMFC), an index to measure the Effectiveness (εT) of that humidifier, and an air compressor system to replicate related planar-membrane humidifier experiments. PEMFC as a kind of renewable energy has become more and more important in recent years due to its reliability and durability. To maintain the efficiency of the fuel cell, the membrane of PEMFC need to be controlled in a good hydration condition. How to maintain proper membrane humidity is one of the key issues to optimize PEMFC. We developed new humidifier to recycle water vapor from cathode air outlet so as to keep the moisture content of cathode air inlet in a PEMFC. By measuring parameters such as dry side air outlet dew point temperature, dry side air inlet temperature and humidity, wet side air inlet temperature and humidity, and differential pressure between dry side and wet side, we calculated indices obtained by dew point approach temperature (DPAT), water flux (J), water recovery ratio (WRR), effectiveness (εT), and differential pressure (ΔP). We discussed six topics including sealing effect, flow rate effect, flow direction effect, channel effect, temperature effect, and humidity effect by using these indices. Gas cylinders are used as sources of air supply in many studies of humidifiers. Gas cylinder depletes quickly during experiment at 1kW air flow rate, and it causes replication difficult. In order to ensure high stable air quality and better replication of experimental data, this study designs an air supply system to overcome this difficulty. The experimental result shows that the best rate of pressure loss of humidifier is 0.133×10³ Pa(g)/min at the torque of 25 (N.m). The best humidifier performance ranges from 30-40 (LPM) of air flow rates. The counter flow configured humidifies moisturizes the dry side inlet air more effectively than the parallel flow humidifier. From the performance measurements of the channel plates various rib widths studied in this study, it is found that the narrower the rib width is, the more the performance of humidifier improves. Raising channel width in same hydraulic diameter (Dh ) will obtain higher εT and lower ΔP. Moreover, increasing the dry side air inlet temperature or humidity will lead to lower εT. In addition, when the dry side air inlet temperature exceeds 50°C, the effect becomes even more obvious.

Keywords: PEM fuel cell, water management, membrane humidifier, heat and mass transfer, humidifier performance

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Authors: Abdulqader Alkhouzaam, Hazim Qiblawey, Majeda Khraisheh

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Membrane treatment for desalination and wastewater treatment is one of the promising solutions to affordable clean water. It is a developing technology throughout the world and considered as the most effective and economical method available. However, the limitations of membranes’ mechanical and chemical properties restrict their industrial applications. Hence, developing novel membranes was the focus of most studies in the water treatment and desalination sector to find new materials that can improve the separation efficiency while reducing membrane fouling, which is the most important challenge in this field. Graphene oxide (GO) is one of the materials that have been recently investigated in the membrane water treatment sector. In this work, ultrafiltration polysulfone (PSF) membranes with high antifouling properties were synthesized by incorporating different loadings of GO. High-oxidation degree GO had been synthesized using a modified Hummers' method. The synthesized GO was characterized using different analytical techniques including elemental analysis, Fourier transform infrared spectroscopy - universal attenuated total reflectance sensor (FTIR-UATR), Raman spectroscopy, and CHNSO elemental analysis. CHNSO analysis showed a high oxidation degree of GO represented by its oxygen content (50 wt.%). Then, ultrafiltration PSF membranes incorporating GO were fabricated using the phase inversion technique. The prepared membranes were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM) and showed a clear effect of GO on PSF physical structure and morphology. The water contact angle of the membranes was measured and showed better hydrophilicity of GO membranes compared to pure PSF caused by the hydrophilic nature of GO. Separation properties of the prepared membranes were investigated using a cross-flow membrane system. Antifouling properties were studied using bovine serum albumin (BSA) and humic acid (HA) as model foulants. It has been found that GO-based membranes exhibit higher antifouling properties compared to pure PSF. When using BSA, the flux recovery ratio (FRR %) increased from 65.4 ± 0.9 % for pure PSF to 84.0 ± 1.0 % with a loading of 0.05 wt.% GO in PSF. When using HA as model foulant, FRR increased from 87.8 ± 0.6 % to 93.1 ± 1.1 % with 0.02 wt.% of GO in PSF. The pure water permeability (PWP) decreased with loadings of GO from 181.7 L.m⁻².h⁻¹.bar⁻¹ of pure PSF to 181.1, and 157.6 L.m⁻².h⁻¹.bar⁻¹ with 0.02 and 0.05 wt.% GO respectively. It can be concluded from the obtained results that incorporating low loading of GO could enhance the antifouling properties of PSF hence improving its lifetime and reuse.

Keywords: antifouling properties, GO based membranes, hydrophilicity, polysulfone, ultrafiltration

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Authors: Fausto Morais

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Artificial intelligence has been widely used in law. Programs are able to classify suits, to identify decision-making patterns, to predict outcomes, and to formalize legal arguments as well. In Brazil, the artificial intelligence victor has been classifying cases to supreme court’s standards. When those programs act doing those tasks, they simulate some kind of legal decision and legal arguments, raising doubts about how artificial intelligence can be integrated into legal reasoning. Taking this into account, the following three issues are identified; the problem of hypernormatization, the argument of legal anthropocentrism, and the artificial legal principles. Hypernormatization can be seen in the Brazilian legal context in the Supreme Court’s usage of the Victor program. This program generated efficiency and consistency. On the other hand, there is a feasible risk of over standardizing factual and normative legal features. Then legal clerks and programmers should work together to develop an adequate way to model legal language into computational code. If this is possible, intelligent programs may enact legal decisions in easy cases automatically cases, and, in this picture, the legal anthropocentrism argument takes place. Such an argument argues that just humans beings should enact legal decisions. This is so because human beings have a conscience, free will, and self unity. In spite of that, it is possible to argue against the anthropocentrism argument and to show how intelligent programs may work overcoming human beings' problems like misleading cognition, emotions, and lack of memory. In this way, intelligent machines could be able to pass legal decisions automatically by classification, as Victor in Brazil does, because they are binding by legal patterns and should not deviate from them. Notwithstanding, artificial intelligent programs can be helpful beyond easy cases. In hard cases, they are able to identify legal standards and legal arguments by using machine learning. For that, a dataset of legal decisions regarding a particular matter must be available, which is a reality in Brazilian Judiciary. Doing such procedure, artificial intelligent programs can support a human decision in hard cases, providing legal standards and arguments based on empirical evidence. Those legal features claim an argumentative weight in legal reasoning and should serve as references for judges when they must decide to maintain or overcome a legal standard.

Keywords: artificial intelligence, artificial legal principles, hypernormatization, legal anthropocentrism argument, legal reasoning

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Authors: Walid A. M. Ghoneim, Hamdy A. Ashour, Asmaa E. Abdo

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In this paper, linear analysis of a Switched Reluctance Generator (SRG) model is applied on the most common configurations (4/2, 6/4 and 8/6) for both conventional short-pitched and fully-pitched designs, in order to determine the optimum stator/rotor pole angles at which the maximum output voltage is generated per unit excitation current. This study is focused on SRG analysis and design as a proposed solution for renewable energy applications, such as wind energy conversion systems. The world’s potential to develop the renewable energy technologies through dedicated scientific researches was the motive behind this study due to its positive impact on economy and environment. In addition, the problem of rare earth metals (Permanent magnet) caused by mining limitations, banned export by top producers and environment restrictions leads to the unavailability of materials used for rotating machines manufacturing. This challenge gave authors the opportunity to study, analyze and determine the optimum design of the SRG that has the benefit to be free from permanent magnets, rotor windings, with flexible control system and compatible with any application that requires variable-speed operation. In addition, SRG has been proved to be very efficient and reliable in both low-speed or high-speed applications. Linear analysis was performed using MATLAB simulations based on the (Modified generalized matrix approach) of Switched Reluctance Machine (SRM). About 90 different pole angles combinations and excitation patterns were simulated through this study, and the optimum output results for each case were recorded and presented in detail. This procedure has been proved to be applicable for any SRG configuration, dimension and excitation pattern. The delivered results of this study provide evidence for using the 4-phase 8/6 fully pitched SRG as the main optimum configuration for the same machine dimensions at the same angular speed.

Keywords: generalized matrix approach, linear analysis, renewable applications, switched reluctance generator

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Eun-Taek Sin, Hyun-Ju Jang, Chang Geun Song, Yong-Sik Han

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Due to the climate change, the coastal urban area repeatedly suffers from the loss of property and life by flooding. There are three main causes of inland submergence. First, when heavy rain with high intensity occurs, the water quantity in inland cannot be drained into rivers by increase in impervious surface of the land development and defect of the pump, storm sewer. Second, river inundation occurs then water surface level surpasses the top of levee. Finally, Coastal inundation occurs due to rising sea water. However, previous studies ignored the complex mechanism of flooding, and showed discrepancy and inadequacy due to linear summation of each analysis result. In this study, inland flooding and river inundation were analyzed together by HDM-2D model. Petrov-Galerkin stabilizing method and flux-blocking algorithm were applied to simulate the inland flooding. In addition, sink/source terms with exponentially growth rate attribute were added to the shallow water equations to include the inland flooding analysis module. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. To consider the coastal surge, another module was developed by adding seawater to the existing Inland Flooding-River Inundation binding module for comprehensive flooding analysis. Based on the combined modules, the Coastal Inundation – Inland & River Flow Interface was simulated by inputting the flow rate and depth data in artificial flume. Accordingly, it was able to analyze the flood patterns of coastal cities over time. This study is expected to help identify the complex causes of flooding in coastal areas where complex flooding occurs, and assist in analyzing damage to coastal cities. Acknowledgements—This research was supported by a grant ‘Development of the Evaluation Technology for Complex Causes of Inundation Vulnerability and the Response Plans in Coastal Urban Areas for Adaptation to Climate Change’ [MPSS-NH-2015-77] from the Natural Hazard Mitigation Research Group, Ministry of Public Safety and Security of Korea.

Keywords: flooding analysis, river inundation, inland flooding, 2D hydrodynamic model

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Alan T. Sassler

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Biofouling is a significant issue for ships, especially those based in warm water ports. Biofouling damages hull coatings, degrades platform hydrodynamics, blocks cooling water intakes, and returns, reduces platform range and speed, and increases fuel consumption. Although platforms are protected to some degree by antifouling paints, these paints are much less effective on stationary platforms, and problematic biofouling can occur on antifouling paint-protected stationary platforms in some environments in as little as a matter of weeks. Remediation hull cleaning operations are possible, but they are very expensive, sometimes result in damage to the vessel’s paint or hull and are generally not completely effective. Ultrasound with sufficient intensity focused on specific frequency ranges can be used to prevent the growth of biofouling organisms. The use of ultrasound to prevent biofouling isn't new, but systems to date have focused on protecting platforms by shaking the hull using internally mounted transducers similar to those used in ultrasonic cleaning machines. While potentially effective, this methodology doesn't scale well to large platforms, and there are significant costs associated with installing and maintaining these systems, which dwarf the initial purchase price. An alternative approach has been developed, which uses highly directional pier-mounted transducers to project high-intensity spread-spectrum ultrasonic energy into the water column focused near the surface. This focused energy has been shown to prevent biofouling at ranges of up to 50 meters from the source. Spreading the energy out over a multi-kilohertz band makes the system both more effective and more environmentally friendly. This system has been shown to be both effective and inexpensive in small-scale testing and is now being characterized on a larger scale in selected marinas. To date, test results have been collected in Florida marinas suggesting that this approach can be used to keep ensonified areas of thousands of square meters free from biofouling, although care must be taken to minimize shaded areas.

Keywords: biofouling, ultrasonic, environmentally friendly antifoulant, marine protection, antifouling

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Authors: Filip Rusak, Yulia Arzhaeva, Dadong Wang

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Machine learning based Computer-Aided Diagnosis (CAD) is gaining much popularity in medical imaging and diagnostic radiology. However, it requires a large amount of high quality and labeled training image datasets. The training images may come from different sources and be acquired from different radiography machines produced by different manufacturers, digital or digitized copies of film radiographs, with various sizes as well as different pixel intensity distributions. In this paper, a content-aware image augmentation method is presented to deal with these variations. The results of the proposed method have been validated graphically by plotting the removed and added seams of pixels on original images. Two different chest X-ray (CXR) datasets are used in the experiments. The CXRs in the datasets defer in size, some are digital CXRs while the others are digitized from analog CXR films. With the proposed content-aware augmentation method, the Seam Carving algorithm is employed to resize CXRs and the corresponding labels in the form of image masks, followed by histogram matching used to normalize the pixel intensities of digital radiography, based on the pixel intensity values of digitized radiographs. We implemented the algorithms, resized the well-known Montgomery dataset, to the size of the most frequently used Japanese Society of Radiological Technology (JSRT) dataset and normalized our digital CXRs for testing. This work resulted in the unified off-the-shelf CXR dataset composed of radiographs included in both, Montgomery and JSRT datasets. The experimental results show that even though the amount of augmentation is large, our algorithm can preserve the important information in lung fields, local structures, and global visual effect adequately. The proposed method can be used to augment training and testing image data sets so that the trained machine learning model can be used to process CXRs from various sources, and it can be potentially used broadly in any medical imaging applications.

Keywords: computer-aided diagnosis, image augmentation, lung segmentation, medical imaging, seam carving

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: S. Apprich, F. Wulle, A. Lechler, A. Pott, A. Verl

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Large-scale machine tools for the manufacturing of large work pieces, e.g. blades, casings or gears for wind turbines, feature pose-dependent dynamic behavior. Small structural damping coefficients lead to long decay times for structural vibrations that have negative impacts on the production process. Typically, these vibrations are handled by increasing the stiffness of the structure by adding mass. That is counterproductive to the needs of sustainable manufacturing as it leads to higher resource consumption both in material and in energy. Recent research activities have led to higher resource efficiency by radical mass reduction that rely on control-integrated active vibration avoidance and damping methods. These control methods depend on information describing the dynamic behavior of the controlled machine tools in order to tune the avoidance or reduction method parameters according to the current state of the machine. The paper presents the appearance, consequences and challenges of the pose-dependent dynamic behavior of lightweight large-scale machine tool structures in production. The paper starts with the theoretical introduction of the challenges of lightweight machine tool structures resulting from reduced stiffness. The statement of the pose-dependent dynamic behavior is corroborated by the results of the experimental modal analysis of a lightweight test structure. Afterwards, the consequences of the pose-dependent dynamic behavior of lightweight machine tool structures for the use of active control and vibration reduction methods are explained. Based on the state of the art on pose-dependent dynamic machine tool models and the modal investigation of an FE-model of the lightweight test structure, the criteria for a pose-dependent model for use in vibration reduction are derived. The description of the approach for a general pose-dependent model of the dynamic behavior of large lightweight machine tools that provides the necessary input to the aforementioned vibration avoidance and reduction methods to properly tackle machine vibrations is the outlook of the paper.

Keywords: dynamic behavior, lightweight, machine tool, pose-dependency

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Authors: M. Hossain, A. Abdkader, C. Cherif, A. Berger, M. Sparing, R. Hühne, L. Schultz, K. Nielsch

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Due to the best quality of yarn and the flexibility of the machine, the ring spinning process is the most widely used spinning method for short staple yarn production. However, the productivity of these machines is still much lower in comparison to other spinning systems such as rotor or air-jet spinning process. The main reason for this limitation lies on the twisting mechanism of the ring spinning process. In the ring/traveler twisting system, each rotation of the traveler along with the ring inserts twist in the yarn. The rotation of the traveler at higher speed includes strong frictional forces, which in turn generates heat. Different ring/traveler systems concerning with its geometries, material combinations and coatings have already been implemented to solve the frictional problem. However, such developments can neither completely solve the frictional problem nor increase the productivity. The friction free superconducting magnetic bearing (SMB) system can be a right alternative replacing the existing ring/traveler system. The unique concept of SMB bearings is that they possess a self-stabilizing behavior, i.e. they remain fully passive without any necessity for expensive position sensing and control. Within the framework of a research project funded by German research foundation (DFG), suitable concepts of the SMB-system have been designed, developed, and integrated as a twisting device of ring spinning replacing the existing ring/traveler system. With the help of the developed mathematical model and experimental investigation, the physical limitations of this innovative twisting device in the spinning process have been determined. The interaction among the parameters of the spinning process and the superconducting twisting element has been further evaluated, which derives the concrete information regarding the new spinning process. Moreover, the influence of the implemented SMB twisting system on the yarn quality has been analyzed with respect to different process parameters. The presented work reveals the enormous potential of the innovative twisting mechanism, so that the productivity of the ring spinning process especially in case of thermoplastic materials can be at least doubled for the first time in a hundred years. The SMB ring spinning tester has also been presented in the international fair “International Textile Machinery Association (ITMA) 2015”.

Keywords: ring spinning, superconducting magnetic bearing, yarn properties, productivity

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Authors: A. G. Cunha, M. Inácio, M. C. Freitas, C. Antunes, T. Silva, C. Andrade, V. Lopes

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Saltmarshes are essential ecosystems both from an ecological and biological point of view. Furthermore, they constitute an important social niche, providing valuable economic and protection functions. Thus, understanding their rates and patterns of sedimentation is critical for functional management and rehabilitation, especially in an SLR scenario. The Sado estuary is located 40 km south of Lisbon. It is a bar built estuary, separated from the sea by a large sand spit: the Tróia barrier. Caldeira de Tróia is located on the free edge of this barrier, and encompasses a salt marsh with ca. 21,000 m². Sediment cores were collected in the high and low marshes and in the mudflat area of the North bank of Caldeira de Tróia. From the low marsh core, fifteen samples were chosen for ²¹⁰Pb and ¹³⁷Cs determination at University of Geneva. The cores from the high marsh and the mudflat are still being analyzed. A sedimentation rate of 2.96 mm/year was derived from ²¹⁰Pb using the Constant Flux Constant Sedimentation model. The ¹³⁷Cs profile shows a peak in activity (1963) between 15.50 and 18.50 cm, giving a 3.1 mm/year sedimentation rate for the past 53 years. The adopted sea level rise scenario was based on a model built with the initial rate of SLR of 2.1 mm/year in 2000 and an acceleration of 0.08 mm/year². Based on the harmonic analysis of Setubal-Tróia tide gauge of 2005 data, the tide model was estimated and used to build the tidal tables to the period 2000-2016. With these tables, the average mean water levels were determined for the same time span. A digital terrain model was created from LIDAR scanning with 2m horizontal resolution (APA-DGT, 2011) and validated with altimetric data obtained with a DGPS-RTK. The response model calculates a new elevation for each pixel of the DTM for 2050 and 2100 based on the sedimentation rates specific of each environment. At this stage, theoretical values were chosen for the high marsh and the mudflat (respectively, equal and double the low marsh rate – 2.92 mm/year). These values will be rectified once sedimentation rates are determined for the other environments. For both projections, the total surface of the marsh decreases: 2% in 2050 and 61% in 2100. Additionally, the high marsh coverage diminishes significantly, indicating a regression in terms of maturity.

Keywords: ¹³⁷Cs, ²¹⁰Pb, saltmarsh, sea level rise, response model

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Authors: O. Eso, M. Mohammadi, J. Darkwa, J. Calautit

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Residential buildings are responsible for 22% of the global end-use energy demand and 17% of global CO₂ emissions. Tropical climates particularly present higher latent heat gains, leading to more cooling loads. However, the cooling processes are all based on conventional mechanical air conditioning systems which are energy and carbon intensive technologies. Passive cooling systems have in the past been considered as alternative technologies for minimizing energy consumption in buildings. Nevertheless, replacing mechanical cooling systems with passive ones will require a careful assessment of the passive cooling system heat transfer to determine if suitable to outperform their conventional counterparts. This is because internal heat gains, indoor-outdoor heat transfer, and heat transfer through envelope affects the performance of passive cooling systems. While many studies have investigated sensible heat transfer in passive cooling systems, not many studies have focused on their latent heat transfer capabilities. Furthermore, combining heat prevention, heat modulation and heat dissipation to passively cool indoor spaces in the tropical climates is critical to achieve thermal comfort. Since passive cooling systems use only one of these three approaches at a time, integrating more than one passive cooling system for effective indoor latent heat removal while still saving energy is studied. This study is a systematic review of recently published peer review journals on integrated passive cooling systems for tropical residential buildings. The missing links in the experimental and numerical studies with regards to latent heat reduction interventions are presented. Energy simulation studies of integrated passive cooling systems in tropical residential buildings are also discussed. The review has shown that comfortable indoor environment is attainable when two or more passive cooling systems are integrated in tropical residential buildings. Improvement occurs in the heat transfer rate and cooling performance of the passive cooling systems when thermal energy storage systems like phase change materials are included. Integrating passive cooling systems in tropical residential buildings can reduce energy consumption by 6-87% while achieving up to 17.55% reduction in indoor heat flux. The review has highlighted a lack of numerical studies regarding passive cooling system performance in tropical savannah climates. In addition, detailed studies are required to establish suitable latent heat transfer rate in passive cooling ventilation devices under this climate category. This should be considered in subsequent studies. The conclusions and outcomes of this study will help researchers understand the overall energy performance of integrated passive cooling systems in tropical climates and help them identify and design suitable climate specific options for residential buildings.

Keywords: energy savings, latent heat, passive cooling systems, residential buildings, tropical residential buildings

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Authors: Ahmed A. El-Gindy, Elham S. El-Nashar, Abdallah Nafaa, Sameh El-Kafrawy

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The generation of energy from marine energy became one of the most preferable resources since it is a clean source and friendly to environment. Egypt has long shores along Mediterranean with important cities that need energy resources with significant wave energy. No detailed studies have been done on wave energy distribution in the Egyptian waters. The objective of this paper is to assess the energy wave power available in the Egyptian waters for the choice of the most suitable devices to be used in this area. This paper deals the characteristics and power of the offshore waves in the Egyptian waters. Since the field observations of waves are not frequent and need much technical work, the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis data in Mediterranean, with a grid size 0.75 degree, which is a relatively course grid, are considered in the present study for preliminary assessment of sea waves characteristics and power. The used data covers the period from 2012 to 2014. The data used are significant wave height (swh), mean wave period (mwp) and wave direction taken at six hourly intervals, at seven chosen stations, and at grid points covering the Egyptian waters. The wave power (wp) formula was used to calculate energy flux. Descriptive statistical analysis including monthly means and standard deviations of the swh, mwp, and wp. The percentiles of wave heights and their corresponding power are done, as a tool of choice of the best technology suitable for the site. The surfer is used to show spatial distributions of wp. The analysis of data at chosen 7 stations determined the potential of wp off important Egyptian cities. Offshore of Al Saloum and Marsa Matruh, the highest wp occurred in January and February (16.93-18.05) ± (18.08-22.12) kw/m while the lowest occurred in June and October (1.49-1.69) ± (1.45-1.74) kw/m. In front of Alexandria and Rashid, the highest wp occurred in January and February (16.93-18.05) ± (18.08-22.12) kw/m while the lowest occurred in June and September (1.29-2.01) ± (1.31-1.83) kw/m. In front of Damietta and Port Said, the highest wp occurred in February (14.29-17.61) ± (21.61-27.10) kw/m and the lowest occurred in June (0.94-0.96) ± (0.71-0.72) kw/m. In winter, the probabilities of waves higher than 0.8 m in percentage were, at Al Saloum and Marsa Matruh (76.56-80.33) ± (11.62-12.05), at Alexandria and Rashid (73.67-74.79) ± (16.21-18.59) and at Damietta and Port Said (66.28-68.69) ± (17.88-17.90). In spring, the percentiles were, at Al Saloum and Marsa Matruh, (48.17-50.92) ± (5.79-6.56), at Alexandria and Rashid, (39.38-43.59) ± (9.06-9.34) and at Damietta and Port Said, (31.59-33.61) ± (10.72-11.25). In summer, the probabilities were, at Al Saloum and Marsa Matruh (57.70-66.67) ± (4.87-6.83), at Alexandria and Rashid (59.96-65.13) ± (9.14-9.35) and at Damietta and Port Said (46.38-49.28) ± (10.89-11.47). In autumn, the probabilities were, at Al Saloum and Marsa Matruh (58.75-59.56) ± (2.55-5.84), at Alexandria and Rashid (47.78-52.13) ± (3.11-7.08) and at Damietta and Port Said (41.16-42.52) ± (7.52-8.34).

Keywords: distribution of sea waves energy, Egyptian Mediterranean waters, waves characteristics, waves power

Procedia PDF Downloads 184

Authors: S. Vivek, Sharad Sharan, R. Arvind, D. V. Praveen, J. Vigneshwar, S. Ajith, V. R. Sanal Kumar

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In this paper numerical studies have been carried out to examine the starting transient flow features of high-performance solid propellant rocket motors with different port geometries but with same propellant loading density. Numerical computations have been carried out using a 3D SST k-ω turbulence model. This code solves standard k-omega turbulence equations with shear flow corrections using a coupled second order implicit unsteady formulation. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations are employed. We have observed from the numerical results that in solid rocket motors with highly loaded propellants having divergent port geometry the hot igniter gases can create pre-ignition thrust oscillations due to flow unsteadiness and recirculation. Under these conditions the convective flux to the surface of the propellant will be enhanced, which will create reattachment point far downstream of the transition region and it will create a situation for secondary ignition and formation of multiple-flame fronts. As a result the effective time required for the complete burning surface area to be ignited comes down drastically giving rise to a high pressurization rate (dp/dt) in the second phase of starting transient. This in effect could lead to starting thrust oscillations and eventually a hard start of the solid rocket motor. We have also observed that the igniter temperature fluctuations will be diminished rapidly and will reach the steady state value faster in the case of solid propellant rocket motors with convergent port than the divergent port irrespective of the igniter total pressure. We have concluded that the thrust oscillations and unexpected thrust spike often observed in solid rockets with non-uniform ports are presumably contributed due to the joint effects of the geometry dependent driving forces, transient burning and the chamber gas dynamics forces. We also concluded that the prudent selection of the port geometry, without altering the propellant loading density, for damping the total temperature fluctuations within the motor is a meaningful objective for the suppression and control of instability and/or pressure/thrust oscillations often observed in solid propellant rocket motors with non-uniform port geometry.

Keywords: ignition transient, solid rockets, starting transient, thrust transient

Procedia PDF Downloads 439

Authors: Mastoor Qubra

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Cyber-attacks have frequently disrupted the critical infrastructures of the major global states and now, cyber threat has become one of the dire security risks for the states across the globe. Recently, ransomware cyber-attacks, wannacry and petya, have affected hundreds of thousands of computer servers and individuals’ private machines in more than hundred countries across Europe, Middle East, Asia, United States and Australia. Although, states are rapidly becoming aware of the destructive nature of this new security threat and counter measures are being taken but states’ isolated efforts would be inadequate to deal with this heinous security challenge, rather a global coordination and cooperation is inevitable in order to develop a credible cyber deterrence policy. Hence, the paper focuses that coordinated global approach is required to deter posed cyber threat. This paper intends to analyze the cyber security counter measures in four dimensions i.e. evaluation of prevalent strategies at bilateral level, initiatives and limitations for cooperation at global level, obstacles to combat cyber terrorism and finally, recommendations to deter the threat by applying tools of deterrence theory. Firstly, it focuses on states’ efforts to combat the cyber threat and in this regard, US-Australia Cyber Security Dialogue is comprehensively illustrated and investigated. Secondly, global partnerships and strategic and analytic role of multinational organizations, particularly United Nations (UN), to deal with the heinous threat, is critically analyzed and flaws are highlighted, for instance; less significance of cyber laws within international law as compared to other conflict prone issues. In addition to this, there are certain obstacles and limitations at national, regional and global level to implement the cyber terrorism counter strategies which are presented in the third section. Lastly, by underlining the gaps and grey areas in the current cyber security counter measures, it aims to apply tools of deterrence theory, i.e. defense, attribution and retaliation, in the cyber realm to contribute towards formulating a credible cyber deterrence strategy at global level. Thus, this study is significant in understanding and determining the inevitable necessity of counter cyber terrorism strategies.

Keywords: attribution, critical infrastructure, cyber terrorism, global cooperation

Procedia PDF Downloads 263

Authors: M. H. Ahmadi, A. Mortazavi, H. Zarei

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Several authors have described the main mechanism of formation of cracks in the segment lining during the construction of tunnels with tunnel boring machines. A comprehensive analysis of segmental lining joints may help to guarantee a safe construction during Tunneling and serviceable stages. The most frequent types of segment damage are caused by a condition of uneven segment matching due to contact deficiencies. This paper investigated the interaction mechanism of precast concrete lining joints in tunnels. The Discrete Element Method (DEM) was used to analyze a typical segmental lining model consisting of six segment rings. In the analyses, typical segmental lining design parameters of the Ghomrood water conveyance tunnel, Iran were employed in the study. In the conducted analysis, the worst-case scenario of loading faced during the boring of Ghomrood tunnel was considered. This was associated with the existence of a crushed zone dipping at 75 degree at the location of the key segment. In the analysis, moreover, the effect of changes in horizontal stress ratio on the loads on the segment was assessed. The boundary condition associated with K (ratio of the horizontal to the vertical stress) values of 0.5, 1, 1.5 and 2 were applied to the model and separate analysis was conducted for each case. Important parameters such as stress, moments, and displacements were measured at joint locations and the surrounding rock. Accordingly, the segment joint interactions were assessed and analyzed. Moreover, rock mass properties of the Ghomrood in Ghom were adopted. In this study, the load acting on segments joints are included a crushed zone stratum force that intersect tunnel with 75 slopes in the location of the key segment, gravity force of segments and earth pressures. A numerical investigation was used for different coefficients of stress concentration of 0.5, 1, 1.5, 2 and different geological conditions of saturated crushed zone under the critical scenario. The numerical results also demonstrate that maximum bending moments in longitudinal joints occurred for crushed zone with the weaken strengths (Sandstone). Besides that, increasing the load in segment-stratum interfaces affected radial stress in longitudinal joints and finally the opening of joints occurred.

Keywords: joint, interface, segment, contact

Procedia PDF Downloads 254

Authors: Minh Chien Vu, Tomoaki Satomi, Hiroshi Takahashi

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As being lack of sufficient strength to support the loading of construction as well as service life cause the clay content and clay mineralogy, soft and highly compressible soils (sludge) constitute a major problem in geotechnical engineering projects. Geopolymer, a kind of inorganic polymer, is a promising material with a wide range of applications and offers a lower level of CO₂ emissions than conventional Portland cement. However, the feasibility of geopolymer in term of modified the soft and highly compressible soil has not been received much attention due to the requirement of heat treatment for activating the fly ash component and the existence of high content of clay-size particles in the composition of sludge that affected on the efficiency of the reaction. On the other hand, the geopolymer modified sludge could be affected by other important factors such as initial curing time, initial water content and apparent water content. Therefore, this paper describes a different potential application of geopolymer: soil stabilization in landslide areas to adapt to the technical properties of sludge so that heavy machines can move on. Sludge condition process is utilized to demonstrate the possibility for stabilizing sludge using fly ash-based geopolymer at ambient curing condition ( ± 20 °C) in term of failure strength, strain and bulk density. Sludge conditioning is a process whereby sludge is treated with chemicals or various other means to improve the dewatering characteristics of sludge before applying in the construction area. The effect of initial curing time, water content and apparent water content on the modification of sludge are the main focus of this study. Test results indicate that the initial curing time has potential for improving failure strain and strength of modified sludge with the specific condition of soft soil. The result further shows that the initial water content over than 50% total mass of sludge could significantly lead to a decrease of strength performance of geopolymer-based modified sludge. The optimum apparent water content of geopolymer modified sludge is strongly influenced by the amount of geopolymer content and initial water content of sludge. The solution to minimize the effect of high initial water content will be considered deeper in the future.

Keywords: landslide, sludge, fly ash, geopolymer, sludge conditioning

Procedia PDF Downloads 113

Authors: Feng-Sheng Wang, Chao-Ting Cheng

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Developing a drug from conception to launch is costly and time-consuming. Computer-aided methods can reduce research costs and accelerate the development process during the early drug discovery and development stages. This study developed a fuzzy multi-objective hierarchical optimization framework for identifying potential anticancer targets in a metabolic model. First, RNA-seq expression data of colorectal cancer samples and their healthy counterparts were used to reconstruct tissue-specific genome-scale metabolic models. The aim of the optimization framework was to identify anticancer targets that lead to cancer cell death and evaluate metabolic flux perturbations in normal cells that have been caused by cancer treatment. Four objectives were established in the optimization framework to evaluate the mortality of cancer cells for treatment and to minimize side effects causing toxicity-induced tumorigenesis on normal cells and smaller metabolic perturbations. Through fuzzy set theory, a multiobjective optimization problem was converted into a trilevel maximizing decision-making (MDM) problem. The applied nested hybrid differential evolution was applied to solve the trilevel MDM problem using two nutrient media to identify anticancer targets in the genome-scale metabolic model of colorectal cancer, respectively. Using Dulbecco’s Modified Eagle Medium (DMEM), the computational results reveal that the identified anticancer targets were mostly involved in cholesterol biosynthesis, pyrimidine and purine metabolisms, glycerophospholipid biosynthetic pathway and sphingolipid pathway. However, using Ham’s medium, the genes involved in cholesterol biosynthesis were unidentifiable. A comparison of the uptake reactions for the DMEM and Ham’s medium revealed that no cholesterol uptake reaction was included in DMEM. Two additional media, i.e., a cholesterol uptake reaction was included in DMEM and excluded in HAM, were respectively used to investigate the relationship of tumor cell growth with nutrient components and anticancer target genes. The genes involved in the cholesterol biosynthesis were also revealed to be determinable if a cholesterol uptake reaction was not induced when the cells were in the culture medium. However, the genes involved in cholesterol biosynthesis became unidentifiable if such a reaction was induced.

Keywords: Cancer metabolism, genome-scale metabolic model, constraint-based model, multilevel optimization, fuzzy optimization, hybrid differential evolution

Procedia PDF Downloads 69

Authors: Miriam Borchardt, Agata M. Ritter, Macaliston G. da Silva, Mauricio N. de Carvalho, Giancarlo M. Pereira

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This paper aims to analyze the barriers faced by social enterprises and based on that to propose a social business model framework that helps them to leverage their businesses and the social value delivered. A business model for social enterprises should amplify the value perception including social value for the beneficiaries while generating enough profit to escalate the business. Most of the social value beneficiaries are people from the base of the economic pyramid (BOP) or the ones that have specific needs. Because of this, products and services should be affordable to consumers while solving social needs of the beneficiaries. Developing products and services with social value require tie relationship among the social enterprises and universities, public institutions, accelerators, and investors. Despite being focused on social value and contributing to the beneficiaries’ quality of life as well as contributing to the governments that cannot properly guarantee public services and infrastructure to the BOP, many barriers are faced by the social enterprises to escalate their businesses. This is a work in process and five micro- and small-sized social enterprises in Brazil have been studied: (i) one has developed a kit for cervical uterine cancer detection to allow the BOP women to collect their own material and deliver to a laboratory for U$1,00; (ii) other has developed special products without lactose and it is about 70% cheaper than the traditional brands in the market; (iii) the third has developed prosthesis and orthosis to surplus needs that health public system have not done efficiently; (iv) the fourth has produced and commercialized menstrual panties aiming to reduce the consumption of dischargeable ones while saving money to the consumers; (v) the fifth develops and commercializes clothes from fabric wastes in a partnership with BOP artisans. The preliminary results indicate that the main barriers are related to the public system to recognize these products as public money that could be saved if they bought products from these enterprises instead of the multinational pharmaceutical companies, to the traditional distribution system (e.g. pharmacies) that avoid these products because of the low or non-existing profit, to the difficulty buying raw material in small quantities, to leverage investment by the investors, to cultural barriers and taboos. Interesting strategies to reduce the costs have been observed: some enterprises have focused on simplifying products, others have invested in partnerships with local producers and have developed their machines focusing on process efficiency to leverage investment by the investors.

Keywords: base of the pyramid, business model, social business, social business model, social enterprises

Procedia PDF Downloads 94

Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

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Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

Procedia PDF Downloads 472

Authors: Aya Al Masri, Stefaan Carpentier, Fabrice Leroy, Thibault Julien, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: During an 'Interventional Radiology (IR)' procedure, the patient's skin-dose may become very high for a burn, necrosis and ulceration to appear. In order to prevent these deterministic effects, an accurate calculation of the patient skin-dose mapping is essential. For most machines, the 'Dose Area Product (DAP)' and fluoroscopy time are the only information available for the operator. These two parameters are a very poor indicator of the peak skin dose. We developed a mathematical model that reconstructs the magnitude (delivered dose), shape, and localization of each irradiation field on the patient skin. In case of critical dose exceeding, the system generates warning alerts. We present the results of its comparison with clinical studies. Materials and methods: Two series of comparison of the skin-dose mapping of our mathematical model with clinical studies were performed: 1. At a first time, clinical tests were performed on patient phantoms. Gafchromic films were placed on the table of the IR machine under of PMMA plates (thickness = 20 cm) that simulate the patient. After irradiation, the film darkening is proportional to the radiation dose received by the patient's back and reflects the shape of the X-ray field. After film scanning and analysis, the exact dose value can be obtained at each point of the mapping. Four experimentation were performed, constituting a total of 34 acquisition incidences including all possible exposure configurations. 2. At a second time, clinical trials were launched on real patients during real 'Chronic Total Occlusion (CTO)' procedures for a total of 80 cases. Gafchromic films were placed at the back of patients. We performed comparisons on the dose values, as well as the distribution, and the shape of irradiation fields between the skin dose mapping of our mathematical model and Gafchromic films. Results: The comparison between the dose values shows a difference less than 15%. Moreover, our model shows a very good geometric accuracy: all fields have the same shape, size and location (uncertainty < 5%). Conclusion: This study shows that our model is a reliable tool to warn physicians when a high radiation dose is reached. Thus, deterministic effects can be avoided.

Keywords: clinical experimentation, interventional radiology, mathematical model, patient's skin-dose mapping.

Procedia PDF Downloads 132

Authors: Dimitrios Bakavos, Dimitrios Tsivoulas, Chaowalit Limmaneevichitr

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Aluminium cast alloys, of the Al-Si system, are widely used for shape castings. Their microstructures can be further improved on one hand, by alloying modification and on the other, by optimised artificial ageing. In this project four hypoeutectic Al-alloys, the A356, A356+ Ag, A356+Sc, and A356+Ag+Sc have been studied. The interactions of Ag and Sc during solidification and artificial ageing at 170°C to a T6 temper have been investigated in details. The evolution of the eutectic microstructure is studied by thermal analysis and interrupted solidification. The ageing kinetics of the alloys has been identified by hardness measurements. The precipitate phases, number density, and chemical composition has been analysed by means of transmission electron microscopy (TEM) and EDS analysis. Furthermore, the SHT effect onto the Si eutectic particles for the four alloys has been investigated by means of optical microscopy, image analysis, and the UTS strength has been compared with the UTS of the alloys after casting. The results suggest that the Ag additions, significantly enhance the ageing kinetics of the A356 alloy. The formation of β” precipitates were kinetically accelerated and an increase of 8% and 5% in peak hardness strength has been observed compared to the base A356 and A356-Sc alloy. The EDS analysis demonstrates that Ag is present on the β” precipitate composition. After prolonged ageing 100 hours at 170°C, the A356-Ag exhibits 17% higher hardness strength compared to the other three alloys. During solidification, Sc additions change the macroscopic eutectic growth mode to the propagation of a defined eutectic front from the mold walls opposite to the heat flux direction. In contrast, Ag has no significance effect on the solidification mode revealing a macroscopic eutectic growth similar to A356 base alloy. However, the mechanical strength of the as cast A356-Ag, A356-Sc, and A356+Ag+Sc additions has increased by 5, 30, and 35 MPa, respectively. The outcome is a tribute to the refining of the eutectic Si that takes place which it is strong in the A356-Sc alloy and more profound when silver and scandium has been combined. Moreover after SHT the Al alloy with the highest mechanical strength, is the one with Ag additions, in contrast to the as-cast condition where the Sc and Sc+Ag alloy was the strongest. The increase of strength is mainly attributed to the dissolution of grain boundary precipitates the increase of the solute content into the matrix, the spherodisation, and coarsening of the eutectic Si. Therefore, we could safely conclude for an A356 hypoeutectic alloy additions of: Ag exhibits a refining effect on the Si eutectic which is improved when is combined with Sc. In addition Ag enhance, the ageing kinetics increases the hardness and retains its strength at prolonged artificial ageing in a Al-7Si 0.3Mg hypoeutectic alloy. Finally the addition of Sc is beneficial due to the refinement of the α-Al grain and modification-refinement of the eutectic Si increasing the strength of the as-cast product.

Keywords: ageing, casting, mechanical strength, precipitates

Procedia PDF Downloads 490

Authors: Peggy Näser

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Factory planning is a systematic, objective-oriented process for planning a factory, structured into a sequence of phases, each of which is dependent on the preceding phase and makes use of particular methods and tools, and extending from the setting of objectives to the start of production. The digital factory, on the other hand, is the generic term for a comprehensive network of digital models, methods, and tools – including simulation and 3D visualisation – integrated by a continuous data management system. Its aim is the holistic planning, evaluation and ongoing improvement of all the main structures, processes and resources of the real factory in conjunction with the product. Digital factory planning has already become established in factory planning. The application of Building Information Modeling has not yet been established in factory planning but has been used predominantly in the planning of public buildings. Furthermore, this concept is limited to the planning of the buildings and does not include the planning of equipment of the factory (machines, technical equipment) and their interfaces to the building. BIM is a cooperative method of working, in which the information and data relevant to its lifecycle are consistently recorded, managed and exchanged in a transparent communication between the involved parties on the basis of digital models of a building. Both approaches, the planning approach of Building Information Modeling and the methodical approach of the Digital Factory, are based on the use of a comprehensive data model. Therefore it is necessary to examine how the approach of Building Information Modeling can be extended in the context of factory planning in such a way that an integration of the equipment planning, as well as the building planning, can take place in a common digital model. For this, a number of different perspectives have to be investigated: the equipment perspective including the tools used to implement a comprehensive digital planning process, the communication perspective between the planners of different fields, the legal perspective, that the legal certainty in each country and the quality perspective, on which the quality criteria are defined and the planning will be evaluated. The individual perspectives are examined and illustrated in the article. An approach model for the integration of factory planning into the BIM approach, in particular for the integrated planning of equipment and buildings and the continuous digital planning is developed. For this purpose, the individual factory planning phases are detailed in the sense of the integration of the BIM approach. A comprehensive software concept is shown on the tool. In addition, the prerequisites required for this integrated planning are presented. With the help of the newly developed approach, a better coordination between equipment and buildings is to be achieved, the continuity of the digital factory planning is improved, the data quality is improved and expensive implementation errors are avoided in the implementation.

Keywords: building information modeling, digital factory, digital planning, factory planning

Procedia PDF Downloads 258

Authors: E. Nakamachi, K. Matsumoto, K. Yamamoto, Y. Morita, H. Sakamoto

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In recently, electromagnetic and mechanical stimulations have been recognized as the effective extracellular environment stimulation technique to enhance the defected peripheral nerve tissue regeneration. In this study, we developed a new hybrid bioreactor by adopting 50 Hz uniform alternative current (AC) magnetic stimulation and 4% strain mechanical stimulation. The guide tube for nerve regeneration is mesh structured tube made of biodegradable polymer, such as polylatic acid (PLA). However, when neural damage is large, there is a possibility that peripheral nerve undergoes necrosis. So it is quite important to accelerate the nerve tissue regeneration by achieving enhancement of nerve axonal extension rate. Therefore, we try to design and fabricate the system that can simultaneously load the uniform AC magnetic field stimulation and the stretch stimulation to cells for enhancement of nerve axonal extension. Next, we evaluated systems performance and the effectiveness of each stimulation for rat adrenal pheochromocytoma cells (PC12). First, we designed and fabricated the uniform AC magnetic field system and the stretch stimulation system. For the AC magnetic stimulation system, we focused on the use of pole piece structure to carry out in-situ microscopic observation. We designed an optimum pole piece structure using the magnetic field finite element analyses and the response surface methodology. We fabricated the uniform AC magnetic field stimulation system as a bio-reactor by adopting analytically determined design specifications. We measured magnetic flux density that is generated by the uniform AC magnetic field stimulation system. We confirmed that measurement values show good agreement with analytical results, where the uniform magnetic field was observed. Second, we fabricated the cyclic stretch stimulation device under the conditions of particular strains, where the chamber was made of polyoxymethylene (POM). We measured strains in the PC12 cell culture region to confirm the uniform strain. We found slightly different values from the target strain. Finally, we concluded that these differences were allowable in this mechanical stimulation system. We evaluated the effectiveness of each stimulation to enhance the nerve axonal extension using PC12. We confirmed that the average axonal extension length of PC12 under the uniform AC magnetic stimulation was increased by 16 % at 96 h in our bio-reactor. We could not confirm that the axonal extension enhancement under the stretch stimulation condition, where we found the exfoliating of cells. Further, the hybrid stimulation enhanced the axonal extension. Because the magnetic stimulation inhibits the exfoliating of cells. Finally, we concluded that the enhancement of PC12 axonal extension is due to the magnetic stimulation rather than the mechanical stimulation. Finally, we confirmed that the effectiveness of the uniform AC magnetic field stimulation for the nerve axonal extension using PC12 cells.

Keywords: nerve cell PC12, axonal extension, nerve regeneration, electromagnetic-mechanical stimulation, bioreactor

Procedia PDF Downloads 262

Authors: Peter. M. Kusen, Georg Wandrey, Christopher Probst, Dietrich Kohlheyer, Jochen Buchs, Jorg Pietruszkau

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Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes.

Keywords: caged-compounds, gene expression regulation, optogenetics, photo-labile protecting group

Procedia PDF Downloads 317

Authors: Ahmed Elsayed, Andrew Shea, Nicolas Kelly, John Allison

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In northern European climates, domestic space heating and hot water represents a significant proportion of total primary total primary energy use and meeting these demands from a national electricity grid network supplied by renewable energy sources provides an opportunity for a significant reduction in EU CO₂ emissions. However, in order to adapt to the intermittent nature of renewable energy generation and to avoid co-incident peak electricity usage from consumers that may exceed current capacity, the demand for heat must be decoupled from its generation. Storage of heat within the fabric of dwellings for use some hours, or days, later provides a route to complete decoupling of demand from supply and facilitates the greatly increased use of renewable energy generation into a local or national electricity network. The integration of thermal energy storage into the building fabric for retrieval at a later time requires much evaluation of the many competing thermal, physical, and practical considerations such as the profile and magnitude of heat demand, the duration of storage, charging and discharging rate, storage media, space allocation, etc. In this paper, the authors report investigations of thermal storage in building fabric using concrete material and present an evaluation of several factors that impact upon performance including heating pipe layout, heating fluid flow velocity, storage geometry, thermo-physical material properties, and also present an investigation of alternative storage materials and alternative heat transfer fluids. Reducing the heating pipe spacing from 200 mm to 100 mm enhances the stored energy by 25% and high-performance Vacuum Insulation results in heat loss flux of less than 3 W/m², compared to 22 W/m² for the more conventional EPS insulation. Dense concrete achieved the greatest storage capacity, relative to medium and light-weight alternatives, although a material thickness of 100 mm required more than 5 hours to charge fully. Layers of 25 mm and 50 mm thickness can be charged in 2 hours, or less, facilitating a fast response that could, aggregated across multiple dwellings, provide significant and valuable reduction in demand from grid-generated electricity in expected periods of high demand and potentially eliminate the need for additional new generating capacity from conventional sources such as gas, coal, or nuclear.

Keywords: fabric integrated thermal storage, FITS, demand side management, energy storage, load shifting, renewable energy integration

Procedia PDF Downloads 165

Authors: Sanjay Rathee, Arti Kashyap

Abstract:

Extraction of useful information from large datasets is one of the most important research problems. Association rule mining is one of the best methods for this purpose. Finding possible associations between items in large transaction based datasets (finding frequent patterns) is most important part of the association rule mining. There exist many algorithms to find frequent patterns but Apriori algorithm always remains a preferred choice due to its ease of implementation and natural tendency to be parallelized. Many single-machine based Apriori variants exist but massive amount of data available these days is above capacity of a single machine. Therefore, to meet the demands of this ever-growing huge data, there is a need of multiple machines based Apriori algorithm. For these types of distributed applications, MapReduce is a popular fault-tolerant framework. Hadoop is one of the best open-source software frameworks with MapReduce approach for distributed storage and distributed processing of huge datasets using clusters built from commodity hardware. However, heavy disk I/O operation at each iteration of a highly iterative algorithm like Apriori makes Hadoop inefficient. A number of MapReduce-based platforms are being developed for parallel computing in recent years. Among them, two platforms, namely, Spark and Flink have attracted a lot of attention because of their inbuilt support to distributed computations. Earlier we proposed a reduced- Apriori algorithm on Spark platform which outperforms parallel Apriori, one because of use of Spark and secondly because of the improvement we proposed in standard Apriori. Therefore, this work is a natural sequel of our work and targets on implementing, testing and benchmarking Apriori and Reduced-Apriori and our new algorithm ReducedAll-Apriori on Apache Flink and compares it with Spark implementation. Flink, a streaming dataflow engine, overcomes disk I/O bottlenecks in MapReduce, providing an ideal platform for distributed Apriori. Flink's pipelining based structure allows starting a next iteration as soon as partial results of earlier iteration are available. Therefore, there is no need to wait for all reducers result to start a next iteration. We conduct in-depth experiments to gain insight into the effectiveness, efficiency and scalability of the Apriori and RA-Apriori algorithm on Flink.

Keywords: apriori, apache flink, Mapreduce, spark, Hadoop, R-Apriori, frequent itemset mining

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