Search results for: energy efficient routing protocols

Authors: Athena Nguyen, Rojin Belganeh

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In recycling plastics industries, waste plastics are converted into monomers and other useful molecules by chemical reactions. Thermal energy generated by incineration is recovered when waste plastics melt. During the process, Flame retardants containing products get in, and brominated flame retardants (BFRs) are often used to reduce the flammability of products. Some of the originally formulated brominated flame retardants additives are restricted by the RoHS Directive, such as PBDE and PBB. The determination of BFRs other than those restricted by the RoHS directive is required. Frontier Lab developed a pyrolyzer based on the vertical micro-furnace design. The multi-mode pyrolyzer with different modes of operations, including evolve gas analysis (EGA), flash pyrolysis, thermal desorption, heart cutting, allows users to choose among the techniques for their analysis purposes. The method requires very little sample preparation. The first step is to perform an EGA using temperature programs. This technique provides information about the thermal temperature behaviors of the sample. The EGA thermogram is then used to determine the next steps in the analysis process. In this presentation, with an Optimal thermal temperature zone identified based on EGA thermogram, thermal desorption GC/MS is a chosen technique for the determination of brominated flame retardants in recycled plastic toys. Five types of general-purpose brominated flame retardants other than those restricted by the RoHS Directive are determined by the standard addition method.

Keywords: gas chromatography/mass spectrometry, pyrolysis, pyrolyzer, thermal desorption-GC/MS

Procedia PDF Downloads 181

Authors: Veniamin Boiarkin, Bruno Bogaz Zarpelão, Muttukrishnan Rajarajan

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The manufacturing sector is a vital component of most economies, which leads to a large number of cyberattacks on organisations, whereas disruption in operation may lead to significant economic consequences. Adversaries aim to disrupt the production processes of manufacturing companies, gain financial advantages, and steal intellectual property by getting unauthorised access to sensitive data. Access to sensitive data helps organisations to enhance the production and management processes. However, the majority of the existing data-sharing mechanisms are either susceptible to different cyber attacks or heavy in terms of computation overhead. In this paper, a privacy-preserving data-sharing scheme for smart utilities is proposed. First, a customer’s privacy adjustment mechanism is proposed to make sure that end-users have control over their privacy, which is required by the latest government regulations, such as the General Data Protection Regulation. Secondly, a local differential privacy-based mechanism is proposed to ensure the privacy of the end-users by hiding real data based on the end-user preferences. The proposed scheme may be applied to different industrial control systems, whereas in this study, it is validated for energy utility use cases consisting of smart, intelligent devices. The results show that the proposed scheme may guarantee the required level of privacy with an expected relative error in utility.

Keywords: data-sharing, local differential privacy, manufacturing, privacy-preserving mechanism, smart utility

Procedia PDF Downloads 67

Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

Procedia PDF Downloads 116

Authors: O. Ubani, H. I. Atagana, M. S. Thantsha, R. Adeleke

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The oil sludge components (polycyclic aromatic hydrocarbons, PAHs) have been found to be cytotoxic, mutagenic and potentially carcinogenic and microorganisms such as bacteria and fungi can degrade the oil sludge to less toxic compounds such as carbon dioxide, water and salts. In the present study, we isolated different bacteria with PAH-degrading potentials from the co-composting of oil sludge and different animal manure. These bacteria were isolated on the mineral base medium and mineral salt agar plates as a growth control. A total of 31 morphologically distinct isolates were carefully selected from 5 different compost treatments for identification using polymerase chain reaction (PCR) of the 16S rDNA gene with specific primers (16S-P1 PCR and 16S-P2 PCR). The amplicons were sequenced and sequences were compared with the known nucleotides from the gene bank database. The phylogenetical analyses of the isolates showed that they belong to 3 different clades namely Firmicutes, Proteobacteria and Actinobacteria. These bacteria identified were closely related to genera Bacillus, Arthrobacter, Staphylococcus, Brevibacterium, Variovorax, Paenibacillus, Ralstonia and Geobacillus species. The results showed that Bacillus species were more dominant in all treated compost piles. Based on their characteristics these bacterial isolates have high potential to utilise PAHs of different molecular weights as carbon and energy sources. These identified bacteria are of special significance in their capacity to emulsify the PAHs and their ability to utilize them. Thus, they could be potentially useful for bioremediation of oil sludge and composting processes.

Keywords: bioaugmentation, biodegradation, bioremediation, composting, oil sludge, PAHs, animal manures

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Authors: Chandra Sekhar Singh, P. Chakrapani, B. Arun Jyothi, A. Roja Rani

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The green synthesis of metallic nanoparticles (NPs) involves biocompatible ingredients under physiological conditions of temperature and pressure. Moreover, the biologically active molecules involved in the green synthesis of NPs act as functionalizing ligands, making these NPs more suitable for biomedical applications. Among the most important bioreductants are plant extracts, which are relatively easy to handle, readily available, low cost, and have been well explored for the green synthesis of other nanomaterials. Various types of metallic NPs have already been synthesized using plant extracts. They have wide applicability in various areas such as electronics, catalysis, chemistry, energy, and medicine. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and flammable. In our study, we were described a cost effective and environment friendly technique for green synthesis of silver nanoparticles from 1mM AgNO3 solution through the aqueous extract of Erythrina indica as reducing as well as capping agent. Nanoparticles were characterized using UV–Vis absorption spectroscopy, FTIR, XRD, X-ray diffraction, SEM and TEM analysis showed the average particle size of 30 nm as well as revealed their spherical structure. Further these biologically synthesized nanoparticles were found to be highly toxic against different human pathogens viz. two Gram positive namely Klebsiella pneumonia and Bacillus subtilis bacteria and two were Gram negative bacteria namely Staphylococcus aureus and Escherichia coli (E. coli). This is for the first time reporting that Erythrina indica plant extract was used for the synthesis of nanoparticles.

Keywords: silver nanoparticles, green synthesis, antibacterial activity, FTIR, TEM, SEM

Procedia PDF Downloads 492

Authors: Reina Kawase, Yuzuru Matsuoka

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To mitigate climate change, to reduce CO2 emission from steel sector, energy intensive sector, is essential. One of the effective countermeasure is recycling of iron scrap and shifting to electric arc furnace. This research analyzes the feasibility of iron scrap recycling with considering demand-supply balance and quantifies the effective by CO2 emission reduction. Generally, the quality of steel made from iron scrap is lower than the quality of steel made from basic oxygen furnace. So, the constraint of demand side is goods-wise steel demand and that of supply side is generation of iron scap. Material Stock and Flow Model (MSFM_demand) was developed to estimate goods-wise steel demand and generation of iron scrap and was applied to 35 regions which aggregated countries in the world for 2005-2050. The crude steel production was estimated under two case; BaU case (No countermeasures) and CM case (With countermeasures). For all the estimation periods, crude steel production is greater than generation of iron scrap. This makes it impossible to substitute electric arc furnaces for all the basic oxygen furnaces. Even though 100% recycling rate of iron scrap, under BaU case, CO2 emission in 2050 increases by 12% compared to that in 2005. With same condition, 32% of CO2 emission reduction is achieved in CM case. With a constraint from demand side, the reduction potential is 6% (CM case).

Keywords: iron scrap recycling, CO2 emission reduction, steel demand, MSFM demand

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Authors: Yasser Mahmoudi, Nader Karimi

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The present work investigates numerically the effect of thermal radiation from the solid phase on the rate of heat transfer inside a porous medium. Forced convection heat transfer process within a pipe filled with a porous media is considered. The Darcy-Brinkman-Forchheimer model is utilized to represent the fluid transport within the porous medium. A local thermal non-equilibrium (LTNE), two-equation model is used to represent the energy transport for the solid and fluid phases. The radiative heat transfer equation is solved by discrete ordinate method (DOM) to compute the radiative heat flux in the porous medium. Two primary approaches (models A and B) are used to represent the boundary conditions for constant wall heat flux. The effects of radiative heat transfer on the Nusselt numbers of the two phases are examined by comparing the results obtained by the application of models A and B. The fluid Nusselt numbers calculated by the application of models A and B show that the Nusselt number obtained by model A for the radiative case is higher than those predicted for the non-radiative case. However, for model B the fluid Nusselt numbers obtained for the radiative and non-radiative cases are similar.

Keywords: porous media, local thermal non-equilibrium, forced convection heat transfer, thermal radiation, Discrete Ordinate Method (DOM)

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Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

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Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

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Authors: Kulin Dave, Kapil Mohan

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Earthquakes are considered to be the most destructive rapid-onset disasters human beings are exposed to. The amount of loss it brings in is sufficient to take careful considerations for designing of structures and facilities. Seismic Hazard Analysis is one such tool which can be used for earthquake resistant design. Ground Response Analysis is one of the most crucial and decisive steps for seismic hazard analysis. Rapar district of Kutch, Gujarat falls in Zone 5 of earthquake zone map of India and thus has high seismicity because of which it is selected for analysis. In total 8 bore-log data were studied at different locations in and around Rapar district. Different soil engineering properties were analyzed and relevant empirical correlations were used to calculate maximum shear modulus (Gmax) and shear wave velocity (Vs) for the soil layers. The soil was modeled using Pressure-Dependent Modified Kodner Zelasko (MKZ) model and the reference curve used for fitting was Seed and Idriss (1970) for sand and Darendeli (2001) for clay. Both Equivalent linear (EL), as well as Non-linear (NL) ground response analysis, has been carried out with Masing Hysteretic Re/Unloading formulation for comparison. Commercially available DEEPSOIL v. 7.0 software is used for this analysis. In this study an attempt is made to quantify ground response regarding generated acceleration time-history at top of the soil column, Response spectra calculation at 5 % damping and Fourier amplitude spectrum calculation. Moreover, the variation of Peak Ground Acceleration (PGA), Maximum Displacement, Maximum Strain (in %), Maximum Stress Ratio, Mobilized Shear Stress with depth is also calculated. From the study, PGA values estimated in rocky strata are nearly same as bedrock motion and marginal amplification is observed in sandy silt and silty clays by both analyses. The NL analysis gives conservative results of maximum displacement as compared to EL analysis. Maximum strain predicted by both studies is very close to each other. And overall NL analysis is more efficient and realistic because it follows the actual hyperbolic stress-strain relationship, considers stiffness degradation and mobilizes stresses generated due to pore water pressure.

Keywords: DEEPSOIL v 7.0, ground response analysis, pressure-dependent modified Kodner Zelasko model, MKZ model, response spectra, shear wave velocity

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Authors: Christoph Hacker, Zeynep Karahaliloglu, Gunnar Seide, Emir Baki Denkbas, Thomas Gries

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A wound dressing material is designed to facilitate wound healing and minimize scarring. An ideal wound dressing material should protect the wound from any contaminations of exogeneous microorganism. In addition, the dressing material should provide a moist environment through extraction of body fluid from the wound area. Recently, wound dressing electrospun nanofibrous membranes are produced by electrospinning from a polymer solution or a polymer melt. These materials have a great potential as dressing materials for wound healing because of superior properties such as high surface-to-volume ratio, high porosity with excellent pore interconnectivity. Melt electrospinning is an attractive tissue engineering scaffold manufacturing process which eliminated the health risk posed by organic solvents used in electrospinning process and reduced the production costs. In this study, antibacterial wound dressing materials were prepared from TPU (Elastollan 1185A) by a melt-electrospinning technique. The electrospinning parameters for an efficient melt-electrospinning process of TPU were optimized. The surface of the fibers was modified with poly(ethylene glycol) (PEG) by radio-frequency glow discharge plasma deposition method and with silver nanoparticles (nAg) to improve their wettability and antimicrobial properties. TPU melt-electrospun mats were characterized using SEM, DSC, TGA and XPS. The cell viability and proliferation on modified melt-electrospun TPU mats were evaluated using a mouse fibroblast cell line (L929). Antibacterial effects of theirs against both Staphylococcus aureus strain and Escherichia coli were investigated by disk-diffusion method. TPU was successfully processed into a porous, fibrous network of beadless fibers in the micrometer range (4.896±0.94 µm) with a voltage of 50 kV, a working distance of 6 cm, a temperature of the thermocouple and hot coil of 225–230ºC, and a flow rate of 0.1 mL/h. The antibacterial test indicated that PEG-modified nAg-loaded TPU melt-electrospun structure had excellent antibacterial effects and cell study results demonstrated that nAg-loaded TPU mats had no cytotoxic effect on the fibroblast cells. In this work, the surface of a melt-electrospun TPU mats was modified via PEG monomer and then nAg. Results showed melt-electrospun TPU mats modified with PEG and nAg have a great potential for use as an antibacterial wound dressing material and thus, requires further investigation.

Keywords: melt electrospinning, nanofiber, silver nanoparticles, wound dressing

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Authors: Yuchen Chen, Dehong Li, Bin Li, Denis Rodrigue, Xiaodong (Alice) Wang

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When selecting insulation materials, not only should their thermal efficiency be considered, but also their impact on the environment. Compared to conventional insulation materials, bio-based materials not only have comparable thermal performance, but they also have a lower embodied energy. Sheep wool has the advantages of low negative health impact, high fire resistance, eco-friendliness, and high moisture resistance. However, studies on applying sheep wool insulation in cold and humid climates are still insufficient. The purpose of this study is to simulate the hygrothermal performance of sheep wool insulation for the Quebec City climate, as well as analyze the mold growth risks. The results show that a sheep wool wall has better thermal performance than a reference wall and that both meet the minimum requirements of the Quebec Code for the thermal performance of above-ground walls. The total water content indicates that the sheep wool wall can reach dynamic equilibrium in the Quebec climate and can dry out. At the same time, a delay of almost four months in the maximum total water content indicates that the sheep wool wall has high moisture absorption compared to the reference wall. The hygrothermal profiles show that the sheathing-insulation interface of both walls is at the highest risk for condensation. When the interior surface gypsum was replaced by stucco, the mold index significantly dropped.

Keywords: sheep wool, water content, hygrothermal performance, mould growth risk

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Authors: Usman Abubakar, Xiaoyuan Wang, Sayyed Haleem Shah, Sadiq Ur Rahman, Rabiu Saleh Zakariyya

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High-speed Permanent magnet synchronous machine (HSPMSM) uses in different industrial applications like blowers, compressors as a result of its superb performance. Nevertheless, the over-temperature rise of both winding and PM is one of their substantial problem for a high-power HSPMSM, which affects its lifespan and performance. According to the literature, HSPMSM with a Hybrid cooling configuration has a much lower temperature rise than non-hybrid cooling. This paper presents the design 185kW, 26K rpm with two different cooling configurations, i.e., hybrid cooling configuration (forced air and housing spiral water jacket) and non-hybrid (forced air cooling assisted with winding’s potting material and sleeve’s material) to enhance the heat dissipation of winding and PM respectively. Firstly, the machine’s electromagnetic design is conducted by the finite element method to accurately account for machine losses. Then machine’s cooling configurations are introduced, and their effectiveness is validated by lumped parameter thermal network (LPTN). Investigation shows that using potting, sleeve materials to assist non-hybrid cooling configuration makes the machine’s winding and PM temperature closer to hybrid cooling configuration. Therefore, the machine with non-hybrid cooling is prototyped and tested due to its simplicity, lower energy consumption and can still maintain the lifespan and performance of the HSPMSM.

Keywords: airflow network, axial ventilation, high-speed PMSM, thermal network

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Peter C. St. John, Michael F. Crowley, Yannick J. Bomble

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Production of chemicals from engineered organisms in a batch culture typically involves a trade-off between productivity, yield, and titer. However, strategies for strain design typically involve designing mutations to achieve the highest yield possible while maintaining growth viability. Such approaches tend to follow the principle of designing static networks with minimum metabolic functionality to achieve desired yields. While these methods are computationally tractable, optimum productivity is likely achieved by a dynamic strategy, in which intracellular fluxes change their distribution over time. One can use multi-stage fermentations to increase either productivity or yield. Such strategies would range from simple manipulations (aerobic growth phase, anaerobic production phase), to more complex genetic toggle switches. Additionally, some computational methods can also be developed to aid in optimizing two-stage fermentation systems. One can assume an initial control strategy (i.e., a single reaction target) in maximizing productivity - but it is unclear how close this productivity would come to a global optimum. The calculation of maximum theoretical yield in metabolic engineering can help guide strain and pathway selection for static strain design efforts. Here, we present a method for the calculation of a maximum theoretical productivity of a batch culture system. This method follows the traditional assumptions of dynamic flux balance analysis: that internal metabolite fluxes are governed by a pseudo-steady state and external metabolite fluxes are represented by dynamic system including Michealis-Menten or hill-type regulation. The productivity optimization is achieved via dynamic programming, and accounts explicitly for an arbitrary number of fermentation stages and flux variable changes. We have applied our method to succinate production in two common microbial hosts: E. coli and A. succinogenes. The method can be further extended to calculate the complete productivity versus yield Pareto surface. Our results demonstrate that nearly optimal yields and productivities can indeed be achieved with only two discrete flux stages.

Keywords: A. succinogenes, E. coli, metabolic engineering, metabolite fluxes, multi-stage fermentations, succinate

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Authors: Cagri Mollamahmutoglu, Aykut Levent, Ali Mercan

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Micro-beams are one of the most common components of Nano-Electromechanical Systems (NEMS) and Micro Electromechanical Systems (MEMS). For this reason, static bending, buckling, and free vibration analysis of micro-beams have been the subject of many studies. In addition, micro-beams restrained with elastic type foundations have been of particular interest. In the analysis of microstructures, closed-form solutions are proposed when available, but most of the time solutions are based on numerical methods due to the complex nature of the resulting differential equations. Thus, a robust and efficient solution method has great importance. In this study, a mixed finite element formulation is obtained for a functionally graded Timoshenko micro-beam resting on two-parameter elastic foundation. In the formulation modified couple stress theory is utilized for the micro-scale effects. The equation of motion and boundary conditions are derived according to Hamilton’s principle. A functional, derived through a scientific procedure based on Gateaux Differential, is proposed for the bending and buckling analysis which is equivalent to the governing equations and boundary conditions. Most important advantage of the formulation is that the mixed finite element formulation allows usage of C₀ type continuous shape functions. Thus shear-locking is avoided in a built-in manner. Also, element matrices are sparsely populated and can be easily calculated with closed-form integration. In this framework results concerning the effects of micro-scale length parameter, power-law parameter, aspect ratio and coefficients of partially or fully continuous elastic foundation over the static bending, buckling, and free vibration response of FG-micro-beam under various boundary conditions are presented and compared with existing literature. Performance characteristics of the presented formulation were evaluated concerning other numerical methods such as generalized differential quadrature method (GDQM). It is found that with less computational burden similar convergence characteristics were obtained. Moreover, formulation also includes a direct calculation of the micro-scale related contributions to the structural response as well.

Keywords: micro-beam, functionally graded materials, two-paramater elastic foundation, mixed finite element method

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Authors: Noorizal Huang, Christian Girsang, Mohamad Razi Mansoor

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Shallow gas seepage was first spotted at a central processing platform offshore Malaysia in 2010, acknowledged as Platform T in this paper. Frequent monitoring of the gas seepage was performed through remotely operated vehicle (ROV) baseline survey and a comprehensive geophysical survey was conducted to understand the characteristics of the gas seepage and to ensure that the integrity of the foundation at Platform T was not compromised. The origin of the gas back then was unknown. A soil investigation campaign was performed in 2016 to study the origin of the gas seepage. Two boreholes were drilled; a composite borehole to 150m below seabed for the purpose of soil sampling and in-situ testing and a pilot hole to 155m below the seabed, which was later converted to a fit-for-purpose relief well as an alternate migration path for the gas. During the soil investigation campaign, dissipation tests were performed at several layers which were potentially the source or migration path for the gas. Five (5) soil samples were segregated for headspace test, to identify the gas type which subsequently can be used to identify the origin of the gas. Dissipation tests performed at four depth intervals indicates pore water pressure less than 20 % of the effective vertical stress and appear to continue decreasing if the test had not been stopped. It was concluded that a low to a negligible amount of excess pore pressure exist in clayey silt layers. Results from headspace test show presence of methane corresponding to the clayey silt layers as reported in the boring logs. The gas most likely comes from biogenic sources, feeding on organic matter in situ over a large depth range. It is unlikely that there are large pockets of gas in the soil due to its homogeneous clayey nature and the lack of excess pore pressure in other permeable clayey silt layers encountered. Instead, it is more likely that when pore water at certain depth encounters a more permeable path, such as a borehole, it rises up through this path due to the temperature gradient in the soil. As the water rises the pressure decreases, which could cause gases dissolved in the water to come out of solution and form bubbles. As a result, the gas will have no impact on the integrity of the foundation at Platform T. The fit-for-purpose relief well design as well as adopting headspace testing can be used to address the shallow gas issue at Platform T in a cost effective and efficient manners.

Keywords: dissipation test, headspace test, excess pore pressure, relief well, shallow gas

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Authors: Yasser Mahmoudi, Nader Karimi

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The present work examines analytically the effect internal heat generation on temperature fields in a channel partially-filled with a porous under local thermal non-equilibrium condition. The Darcy-Brinkman model is used to represent the fluid transport through the porous material. Two fundamental models (models A and B) represent the thermal boundary conditions at the interface between the porous medium and the clear region. The governing equations of the problem are manipulated, and for each interface model, exact solutions for the solid and fluid temperature fields are developed. These solutions incorporate the porous material thickness, Biot number, fluid to solid thermal conductivity ratio Darcy number, as the non-dimensional energy terms in fluid and solid as parameters. Results show that considering any of the two models and under zero or negative heat generation (heat sink) and for any Darcy number, an increase in the porous thickness increases the amount of heat flux transferred to the porous region. The obtained results are applicable to the analysis of complex porous media incorporating internal heat generation, such as heat transfer enhancement (THE), tumor ablation in biological tissues and porous radiant burners (PRBs).

Keywords: porous media, local thermal non-equilibrium, forced convection, heat transfer, exact solution, internal heat generation

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Authors: Arunava Chakrabarti

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A one-dimensional chain of magnetic atoms, representative of a quantum gas in an artificial quasi-periodic potential and modeled by the well-known Aubry-Andre function and its variants are studied in respect of its capability of working as a spin filter for arbitrary spins. The basic formulation is explained in terms of a perfectly periodic chain first, where it is shown that a definite correlation between the spin S of the incoming particles and the magnetic moment h of the substrate atoms can open up a gap in the energy spectrum. This is crucial for a spin filtering action. The simple one-dimensional chain is shown to be equivalent to a 2S+1 strand ladder network. This equivalence is exploited to work out the condition for the opening of gaps. The formulation is then applied for a one-dimensional chain with quasi-periodic variation in the site potentials, the magnetic moments and their orientations following an Aubry-Andre modulation and its variants. In addition, we show that a certain correlation between the system parameters can generate absolutely continuous bands in such systems populated by Bloch like extended wave functions only, signaling the possibility of a metal-insulator transition. This is a case of correlated disorder (a deterministic one), and the results provide a non-trivial variation to the famous Anderson localization problem. We have worked within a tight binding formalism and have presented explicit results for the spin half, spin one, three halves and spin five half particles incident on the magnetic chain to explain our scheme and the central results.

Keywords: Aubry-Andre model, correlated disorder, localization, spin filter

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Authors: Majid Farsadrooh, Mehran Feizi-Dehnayebi

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Serum albumin is the most abundant protein that is present in the circulatory system of a wide variety of organisms. Although it is a significant macromolecule, it can contribute to osmotic blood pressure and also, plays a superior role in drug disposition and efficiency. Molecular docking simulation can improve in silico drug design and discovery procedures to propound a lead compound and develop it from the discovery step to the clinic. In this study, the molecular docking simulation was applied to select a lead molecule through an investigation of the interaction of the two anticancer drugs (Alitretinoin and Abemaciclib) with Human Serum Albumin (HSA). Then, a series of new compounds (a-e) were suggested using lead molecule modification. Density functional theory (DFT) including MEP map and HOMO-LUMO analysis were used for the newly proposed compounds to predict the reactivity zones on the molecules, stability, and chemical reactivity. DFT calculation illustrated that these new compounds were stable. The estimated binding free energy (ΔG) values for a-e compounds were obtained as -5.78, -5.81, -5.95, -5,98, and -6.11 kcal/mol, respectively. Finally, the pharmaceutical properties and toxicity of these new compounds were estimated through OSIRIS DataWarrior software. The results indicated no risk of tumorigenic, irritant, or reproductive effects and mutagenicity for compounds d and e. As a result, compounds d and e, could be selected for further study as potential therapeutic candidates. Moreover, employing molecular docking simulation with the prediction of pharmaceutical properties helps to discover new potential drug compounds.

Keywords: drug design, anticancer, computational studies, DFT analysis

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Authors: Di Wang, Li Fang, Shengyu Fang, Jianhua Li, Honghong Dong, Zhongzhi Zhang

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Heavy oily refinery wastewater with the characteristics of high concentration of toxic organic pollutant, poor biodegradability and complicated dissolved recalcitrant compounds is intractable to be degraded. In order to reduce the concentrations of COD and total nitrogen pollutants which are the major pollutants in heavy oily refinery wastewater, the Anoxic - Oxic microbiological technology relies mainly on anaerobic microbial reactor which works with methanogenic archaea mainly that can convert organic pollutants to methane gas, and supplemented by aerobic treatment. The results of continuous operation for 2 months with a hydraulic retention time (HRT) of 60h showed that, the COD concentration from influent water of anaerobic reactor and effluent water from aerobic reactor were 547.8mg/L and 93.85mg/L, respectively. The total removal rate of COD was up to 84.9%. Compared with the 46.71mg/L of total nitrogen pollutants in influent water of anaerobic reactor, the concentration of effluent water of aerobic reactor decreased to 14.11mg/L. In addition, the average removal rate of total nitrogen pollutants reached as high as 69.8%. Based on the data displayed, Anoxic - Oxic microbial technology shows a great potential to dispose heavy oil sewage in energy saving and high-efficiency of biodegradation.

Keywords: anoxic - oxic microbiological technology, COD, heavy oily refinery wastewater, total nitrogen pollutant

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Authors: Majid Farsadrooh, Najmeh Sabbaghi, Seyed Mohammad Mostashari, Abolhasan Moradi

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Phenolic compounds are chief environmental contaminants on account of their hazardous and toxic nature on human health. The preparation of sensitive and potent chemosensors to monitor emerging pollution in water and effluent samples has received great consideration. A novel and versatile nanocomposite sensor based on poly pyrogallol is presented for the first time in this study, and its electrochemical behavior for simultaneous detection of hydroquinone (HQ), catechol (CT), and resorcinol (RS) in the presence of nitrite is evaluated. The physicochemical characteristics of the fabricated nanocomposite were investigated by emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy (EDS), and Brunauer-Emmett-Teller (BET). The electrochemical response of the proposed sensor to the detection of HQ, CT, RS, and nitrite is studied using cyclic voltammetry (CV), chronoamperometry (CA), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The kinetic characterization of the prepared sensor showed that both adsorption and diffusion processes can control reactions at the electrode. In the optimized conditions, the new chemosensor provides a wide linear range of 0.5-236.3, 0.8-236.3, 0.9-236.3, and 1.2-236.3 μM with a low limit of detection of 21.1, 51.4, 98.9, and 110.8 nM (S/N = 3) for HQ, CT and RS, and nitrite, respectively. Remarkably, the electrochemical sensor has outstanding selectivity, repeatability, and stability and is successfully employed for the detection of RS, CT, HQ, and nitrite in real water samples with the recovery of 96.2%–102.4%, 97.8%-102.6%, 98.0%–102.4% and 98.4%–103.2% for RS, CT, HQ, and nitrite, respectively. These outcomes illustrate that poly pyrogallol is a promising candidate for effective electrochemical detection of dihydroxybenzene isomers in the presence of nitrite.

Keywords: electrochemical sensor, poly pyrogallol, phenolic compounds, simultaneous determination

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Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: analytics, digitization, industry 4.0, manufacturing

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Authors: Rui Teixeira, Alan O’Connor, Maria Nogal

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The statistical theory of extreme events is progressively a topic of growing interest in all the fields of science and engineering. The changes currently experienced by the world, economic and environmental, emphasized the importance of dealing with extreme occurrences with improved accuracy. When it comes to the design of offshore structures, particularly offshore wind turbines, the importance of efficiently characterizing extreme events is of major relevance. Extreme events are commonly characterized by extreme values theory. As an alternative, the accurate modeling of the tails of statistical distributions and the characterization of the low occurrence events can be achieved with the application of the Peak-Over-Threshold (POT) methodology. The POT methodology allows for a more refined fit of the statistical distribution by truncating the data with a minimum value of a predefined threshold u. For mathematically approximating the tail of the empirical statistical distribution the Generalised Pareto is widely used. Although, in the case of the exceedances of significant wave data (H_s) the 2 parameters Weibull and the Exponential distribution, which is a specific case of the Generalised Pareto distribution, are frequently used as an alternative. The Generalized Pareto, despite the existence of practical cases where it is applied, is not completely recognized as the adequate solution to model exceedances over a certain threshold u. References that set the Generalised Pareto distribution as a secondary solution in the case of significant wave data can be identified in the literature. In this framework, the current study intends to tackle the discussion of the application of statistical models to characterize exceedances of wave data. Comparison of the application of the Generalised Pareto, the 2 parameters Weibull and the Exponential distribution are presented for different values of the threshold u. Real wave data obtained in four buoys along the Irish coast was used in the comparative analysis. Results show that the application of the statistical distributions to characterize significant wave data needs to be addressed carefully and in each particular case one of the statistical models mentioned fits better the data than the others. Depending on the value of the threshold u different results are obtained. Other variables of the fit, as the number of points and the estimation of the model parameters, are analyzed and the respective conclusions were drawn. Some guidelines on the application of the POT method are presented. Modeling the tail of the distributions shows to be, for the present case, a highly non-linear task and, due to its growing importance, should be addressed carefully for an efficient estimation of very low occurrence events.

Keywords: extreme events, offshore structures, peak-over-threshold, significant wave data

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Authors: Teemu Saressalo

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This article examines the evolution of the Israel Defence Forces’ information operation activities during an eight-year timespan from the 2006 war with Hezbollah to more recent operations such as Pillar of Defence and Protective Edge. To this end, the case study will show a change in the Israel Defence Forces’ activities in the information domain. In the 2006 war with Hezbollah in Lebanon, Israel inflicted enormous damage on the Lebanese infrastructure, leaving more than 1,200 people dead and 4,400 injured. Casualties among Hezbollah, Israel’s main adversary, were estimated to range from 250 to 700 fighters. Damage to the Lebanese infrastructure was estimated at over USD 2.5bn, with almost 2,000 houses and buildings damaged and destroyed. Even this amount of destruction did not force Hezbollah to yield and while both sides were claiming victory in the war, Israel paid a heavier price in political backlashes and loss of reputation, mainly due to failures in the media and the way in which the war was portrayed and perceived in Israel and abroad. Much of this can be credited to Hezbollah’s efficient use of the media, and Israel’s failure to do so. Israel managed the next conflict it was engaged in completely differently – it had learnt its lessons and built up new ways to counter its adversary’s propaganda and media operations. In Operation Cast Lead at the turn of 2009, Hamas, Israel’s adversary and Gaza’s dominating faction, was not able to utilize the media in the same way that Hezbollah had. By creating a virtual and physical barrier around the Gaza Strip, Israel almost totally denied its adversary access to the worldwide media, and by restricting the movement of journalists in the area, Israel could let its voice be heard above all. The operation Cast Lead began with a deception operation, which caught Hamas totally off guard. The 21-day campaign left the Gaza Strip devastated, but did not cause as much protest in Israel during the operation as the 2006 war did, mainly due to almost total Israeli dominance in the information dimension. The most important outcome from the Israeli perspective was the fact that Operation Cast Lead was assessed to be a success and the operation enjoyed domestic support along with support from many western nations, which had condemned Israeli actions in the 2006 war. Later conflicts have shown the same tendency towards virtually total dominance in the information domain, which has had an impact on target audiences across the world. Thus, it is clear that well-planned and conducted information operations are able to shape public opinion and influence decision-makers, although Israel might have been outpaced by its rivals.

Keywords: Hamas, Hezbollah, information operations, Israel Defence Forces

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Authors: Mateusz Paszko, Ksenia Siadkowska

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Due to the low-altitude and relatively low-speed flight, helicopters are easy targets for actual combat assets e.g. infrared-guided missiles. Current techniques aim to increase the combat effectiveness of the military helicopters. Protection of the helicopter in flight from early detection, tracking and finally destruction can be realized in many ways. One of them is cooling hot exhaust gasses, emitting from the engines to the atmosphere in special heat exchangers. Nowadays, this process is realized in ejective coolers, where strong heat and momentum exchange between hot exhaust gases and cold air ejected from atmosphere takes place. Flow effects of air, exhaust gases; mixture of those two and the heat transfer between cold air and hot exhaust gases are given by differential equations of: Mass transportation–flow continuity, ejection of cold air through expanding exhaust gasses, conservation of momentum, energy and physical relationship equations. Calculation of those processes in ejective cooler by means of classic mathematical analysis is extremely hard or even impossible. Because of this, it is necessary to apply the numeric approach with modern, numeric computer programs. The paper discussed the general usability of the Computational Fluid Dynamics (CFD) in a process of projecting the ejective exhaust gases cooler cooperating with helicopter turbine engine. In this work, the CFD calculations have been performed for ejective-based cooler cooperating with the PA W3 helicopter’s engines.

Keywords: aviation, CFD analysis, ejective-cooler, helicopter techniques

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Authors: Oluwole Durodolu

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The rationale for this study is to explore the adaptive strategy that librarians adopt in performing night shifts in a mega-city like Lagos state. Maslach Burnout Theory would be used to measure the three proportions of burnout in understanding emotional exhaustion, depersonalisation, and individual accomplishment to scrutinise job-related burnout syndrome allied with longstanding, unsolved stress. The qualitative methodology guided by a phenomenological research paradigm, which is an approach that focuses on the commonality of real-life experience in a particular group, would be used, focus group discussion adopted as a method of data collection from library staff who are involved in night-shift. The participant for the focus group discussion would be selected using a convenience sampling technique in which staff at the cataloguing unit would be included in the sample because of the representative characteristics of the unit. This would be done to enable readers to understand phenomena as it is reasonable than from a remote perspective. The exploratory interviews which will be in focus group method to shed light on issues relating to security, housing, transportation, budgeting, energy supply, employee duties, time management, information access, and sustaining professional levels of service and how all these variables affect the productivity of all the 149 library staff and their work-life balance.

Keywords: nightshift, work-life balance, mega-city, academic library, Maslach Burnout Theory, Lagos State, University of Lagos

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Authors: Atousa Khodadadyan, Ali Rostami

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The objective of off-site construction manufacturing is to utilise the workforce and machinery in a controlled environment without external interference for higher productivity and quality. The usage of prefabricated components can save up to 14% of the total energy consumption in comparison with the equivalent number of cast-in-place ones. Despite the benefits of prefabrication construction, its current project practices encompass technical and managerial issues. Building design, precast components’ production, logistics, and prefabrication installation processes are still mostly discontinued and fragmented. Furthermore, collaboration among prefabrication manufacturers, transportation parties, and on-site assemblers rely on real-time information such as the status of precast components, delivery progress, and the location of components. From the technical point of view, in this industry, geometric variability is still prevalent, which can be caused during the transportation or production of components. These issues indicate that there are still many aspects of prefabricated construction that can be developed using disruptive technologies. Practical real-time risk analysis can be used to address these issues as well as the management of safety, quality, and construction environment issues. On the other hand, the lack of research about risk assessment and the absence of standards and tools hinder risk management modeling in prefabricated construction. It is essential to note that no risk management standard has been established explicitly for prefabricated construction projects, and most software packages do not provide tailor-made functions for this type of projects.

Keywords: project risk management, risk analysis, risk modelling, prefabricated construction projects

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Authors: Mark T. Hanson, Alan T. Varughese

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Osteoporosis is a disease affecting bone quality which in turn can increase the risk of low energy fractures. Treatment of osteoporosis using Bisphosphonates has the beneficial effect of increasing bone mass while at the same time has been linked to the formation of atypical femoral fractures. This has led to the increased study of micro-fractures in bones of patients using Bisphosphonate treatment. One of the mechanics related issues which have been identified in this regard is the loss in stiffness of bones containing one or many micro-fractures. Different theories have been put forth using fracture mechanics to determine the effect of crack presence on elastic properties such as modulus. However, validation of these results in a deterministic way has not been forthcoming. The present analysis seeks to provide this deterministic evaluation of fracture’s effect on the elastic modulus. In particular, the effect of crack size, crack orientation and crack number on elastic modulus is investigated. In particular, the Finite Element method is used to explicitly determine the elastic modulus reduction caused by the presence of cracks in a representative volume element. Single cracks of various lengths and orientations are examined as well as cases of multiple cracks. Cracks in tension as well as under shear stress are considered. Although the focus is predominantly two-dimensional, some three-dimensional results are also presented. The results obtained show the explicit reduction in modulus caused by the parameters of crack size, orientation and number noted above. The present results allow the interpretation of the various theories which currently exist in the literature.

Keywords: cracks, elastic, fracture, modulus

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Authors: Glenn Auld Knierim

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Automated robotic winding of high-temperature superconductors (HTS) addresses precision, efficiency, and reliability critical to the commercialization of products. Today’s HTS materials are mature and commercially promising but require manufacturing attention. In particular to the exaggerated rectangular cross-section (very thin by very wide), winding precision is critical to address the stress that can crack the fragile ceramic superconductor (SC) layer and destroy the SC properties. Damage potential is highest during peak operations, where winding stress magnifies operational stress. Another challenge is operational parameters such as magnetic field alignment affecting design performance. Winding process performance, including precision, capability for geometric complexity, and efficient repeatability, are required for commercial production of current HTS. Due to winding limitations, current HTS magnets focus on simple pancake configurations. HTS motors, generators, MRI/NMR, fusion, and other projects are awaiting robotic wound solenoid, planar, and spherical magnet configurations. As with conventional power cables, full transposition winding is required for long length alternating current (AC) and pulsed power cables. Robotic production is required for transposition, periodic swapping of cable conductors, and placing into precise positions, which allows power utility required minimized reactance. A full transposition SC cable, in theory, has no transmission length limits for AC and variable transient operation due to no resistance (a problem with conventional cables), negligible reactance (a problem for helical wound HTS cables), and no long length manufacturing issues (a problem with both stamped and twisted stacked HTS cables). The Infinity Physics team is solving manufacturing problems by developing automated manufacturing to produce the first-ever reliable and utility-grade commercial SC cables and magnets. Robotic winding machines combine mechanical and process design, specialized sense and observer, and state-of-the-art optimization and control sequencing to carefully manipulate individual fragile SCs, especially HTS, to shape previously unattainable, complex geometries with electrical geometry equivalent to commercially available conventional conductor devices.

Keywords: automated winding manufacturing, high temperature superconductor, magnet, power cable

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Authors: Dinesh Pathaka, Tomas Wagnera, J. M. Nunzib

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We investigated blends of MdPVV.PCBM.AIS for photovoltaic application. AgInSe2 powder was synthesized by sealing and heating the stoichiometric constituents in evacuated quartz tube ampule. Fine grinded AIS powder was dispersed in MD-MOPVV and PCBM with and without surfactant. Different concentrations of these particles were suspended in the polymer solutions and spin casted onto ITO glass. Morphological studies have been performed by atomic force microscopy and optical microscopy. The blend layers were also investigated by various techniques like XRD, UV-VIS optical spectroscopy, AFM, PL, after a series of various optimizations with polymers/concentration/deposition/ suspension/surfactants etc. XRD investigation of blend layers shows clear evidence of AIS dispersion in polymers. Diode behavior and cell parameters also revealed it. Bulk heterojunction hybrid photovoltaic device Ag/MoO3/MdPVV.PCBM.AIS/ZnO/ITO was fabricated and tested with standard solar simulator and device characterization system. The best performance and photovoltaic parameters we obtained was an open-circuit voltage of about Voc 0.54 V and a photocurrent of Isc 117 micro A and an efficiency of 0.2 percent using a white light illumination intensity of 23 mW/cm2. Our results are encouraging for further research on the fourth generation inorganic organic hybrid bulk heterojunction photovoltaics for energy. More optimization with spinning rate/thickness/solvents/deposition rates for active layers etc. need to be explored for improved photovoltaic response of these bulk heterojunction devices.

Keywords: thin films, photovoltaic, hybrid systems, heterojunction

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