Search results for: meshes for numerical simulations

Authors: Yepeng Cheng, Yasuhiko Morimoto

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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: customer value, Huff's Gravity Model, POS, Retailer

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Authors: Gopika Rajagopal, Sudheesh Thiyyakkandi

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Back-to-back reinforced earth (RE) walls are extensively used in these days as bridge abutments and highway ramps, owing to their cost efficiency and ease of construction. High quality select fill is the most suitable backfill material due to its excellent engineering properties and constructability. However, industries are compelled to use low quality, locally available soil because of its ample availability on site. However, several failure cases of such walls are reported, especially subsequent to rainfall events. The stiffness of reinforcement is one of the major factors affecting the performance of RE walls. The present study focused on analyzing the effect of reinforcement stiffness on the performance of complete select fill, complete marginal fill, and hybrid-fill (i.e., combination of select and marginal fills) back-to-back RE walls, immediately after construction and upon rainwater infiltration through finite element modelling. A constant width to height (W/H) ratio of 3 and height (H) of 6 m was considered for the numerical analysis and the stiffness of reinforcement layers was varied from 500 kN/m to 10000 kN/m. Results showed that reinforcement stiffness had a noticeable influence on the response of RE wall, subsequent to construction as well as rainwater infiltration. Facing displacement was found to decrease and maximum reinforcement tension and factor of safety were observed to increase with increasing the stiffness of reinforcement. However, beyond a stiffness of 5000 kN/m, no significant reduction in facing displacement was observed. The behavior of fully marginal fill wall considered in this study was found to be reasonable even after rainwater infiltration when the high stiffness reinforcement layers are used.

Keywords: back-to-back reinforced earth wall, finite element modelling, rainwater infiltration, reinforcement stiffness

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Authors: David C. Ni

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Contemporary models for N-body systems are based on temporal, two-body, and mass point representation of Newtonian mechanics. Other mainstream models include 2D and 3D Ising models based on local neighborhood the lattice structures. In Quantum mechanics, the theories of collective modes are for superconductivity and for the long-range quantum entanglement. However, these models are still mainly for the specific phenomena with a set of designated parameters. We are therefore motivated to develop a new construction directly from the complex-variable N-body systems based on the extended Blaschke functions (EBF), which represent a non-temporal and nonlinear extension of Lorentz transformation on the complex plane – the normalized momentum spaces. A point on the complex plane represents a normalized state of particle momentums observed from a reference frame in the theory of special relativity. There are only two key parameters, normalized momentum and nonlinearity for modelling. An algorithm similar to Jenkins-Traub method is adopted for solving EBF iteratively. Through iteration, the solution sets show a form of σ + i [-t, t], where σ and t are the real numbers, and the [-t, t] shows various distributions, such as 1-peak, 2-peak, and 3-peak etc. distributions and some of them are analog to the canonical distributions. The results of the numerical analysis demonstrate continuum-to-discreteness transitions, evolutional invariance of distributions, phase transitions with conjugate symmetry, etc., which manifest the construction as a potential candidate for the unification of statistics. We hereby classify the observed distributions on the finite convergent domains. Continuous and discrete distributions both exist and are predictable for given partitions in different regions of parameter-pair. We further compare these distributions with canonical distributions and address the impacts on the existing applications.

Keywords: blaschke, lorentz transformation, complex variables, continuous, discrete, canonical, classification

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Authors: Yi-Ling Chen, Dung-Ying Lin

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In the manufacturing process, computer numerical control (CNC) machining plays a crucial role. CNC enables precise machinery control through computer programs, achieving automation in the production process and significantly enhancing production efficiency. However, traditional CNC production lines often require manual intervention for loading and unloading operations, which limits the production line's operational efficiency and production capacity. Additionally, existing CNC automation systems frequently lack sufficient intelligence and fail to achieve optimal configuration efficiency, resulting in the need for substantial time to reconfigure production lines when producing different products, thereby impacting overall production efficiency. Using the NSGA-II algorithm, we generate production line layout configurations that consider field constraints and select robotic arm specifications from an arm list. This allows us to calculate loading and unloading times for each job order, perform demand allocation, and assign processing sequences. The NSGA-II algorithm is further employed to determine the optimal processing sequence, with the aim of minimizing demand completion time and maximizing average machine utilization. These objectives are used to evaluate the performance of each layout, ultimately determining the optimal layout configuration. By employing this method, it enhance the configuration efficiency of CNC production lines and establish an adaptive capability that allows the production line to respond promptly to changes in demand. This will minimize production losses caused by the need to reconfigure the layout, ensuring that the CNC production line can maintain optimal efficiency even when adjustments are required due to fluctuating demands.

Keywords: evolutionary algorithms, multi-objective optimization, pareto optimality, layout optimization, operations sequence

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Authors: Kenneth Harper

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The secure sharing of Electronic Health Records (EHRs) is a critical challenge in modern healthcare, demanding solutions to enhance interoperability, privacy, and data integrity. Traditional standards like Health Information Exchange (HIE) and HL7 have made significant strides in facilitating data exchange between healthcare entities. However, these approaches rely on centralized architectures that are often vulnerable to data breaches, lack sufficient privacy measures, and have scalability issues. This paper proposes a framework for secure, decentralized sharing of EHRs using blockchain technology, cryptographic tokens, and Non-Fungible Tokens (NFTs). The blockchain's immutable ledger, decentralized control, and inherent security mechanisms are leveraged to improve transparency, accountability, and auditability in healthcare data exchanges. Furthermore, we introduce the concept of tokenizing patient data through NFTs, creating unique digital identifiers for each record, which allows for granular data access controls and proof of data ownership. These NFTs can also be employed to grant access to authorized parties, establishing a secure and transparent data sharing model that empowers both healthcare providers and patients. The proposed approach addresses common privacy concerns by employing privacy-preserving techniques such as zero-knowledge proofs (ZKPs) and homomorphic encryption to ensure that sensitive patient information can be shared without exposing the actual content of the data. This ensures compliance with regulations like HIPAA and GDPR. Additionally, the integration of Fast Healthcare Interoperability Resources (FHIR) with blockchain technology allows for enhanced interoperability, enabling healthcare organizations to exchange data seamlessly and securely across various systems while maintaining data governance and regulatory compliance. Through real-world case studies and simulations, this paper demonstrates how blockchain-based EHR sharing can reduce operational costs, improve patient outcomes, and enhance the security and privacy of healthcare data. This decentralized framework holds great potential for revolutionizing healthcare information exchange, providing a transparent, scalable, and secure method for managing patient data in a highly regulated environment.

Keywords: blockchain, electronic health records (ehrs), fast healthcare interoperability resources (fhir), health information exchange (hie), hl7, interoperability, non-fungible tokens (nfts), privacy-preserving techniques, tokens, secure data sharing,

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Authors: Ece Cigdem Mutlu, Burak Alakent

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Maintaining the quality of manufactured products at a desired level depends on the stability of process dispersion and location parameters and detection of perturbations in these parameters as promptly as possible. Shewhart control chart is the most widely used technique in statistical process monitoring to monitor the quality of products and control process mean and variability. In the application of Xbar control charts, sample standard deviation and sample mean are known to be the most efficient conventional estimators in determining process dispersion and location parameters, respectively, based on the assumption of independent and normally distributed datasets. On the other hand, there is no guarantee that the real-world data would be normally distributed. In the cases of estimated process parameters from Phase I data clouded with outliers, efficiency of traditional estimators is significantly reduced, and performance of Xbar charts are undesirably low, e.g. occasional outliers in the rational subgroups in Phase I data set may considerably affect the sample mean and standard deviation, resulting a serious delay in detection of inferior products in Phase II. For more efficient application of control charts, it is required to use robust estimators against contaminations, which may exist in Phase I. In the current study, we present a simple approach to construct robust Xbar control charts using average distance to the median, Qn-estimator of scale, M-estimator of scale with logistic psi-function in the estimation of process dispersion parameter, and Harrell-Davis qth quantile estimator, Hodge-Lehmann estimator and M-estimator of location with Huber psi-function and logistic psi-function in the estimation of process location parameter. Phase I efficiency of proposed estimators and Phase II performance of Xbar charts constructed from these estimators are compared with the conventional mean and standard deviation statistics both under normality and against diffuse-localized and symmetric-asymmetric contaminations using 50,000 Monte Carlo simulations on MATLAB. Consequently, it is found that robust estimators yield parameter estimates with higher efficiency against all types of contaminations, and Xbar charts constructed using robust estimators have higher power in detecting disturbances, compared to conventional methods. Additionally, utilizing individuals charts to screen outlier subgroups and employing different combination of dispersion and location estimators on subgroups and individual observations are found to improve the performance of Xbar charts.

Keywords: average run length, M-estimators, quality control, robust estimators

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Authors: Didier Auroux, Vladimir Groza

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This work is part of STEEP Marie-Curie ITN project, and it focuses on the identification of unknown parameters of the proposed generic Abrasive WaterJet Milling (AWJM) PDE model, that appears as an ill-posed inverse problem. The necessity of studying this problem comes from the industrial milling applications where the possibility to predict and model the final surface with high accuracy is one of the primary tasks in the absence of any knowledge of the model parameters that should be used. In this framework, we propose the identification of model parameters by minimizing a cost function, measuring the difference between experimental and numerical solutions. The adjoint approach based on corresponding Lagrangian gives the opportunity to find out the unknowns of the AWJM model and their optimal values that could be used to reproduce the required trench profile. Due to the complexity of the nonlinear problem and a large number of model parameters, we use an automatic differentiation software tool (TAPENADE) for the adjoint computations. By adding noise to the artificial data, we show that in fact the parameter identification problem is highly unstable and strictly depends on input measurements. Regularization terms could be effectively used to deal with the presence of data noise and to improve the identification correctness. Based on this approach we present results in 2D and 3D of the identification of the model parameters and of the surface prediction both with self-generated data and measurements obtained from the real production. Considering different types of model and measurement errors allows us to obtain acceptable results for manufacturing and to expect the proper identification of unknowns. This approach also gives us the ability to distribute the research on more complex cases and consider different types of model and measurement errors as well as 3D time-dependent model with variations of the jet feed speed.

Keywords: Abrasive Waterjet Milling, inverse problem, model parameters identification, regularization

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Authors: Rukayya Ibrahim Muazu, Aiduan Li Borrion, Julia A. Stegemann

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Biomass briquette gasification is regarded as a promising route for efficient briquette use in energy generation, fuels and other useful chemicals, however, previous research work has focused on briquette gasification in fixed bed gasifiers such as updraft and downdraft gasifiers. Fluidised bed gasifier has the potential to be effectively sized for medium or large scale. This study investigated the use of fuel briquettes produced from blends of rice husks and corn cobs biomass residues, in a bubbling fluidised bed gasifier. The study adopted a combination of numerical equations and Aspen Plus simulation software to predict the product gas (syngas) composition based on briquette's density and biomass composition (blend ratio of rice husks to corn cobs). The Aspen Plus model was based on an experimentally validated model from the literature. The results based on a briquette size of 32 mm diameter and relaxed density range of 500 to 650 kg/m3 indicated that fluidisation air required in the gasifier increased with an increase in briquette density, and the fluidisation air showed to be the controlling factor compared with the actual air required for gasification of the biomass briquettes. The mass flowrate of CO2 in the predicted syngas composition, increased with an increase in the air flow rate, while CO production decreased and H2 was almost constant. The H2/CO ratio for various blends of rice husks and corn cobs did not significantly change at the designed process air, but a significant difference of 1.0 for H2/CO ratio was observed at higher air flow rate, and between 10/90 to 90/10 blend ratio of rice husks to corn cobs. This implies the need for further understanding of biomass variability and hydrodynamic parameters on syngas composition in biomass briquette gasification.

Keywords: aspen plus, briquettes, fluidised bed, gasification, syngas

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Authors: Lori Lioce, Gary Maddux, Norven Goddard, Ishella Fogle, Bernard Schroer

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This paper presents the integration of technologies into nursing education. The collaborative effort includes the College of Nursing (CoN) at the University of Alabama in Huntsville (UAH) and the UAH Systems Management and Production Center (SMAP). The faculty at the CoN conducts needs assessments to identify education and training requirements. A team of CoN faculty and SMAP engineers then prioritize these requirements and establish improvement/development teams. The development teams consist of nurses to evaluate the models and to provide feedback and of undergraduate engineering students and their senior staff mentors from SMAP. The SMAP engineering staff develops and creates the physical models using 3D printing, silicone molds and specialized molding mixtures and techniques. The collaboration has focused on developing teaching and training, or clinical, simulators. In addition, the onset of the Covid-19 pandemic has intensified this relationship, as 3D modeling shifted to supplied personal protection equipment (PPE) to local health care providers. A secondary collaboration has been introducing students to clinical benchmarking through the UAH Center for Management and Economic Research. As a result of these successful collaborations the Model Exchange & Development of Nursing & Engineering Technology (MEDNET) has been established. MEDNET seeks to extend and expand the linkage between engineering and nursing to K-12 schools, technical schools and medical facilities in the region to the resources available from the CoN and SMAP. As an example, stereolithography (STL) files of the 3D printed models, along with the specifications to fabricate models, are available on the MEDNET website. Ten 3D printed models have been developed and are currently in use by the CoN. The following additional training simulators are currently under development:1) suture pads, 2) gelatin wound models and 3) printed wound tattoos. Specification sheets have been written for these simulations that describe the use, fabrication procedures and parts list. These specifications are available for viewing and download on MEDNET. Included in this paper are 1) descriptions of CoN, SMAP and MEDNET, 2) collaborative process used in product improvement/development, 3) 3D printed models of training and teaching simulators, 4) training simulators under development with specification sheets, 5) family care practice benchmarking, 6) integrating the simulators into the nursing curriculum, 7) utilizing MEDNET as a pandemic response, and 8) conclusions and lessons learned.

Keywords: 3D printing, nursing education, simulation, trainers

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Authors: Sohrab Jafarpour, Hamed Farokhi, Mohammad Rahmati, Alireza Gholipour

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In the current study, a nonlinear fluid-structure interaction (FSI) biomechanical model of atherosclerosis in the left anterior descending (LAD) coronary artery is developed to perform a detailed sensitivity analysis of the geometrical features of an atheroma plaque. In the development of the numerical model, first, a 3D geometry of the diseased artery is developed based on patient-specific dimensions obtained from the experimental studies. The geometry includes four influential geometric characteristics: stenosis ratio, plaque shoulder-length, fibrous cap thickness, and eccentricity intensity. Then, a suitable strain energy density function (SEDF) is proposed based on the detailed material stability analysis to accurately model the hyperelasticity of the arterial walls. The time-varying inlet velocity and outlet pressure profiles are adopted from experimental measurements to incorporate the pulsatile nature of the blood flow. In addition, a computationally efficient type of structural boundary condition is imposed on the arterial walls. Finally, a non-Newtonian viscosity model is implemented to model the shear-thinning behaviour of the blood flow. According to the results, the structural responses in terms of the maximum principal stress (MPS) are affected more compared to the fluid responses in terms of wall shear stress (WSS) as the geometrical characteristics are varying. The extent of these changes is critical in the vulnerability assessment of an atheroma plaque.

Keywords: atherosclerosis, fluid-Structure interaction modeling, material stability analysis, and nonlinear biomechanics

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Authors: Rony Tawk, Boutros Ghannam, Maroun Nemer

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Topology optimization technique presents a potential tool for the design and optimization of structures involved in mass and heat transfer. The method starts with an initial intermediate domain and should be able to progressively distribute the solid and the two fluids exchanging heat. The multi-objective function of the problem takes into account minimization of total pressure loss and maximization of heat transfer between solid and fluid subdomains. Existing methods account for the presence of only one fluid, while the actual work extends optimization distribution of solid and two different fluids. This requires to separate the channels of both fluids and to ensure a minimum solid thickness between them. This is done by adding a third objective function to the multi-objective optimization problem. This article uses density approach where each cell holds two local design parameters ranging from 0 to 1, where the combination of their extremums defines the presence of solid, cold fluid or hot fluid in this cell. Finite volume method is used for direct solver coupled with a discrete adjoint approach for sensitivity analysis and method of moving asymptotes for numerical optimization. Several examples are presented to show the ability of the method to find a trade-off between minimization of power dissipation and maximization of heat transfer while ensuring the separation and continuity of the channel of each fluid without crossing or mixing the fluids. The main conclusion is the possibility to find an optimal bi-fluid domain using topology optimization, defining a fluid to fluid heat exchanger device.

Keywords: topology optimization, density approach, bi-fluid domain, laminar steady state regime, fluid-to-fluid heat exchanger

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Authors: H. M. Alfrihidi, H.A. Albarakaty

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Flattening filter-free (FFF) photon beam radiotherapy has increased in the last decade, which is enabled by advancements in treatment planning systems and radiation delivery techniques like multi-leave collimators. FFF beams have higher dose rates, which reduces treatment time. On the other hand, FFF beams have a higher surface dose, which is due to the loss of beam hardening effect caused by the presence of the flatting filter (FF). The possibility of improving FFF beam quality using filters from low-z materials such as steel and aluminium (Al) was investigated using Monte Carlo (MC) simulations. The attenuation coefficient of low-z materials for low-energy photons is higher than that of high-energy photons, which leads to the hardening of the FFF beam and, consequently, a reduction in the surface dose. BEAMnrc user code, based on Electron Gamma Shower (EGSnrc) MC code, is used to simulate the beam of a 6 MV True-Beam linac. A phase-space (phosphor) file provided by Varian Medical Systems was used as a radiation source in the simulation. This phosphor file was scored just above the jaws at 27.88 cm from the target. The linac from the jaw downward was constructed, and radiation passing was simulated and scored at 100 cm from the target. To study the effect of low-z filters, steel and Al filters with a thickness of 1 cm were added below the jaws, and the phosphor file was scored at 100 cm from the target. For comparison, the FF beam was simulated using a similar setup. (BEAM Data Processor (BEAMdp) is used to analyse the energy spectrum in the phosphorus files. Then, the dose distribution resulting from these beams was simulated in a homogeneous water phantom using DOSXYZnrc. The dose profile was evaluated according to the surface dose, the lateral dose distribution, and the percentage depth dose (PDD). The energy spectra of the beams show that the FFF beam is softer than the FF beam. The energy peaks for the FFF and FF beams are 0.525 MeV and 1.52 MeV, respectively. The FFF beam's energy peak becomes 1.1 MeV using a steel filter, while the Al filter does not affect the peak position. Steel and Al's filters reduced the surface dose by 5% and 1.7%, respectively. The dose at a depth of 10 cm (D10) rises by around 2% and 0.5% due to using a steel and Al filter, respectively. On the other hand, steel and Al filters reduce the dose rate of the FFF beam by 34% and 14%, respectively. However, their effect on the dose rate is less than that of the tungsten FF, which reduces the dose rate by about 60%. In conclusion, filters from low-z material decrease the surface dose and increase the D10 dose, allowing for a high-dose delivery to deep tumors with a low skin dose. Although using these filters affects the dose rate, this effect is much lower than the effect of the FF.

Keywords: flattening filter free, monte carlo, radiotherapy, surface dose

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Wen Luo, Phil J. Vardon, Anne-Catherine Dieudonne

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One key process that partly controls the success of geothermal projects is fluid reinjection, which benefits in dealing with waste water, maintaining reservoir pressure, and supplying heat-exchange media, etc. Thus, sustaining the injectivity is of great importance for the efficiency and sustainability of geothermal production. However, the injectivity is sensitive to the reinjection process. Field experiences have illustrated that the injectivity can be damaged or improved. In this paper, the focus is on how the injectivity is improved. Since the injection pressure is far below the formation fracture pressure, hydraulic fracturing cannot be the mechanism contributing to the increase in injectivity. Instead, thermal stimulation has been identified as the main contributor to improving the injectivity. For low-enthalpy geothermal reservoirs, which are not fracture-controlled, thermal fracturing, instead of thermal shearing, is expected to be the mechanism for increasing injectivity. In this paper, field data from the sedimentary low-enthalpy geothermal reservoirs in the Netherlands were analysed to show the occurrence of thermal fracturing due to the cooling shock during reinjection. Injection data were collected and compared to show the effects of the thermal fractures on injectivity. Then, a thermo-hydro-mechanical (THM) model for the near field formation was developed and solved by finite element method to simulate the observed thermal fractures. It was then compared with the HM model, decomposed from the THM model, to illustrate the thermal effects on thermal fracturing. Finally, the effects of operational parameters, i.e. injection temperature and pressure, on the changes in injectivity were studied on the basis of the THM model. The field data analysis and simulation results illustrate that the thermal fracturing occurred during reinjection and contributed to the increase in injectivity. The injection temperature was identified as a key parameter that contributes to thermal fracturing.

Keywords: injectivity, reinjection, thermal fracturing, thermo-hydro-mechanical model

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Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

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To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

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Authors: Muhammad Muzamal, Anders Rasmuson

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Wood material is extensively considered as a raw material for the production of bio-polymers, bio-fuels and value-added chemicals. However, the shortcoming in using wood as raw material is that the enzymatic hydrolysis of wood material is difficult because the accessibility of enzymes to hemicelluloses and cellulose is hindered by complex chemical and physical structure of the wood. The steam explosion (SE) pre-treatment improves the digestion of wood material by creating both chemical and physical modifications in wood. In this process, first, wood chips are treated with steam at high pressure and temperature for a certain time in a steam treatment vessel. During this time, the chemical linkages between lignin and polysaccharides are cleaved and stiffness of material decreases. Then the steam discharge valve is rapidly opened and the steam and wood chips exit the vessel at very high speed. These fast moving wood chips collide with each other and with walls of the equipment and disintegrate to small pieces. More damaged and disintegrated wood have larger surface area and increased accessibility to hemicelluloses and cellulose. The energy required for an increase in specific surface area by same value is 70 % more in conventional mechanical technique, i.e. attrition mill as compared to steam explosion process. The mechanism of wood disintegration during the SE pre-treatment is very little studied. In this study, we have simulated collision and impact of wood chips (dimension 20 mm x 20 mm x 4 mm) with each other and with walls of the vessel. The wood chips are simulated as a 3D orthotropic material. Damage and fracture in the wood material have been modelled using 3D Hashin’s damage model. This has been accomplished by developing a user-defined subroutine and implementing it in the FE software ABAQUS. The elastic and strength properties used for simulation are of spruce wood at 12% and 30 % moisture content and at 20 and 160 OC because the impacted wood chips are pre-treated with steam at high temperature and pressure. We have simulated several cases to study the effects of elastic and strength properties of wood, velocity of moving chip and orientation of wood chip at the time of impact on the damage in the wood chips. The disintegration patterns captured by simulations are very similar to those observed in experimentally obtained steam exploded wood. Simulation results show that the wood chips moving with higher velocity disintegrate more. Moisture contents and temperature decreases elastic properties and increases damage. Impact and collision in specific directions cause easy disintegration. This model can be used to efficiently design the steam explosion equipment.

Keywords: dynamic simulation, disintegration of wood, impact, steam explosion pretreatment

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Authors: Vishnu A., Ashesh Saha

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The operation of high-speed rotating machinery in industries is accompanied by rotor vibrations due to many factors. One of the primary instability mechanisms in a rotor system is the centrifugal force induced due to the eccentricity of the center of mass away from the center of rotation. These unwanted vibrations may lead to catastrophic fatigue failure. So, there is a need to control these rotor vibrations. In this work, control of rotor vibrations by using a 4-pole Radial Active Magnetic Bearing (RAMB) as an actuator is analysed. A continuous rotor system model is considered for the analysis. Several important factors, like the gyroscopic effect and rotary inertia of the shaft and disc, are incorporated into this model. The large deflection of the shaft and the restriction to axial motion of the shaft at the bearings result in nonlinearities in the system governing equation. The rotor system is modeled in such a way that the system dynamics can be related to the geometric and material properties of the shaft and disc. The mathematical model of the rotor system is developed by incorporating the control forces generated by the RAMB. A simple PD controller is used for the attenuation of system vibrations. An analytical expression for the amplitude and phase equations is derived using the Method of Multiple Scales (MMS). Analytical results are verified with the numerical results obtained using an ‘ode’ solver in-built into MATLAB Software. The control force is found to be effective in attenuating the system vibrations. The multi-valued solutions leading to the jump phenomenon are also eliminated with a proper choice of control gains. Most interestingly, the shape of the backbone curves can also be altered for certain values of control parameters.

Keywords: rotor dynamics, continuous rotor system model, active magnetic bearing, PD controller, method of multiple scales, backbone curve

Procedia PDF Downloads 79

Authors: I. Valdez, J. Perdomo, M. Colindres, N. Castro

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Today, digital servo systems are extensively used in industrial manufacturing processes, robotic applications, vehicles and other areas. In such control systems, control action is provided by digital controllers with different compensation algorithms, which are designed to meet specific requirements for a given application. Due to the constant search for optimization in industrial processes, it is of interest to design digital controllers that offer ease of realization, improved computational efficiency, affordable return rates, and ease of tuning that ultimately improve the performance of the controlled actuators. There is a vast range of options of compensation algorithms that could be used, although in the industry, most controllers used are based on a PID structure. This research article compares different types of digital compensators implemented in a servo system for DC motor position control. PID compensation is evaluated on its two most common architectures: PID position form (1 DOF), and PID speed form (2 DOF). State feedback algorithms are also evaluated, testing two modern control theory techniques: discrete state observer for non-measurable variables tracking, and a linear quadratic method which allows a compromise between the theoretical optimal control and the realization that most closely matches it. The compared control systems’ performance is evaluated through simulations in the Simulink platform, in which it is attempted to model accurately each of the system’s hardware components. The criteria by which the control systems are compared are reference tracking and disturbance rejection. In this investigation, it is considered that the accurate tracking of the reference signal for a position control system is particularly important because of the frequency and the suddenness in which the control signal could change in position control applications, while disturbance rejection is considered essential because the torque applied to the motor shaft due to sudden load changes can be modeled as a disturbance that must be rejected, ensuring reference tracking. Results show that 2 DOF PID controllers exhibit high performance in terms of the benchmarks mentioned, as long as they are properly tuned. As for controllers based on state feedback, due to the nature and the advantage which state space provides for modelling MIMO, it is expected that such controllers evince ease of tuning for disturbance rejection, assuming that the designer of such controllers is experienced. An in-depth multi-dimensional analysis of preliminary research results indicate that state feedback control method is more satisfactory, but PID control method exhibits easier implementation in most control applications.

Keywords: control, DC motor, discrete PID, discrete state feedback

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Authors: Mohammadreza Khanmohammadi, Noureddin Nakhostin Ansari, Soofia Naghdi

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Purpose: Our study aimed to validate single item presenteeism question (SIPQ) into the Persian language for patients with low back pain. Background information: low back pain is a common health problem, and it is one of the most prevalent disorder in working people. There are the different subjective way to evaluate the effect of back pain on work productivity that one of them is by implementing single item presenteeism question. This question has not been validated into the Persian language. Method: Patients were asked to answer SIPQ and pain from 0 to 10 according to numerical rating scale (NRS). The functional rating index was administrated to evaluate construct validity. For test-retest reliability, almost 50 patients re-completed the Persian SIPQ. The construct validity of SIPQ was assessed by analyzing Spearman rank correlation between this question and the Persian version of Functional rating index questionnaire. To analyze test-retest reliability, we assessed intraclass correlation coefficient (agreement) (ICC agreement) (two-way random effects model, single measure). Results: The SIPQ score of two groups of patients (84 males, 16 females, mean age ±SD: 33.85±11.16 years, range: 19-67 years) and healthy subjects (48 male, 2 female ones, mean age ±SD: 24.24 ±8.07 years) was statistically significant. (Mann-Whitney U =198.00, P<.001). The Spearman correlation of data showed that there is a significant correlation between Persian SIPQ score and Persian FRI band (r= .559, P<.001). The ICC was .62. So, the analysis indicated good, test-retest reliability. Conclusion: This study showed that Persian version of SIPQ is reliable and valid when applied to back pain patients.

Keywords: cross cultural adaptation, economic burden, low back pain, Persian language, translation

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Authors: G. De Matteis, L. Martina, V. Turco

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The work is focused on determining and comparing special nonlinear static configurations in cholesteric liquid crystals (CLCs), confined between two parallel plates and in the presence of an external static electric/magnetic field. The solutions are stabilised by topological and non-topological conservation laws since they are described in terms of integrable or partially integrable nonlinear boundary value problems. In cholesteric liquid crystals which are subject to geometric frustration; anchoring conditions at boundaries, i.e., homeotropic conditions, are incompatible with the cholesteric twist. This aspect turns out to be essential in the admissible classes of solutions, allowing also for disclination type singularities. Within the framework of Frank-Oseen theory, we study the static configurations for CLCs. First, we find numerical solutions for isolated axisymmetric states in confined CLCs with weak homeotropic anchoring at the boundaries. These solutions describe 3-dimensional modulations, namely spherulites or cholesteric bubbles, actually observed in these systems, of standard baby skyrmions. Relations with well-known nonlinear integrable systems are found and are used to explore the asymptotic behavior of the solutions. Then we turn our attention to extended periodic static configurations called Helicoids or cholesteric fingers, described by an elliptic sine-Gordon model with appropriate boundary conditions, showing how their period and energies are determined by both the thickness of the cell and the intensity of the external electric/magnetic field. We explicitly show that helicoids with π or 2π of rotations of the molecular director are different in many aspects and are not simply algebraically related. The behaviour of the solutions, their energy and the properties of the associated disclinations are discussed in detail, both analytically and numerically.

Keywords: cholesteric liquid crystals, geometric frustration, helicoids, skyrmions

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Authors: Adel A. Ghoneim

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Air conditioning devices are substantially utilized in the summer months, as a result maximum loads in Kuwait take place in these intervals. Peak energy consumption are usually more expensive to satisfy compared to other standard power sources. The primary objective of the current work is to enhance the performance of high concentrated photovoltaic (HCPV) systems in an attempt to minimize peak power usage in Kuwait using HCPV modules. High concentrated PV multi-junction solar cells provide a promising method towards accomplishing lowest pricing per kilowatt-hour. Nevertheless, these cells have various features that should be resolved to be feasible for extensive power production. A single diode equivalent circuit model is formulated to analyze multi-junction solar cells efficiency in Kuwait weather circumstances taking into account the effects of both the temperature and the concentration ratio. The diode shunt resistance that is commonly ignored in the established models is considered in the present numerical model. The current model results are successfully validated versus measurements from published data to within 1.8% accuracy. Present calculations reveal that the single diode model considering the shunt resistance provides accurate and dependable results. The electrical efficiency (η) is observed to increase with concentration to a specific concentration level after which it reduces. Implementing grid systems is noticed to increase with concentration to a certain concentration degree after which it decreases. Employing grid connected HCPV systems results in significant peak load reduction.

Keywords: grid connected, high concentrated photovoltaic systems, peak load, solar cells

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Authors: Kumar Divyendra

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Underwater Sensor Networks (UWSNs) have wide applications in areas such as water quality monitoring, marine wildlife management etc. A typical UWSN system consists of a set of sensors deployed randomly underwater which communicate with each other using acoustic links. RF communication doesn't work underwater, and GPS too isn't available underwater. Additionally Automated Underwater Vehicles (AUVs) are deployed to collect data from some special nodes called Cluster Heads (CHs). These CHs aggregate data from their neighboring nodes and forward them to the AUVs using optical links when an AUV is in range. This helps reduce the number of hops covered by data packets and helps conserve energy. We consider the three-dimensional model of the UWSN. Nodes are initially deployed randomly underwater. They attach themselves to the surface using a rod and can only move upwards or downwards using a pump and bladder mechanism. We use graph theory concepts to maximize the coverage volume while every node maintaining connectivity with at least one surface node. We treat the surface nodes as landmarks and each node finds out its hop distance from every surface node. We treat these hop-distances as coordinates and use them for AUV navigation. An AUV intending to move closer to a node with given coordinates moves hop by hop through nodes that are closest to it in terms of these coordinates. In absence of GPS, multiple different approaches like Inertial Navigation System (INS), Doppler Velocity Log (DVL), computer vision-based navigation, etc., have been proposed. These systems have their own drawbacks. INS accumulates error with time, vision techniques require prior information about the environment. We propose a method that makes use of the earth's magnetic field values for navigation and combines it with other methods that simultaneously increase the coverage volume under the UWSN. The AUVs are fitted with magnetometers that measure the magnetic intensity (I), horizontal inclination (H), and Declination (D). The International Geomagnetic Reference Field (IGRF) is a mathematical model of the earth's magnetic field, which provides the field values for the geographical coordinateson earth. Researchers have developed an inverse deep learning model that takes the magnetic field values and predicts the location coordinates. We make use of this model within our work. We combine this with with the hop-by-hop movement described earlier so that the AUVs move in such a sequence that the deep learning predictor gets trained as quickly and precisely as possible We run simulations in MATLAB to prove the effectiveness of our model with respect to other methods described in the literature.

Keywords: clustering, deep learning, network backbone, parallel computing

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Authors: Muhammad Shahbaz Akhtar

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Background; Tuberculosis remains a significant public health challenge in Pakistan, with high incidence and prevalence rates, particularly among vulnerable populations. Addressing the TB burden requires comprehensive efforts to improve healthcare infrastructure, increase access to quality diagnosis and treatment services, raise public awareness, and address socioeconomic determinants of health. Objective; To assess the knowledge and practices of healthcare workers and patients regarding prevention of tuberculosis at a tertiary care hospital of Southern Punjab.Material and methods; Data will be collected from 135 healthcare workers and 135 TB patients visiting Nishtar Hospital, Multan in this descriptive cross – sectional study using non – probability consecutive sampling technique. Proper approval will be taken from Hospital authorities to conduct this study. Study participants will be recruited after taking informed written consent, describing them objectives of this study. The study participants will be ensured of their confidentiality of the data and interviewed to assess their knowledge and practices regarding prevention of tuberculosis. Data Analysis Procedure; Data will be entered and analyzed by using SPSS version 25 to calculated mean and standard deviation for the numerical data such as age, duration of disease and duration of experience. Frequencies and percentages will be calculated for gender, age groups, level of knowledge, qualification, designation and practices. Impact of confounders like gender, age groups, duration of experience, disease duration, years of experience and designation will be assessed by stratification. Post stratification chi – square test will be applied at 0.05 level of significance at 95 % CI.

Keywords: tuberculosis, data analysis, HIV/AIDS, preventable

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Authors: Mohamed Farhat O. Hameed, Yasamin K. A. Alrayk, A. A Shaalan, S. S. A. Obayya

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The surface plasmon resonance (SPR) sensors are widely used due to its high sensitivity with molecular labels free. The commercial SPR sensors depend on the conventional prism-coupled configuration. However, this type of configuration suffers from miniaturization and integration. Therefore, the search for compact, portable and highly sensitive SPR sensors becomes mandatory.In this paper, sensitivity enhancement of a novel photonic crystal fiber biosensoris introduced and studied. The suggested design has microstructure of air holes in the core region surrounded by two large semicircular metallized channels filled with the analyte. The inner surfaces of the two channels are coated by a silver layer followed by a gold layer.The simulation results are obtained using full vectorial finite element methodwith perfect matched layer (PML) boundary conditions. The proposed design depends on bimetallic configuration to enhance the biosensor sensitivity. Additionally, the suggested biosensor can be used for multi-channel/multi-analyte sensing. In this study, the sensor geometrical parameters are studied to maximize the sensitivity for the two polarized modes. The numerical results show that high refractive index sensitivity of 4750 nm/RIU (refractive index unit) and 4300 nm/RIU can be achieved for the quasi (transverse magnetic) TM and quasi (transverse electric) TE modes of the proposed biosensor, respectively. The reportedbiosensor has advantages of integration of microfluidics setup, waveguide and metallic layers into a single structure. As a result, compact biosensor with better integration compared to conventional optical fiber SPR biosensors can be obtained.

Keywords: photonic crystal fibers, gold, silver, surface plasmon, biosensor

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Authors: Tarek M. Alguhane, Ayman H. Khalil, M. N. Fayed, Ayman M. Ismail

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This paper deals with different modeling aspects of masonry infill: no infill model, Layered shell infill model, and strut infill model. These models consider the complicated behavior of the in-filled plane frames under lateral load similar to an earthquake load. Three strut infill models are used: NBCC (2005) strut infill model, ASCE/SEI 41-06 strut infill model and proposed strut infill model based on modification to Canadian, NBCC (2005) strut infill model. Pushover and modal analyses of a masonry infill concrete frame with a single storey and an existing 5-storey RC building have been carried out by using different models for masonry infill. The corresponding hinge status, the value of base shear at target displacement as well as their dynamic characteristics have been determined and compared. A validation of the structural numerical models for the existing 5-storey RC building has been achieved by comparing the experimentally measured and the analytically estimated natural frequencies and their mode shapes. This study shows that ASCE/SEI 41-06 equation underestimates the values for the equivalent properties of the diagonal strut while Canadian, NBCC (2005) equation gives realistic values for the equivalent properties. The results indicate that both ASCE/SEI 41-06 and Canadian, NBCC (2005) equations for strut infill model give over estimated values for dynamic characteristic of the building. Proposed modification to Canadian, NBCC (2005) equation shows that the fundamental dynamic characteristic values of the building are nearly similar to the corresponding values using layered shell elements as well as measured field results.

Keywords: masonry infill, framed structures, RC buildings, non-structural elements

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Authors: Siobhan Laird

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Under article 12 of the Convention on the Rights of the Child, which extends human rights in their application to those under the age of 18 years, children must be consulted ‘in all matters affecting the child’. The Office of the Children’s Commissioner for England is responsible for improving the welfare of children and young people by ensuring that their Convention rights are respected and realised and their views taken seriously. In 2014 the Children’s Commissioner engaged a team of researchers at the Centre for Social Work, University of Nottingham to develop and roll out an online survey to gather information from children and young people about their exercise of choice within the public care system. Approximately 3,000 children responded to this survey, which comprised both closed and open-ended questions. SPSS was used to analyse the numerical data and a thematic analysis of textual data was conducted on answers to open-ended questions. Findings revealed that children exercised considerable choice over personal space and their spare time, but had much less choice in relation to contact with their birth families, where they lived, or the timings of moves from one placement into another. The majority of children described how they were supported to express their opinions and believed that these were taken seriously. However, a significant number reported problems and explained how specific behaviours by professionals and carers made it difficult for them to express their opinion or to feel that they had influenced decisions which affected them. In open-ended questions eliciting information about their experiences, children and young people were asked to describe how they could be better supported to make choices and what changes would assist for these to be better acknowledged and acted upon by professionals and carers. This paper concludes by presenting the ideas and suggestions of children and young people for improving the public care system in Britain in relation to their exercise of choice.

Keywords: children, choice, participation, public care

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Authors: Tiziana Biasutti, Daniela Rigamonti, Lorenzo Palmiotti, Adelaide Nespoli, Paolo Bettini

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Aerospace industry is based on the continuous development of new technologies and solutions that allows constant improvement of the systems. Shape Memory Alloys are smart materials that can be used as dampers due to their pseudoelastic effect. The purpose of the research was to design a passive damper in Nitinol, manufactured by Selective Laser Melting, for space applications to reduce vibration between different structural parts in space structures. The powder is NiTi (50.2 at.% of Ni). The structure manufactured by additive technology allows us to eliminate the presence of joint and moving parts and to have a compact solution with high structural strength. The designed dampers had single or double cell structures with three different internal angles (30°, 45° and 60°). This particular shape has damping properties also without the pseudoelastic effect. For this reason, the geometries were reproduced in different materials, SS316L and Ti6Al4V, to test the geometry loss factor. The mechanical performances of these specimens were compared to the ones of NiTi structures, pointing out good damping properties of the designed structure and the highest performances of the NiTi pseudoelastic effect. The NiTi damper was mechanically characterized by static and dynamic tests and with DSC and microscope observations. The experimental results were verified with numerical models and with some scaled steel specimens in which optical fibers were embedded. The realized structure presented good mechanical and damping properties. It was observed that the loss factor and the dissipated energy increased with the angles of the cells.

Keywords: additive manufacturing, damper, nitinol, pseudo elastic effect, selective laser melting, shape memory alloys

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Authors: Anders Schou Simonsen, Kim Sorensen, Thomas Condra

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Wet scrubbers are used for flue gas desulfurization by injecting water directly into the flue gas stream from a set of sprayers. The water droplets will flow freely inside the scrubber, and flow down along the scrubber walls as a thin wall film while reacting with the gas phase to remove SO₂. This complex multiphase phenomenon can be divided into three main contributions: the continuous gas phase, the liquid droplet phase, and the liquid wall film phase. This study proposes a complete model, where all three main contributions are taken into account and resolved using OpenFOAM for the continuous gas phase, and MATLAB for the liquid droplet and wall film phases. The 3D continuous gas phase is composed of five species: CO₂, H₂O, O₂, SO₂, and N₂, which are resolved along with momentum, energy, and turbulence. Source terms are present for four species, energy and momentum, which are affecting the steady-state solution. The liquid droplet phase experiences breakup, collisions, dynamics, internal chemistry, evaporation and condensation, species mass transfer, energy transfer and wall film interactions. Numerous sub-models have been implemented and coupled to realise the above-mentioned phenomena. The liquid wall film experiences impingement, acceleration, atomization, separation, internal chemistry, evaporation and condensation, species mass transfer, and energy transfer, which have all been resolved using numerous sub-models as well. The continuous gas phase has been coupled with the liquid phases using source terms by an approach, where the two software packages are couples using a link-structure. The complete CFD model has been verified using 16 experimental tests from an existing scrubber installation, where a gradient-based pattern search optimization algorithm has been used to tune numerous model parameters to match the experimental results. The CFD model needed to be fast for evaluation in order to apply this optimization routine, where approximately 1000 simulations were needed. The results show that the complex multiphase phenomena governing wet scrubbers can be resolved in a single model. The optimization routine was able to tune the model to accurately predict the performance of an existing installation. Furthermore, the study shows that a coupling between OpenFOAM and MATLAB is realizable, where the data and source term exchange increases the computational requirements by approximately 5%. This allows for exploiting the benefits of both software programs.

Keywords: desulfurization, discrete phase, scrubber, wall film

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Authors: Gagan Kumar, Koijam M. Devi, Amarendra K. Sarma, Dibakar Roy Chowdhury

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Research in metamaterials has been gaining momentum over the past decade owing to its ability in controlling electromagnetic wave properties through careful design at the sub-wavelength scale. The metamaterials have led to several important phenomena which are useful in a variety of applications. One such phenomenon is the electromagnetically induced transparency (EIT) effect in which a narrow transparency region is created in an otherwise absorptive spectrum. In our work, we explore plasmon induced transparency (PIT) in terahertz metamaterials which is analogues to EIT effect. The PIT effect is achieved using the plasmonic metamaterials in which a unit cell is comprised of two C (2C) shaped resonators and a cut-wire (CW). When terahertz wave of a particular polarization is normally incident on the proposed metamaterials geometry, it strongly couples with the cut wire, resulting in the excitation of the bright mode. However due to the specific polarization of the incident beam, the fundamental modes of the C-shaped resonators are not excited by the incident terahertz, hence they are termed as the dark mode. The PIT effect occurs as a result of interference between the bright and the dark mode. In order to observe PIT effect, both the bright and dark modes should have similar resonant frequencies with a little deviation. We further have examined that the PIT window can be modulated by displacing the C-shaped resonators w.r.t. the cut-wire. The numerical observations for different coupling configurations can be explained through an equivalent lumped element circuit model. Moving ahead the PIT effect is further explored in a metamaterial comprising of a cross like structure and four C-shaped resonators. For such configuration, equally strong PIT effect is observed for two orthogonally polarized lights. Therefore, such metamaterials demonstrate a polarization independent PIT response w.r.t the incident terahertz radiation. The proposed study could be significant in the development of slow light devices and polarization independent sensing applications.

Keywords: terahertz, metamaterial, split ring resonator, plasmon

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Authors: Wahab Abdul Ghafar, Tao Zhong, Baba Kalan Enamullah

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Steel plate shear walls (SPSWs) are a robust lateral load resistance structure because of their high flexibility and efficient energy dissipation when subjected to seismic loads. This research investigates the seismic Performance of an innovative infill web strip (IWS-SPSW) and a typical unstiffened steel plate shear wall (USPSW). As a result, two 1:3 scale specimens of an IWS-SPSW and USPSW with a single story and a single bay were built and subjected to a cyclic lateral loading methodology. In the prototype, the beam-to-column connections were accomplished with the assistance of semi-rigid end-plate connectors. IWS-SPSW demonstrated exceptional ductility and shear load-bearing capacity during the testing process, with no cracks or other damage occurring. In addition, the IWS-SPSW could effectively dissipate energy without causing a significant amount of beam-column connection distortion. The shear load-bearing capacity of the USPSW was exceptional. However, it exhibited low ductility, severe infill plate corner ripping, and huge infill web plate cracks. The FE models were created and then confirmed using the experimental data. It has been demonstrated that the infill web strips of an SPSW system can affect the system's high Performance and total energy dissipation. In addition, a parametric analysis was carried out to evaluate the material qualities of the IWS, which can considerably improve the system's seismic performances. These properties include the steel's strength as well as its thickness.

Keywords: steel shear walls, seismic performance, failure mode, hysteresis response, nonlinear finite element analysis, parametric study.

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