Search results for: phase plots

Authors: Homayon Ahmad Panahi, Niusha Mohseni Darabi, Elham Moniri

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A new biosorbent is prepared by coupling a cibacron blue to yeast cells. The modified yeast cells with cibacron blue has been characterized by Fourier transform infrared spectroscopy (FT-IR) and elemental analysis and applied for the preconcentration and solid phase extraction of trace cadmium ion from water samples. The optimum pH value for sorption of the cadmium ions by yeast cells- cibacron blue was 5.5. The sorption capacity of modified biosorbent was 45 mg. g−1. A recovery of 98.2% was obtained for Cd(II) when eluted with 0.5 M nitric acid. The method was applied for Cd(II) preconcentration and determination in sea water sample.

Keywords: solid phase extraction, yeast cells, Nickl, isotherm study

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Authors: Ararat Khachatryan, Davit Mirzoyan

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In sub micrometer technology, the aging phenomenon starts to have a significant impact on the reliability of integrated circuits by bringing performance degradation. For that reason, it is important to have a capability to evaluate the aging effects accurately. This paper presents an accurate aging measurement approach based on phase-locked loop (PLL) and voltage-controlled oscillator (VCO) circuit. The architecture is rejecting the circuit self-aging effect from the characteristics of PLL, which is generating the frequency without any aging phenomena affects. The aging monitor is implemented in low power 32 nm CMOS technology, and occupies a pretty small area. Aging simulation results show that the proposed aging measurement circuit improves accuracy by about 2.8% at high temperature and 19.6% at high voltage.

Keywords: aging effect, HCI, NBTI, nanoscale

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Authors: Saeid Seddegh, Xiaolin Wang, Alan D. Henderson, Dong Chen, Oliver Oims

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The main objective of this research is to study the heat transfer processes and phase change behaviour of a phase change material (PCM) in shell and tube latent heat thermal energy storage (LHTES) systems. The thermal behaviour in a vertical and horizontal shell-and-tube heat energy storage system using a pure thermal conduction model and a combined conduction-convection heat transfer model is compared in this paper. The model is first validated using published experimental data available in literature and then used to study the temperature variation, solid-liquid interface, phase distribution, total melting and solidification time during melting and solidification processes of PCMs. The simulated results show that the combined convection and conduction model can better describe the energy transfer in PCMs during melting process. In contrast, heat transfer by conduction is more significant during the solidification process since the two models show little difference. Also, it was concluded that during the charging process for the horizontal orientation, convective heat transfer has a strong effect on melting of the upper part of the solid PCM and is less significant during melting of the lower half of the solid PCM. However, in the vertical orientation, convective heat transfer is the same active during the entire charging process. In the solidification process, the thermal behavior does not show any difference between horizontal and vertical systems.

Keywords: latent heat thermal energy storage, phase change material, natural convection, melting, shell and tube heat exchanger, melting, solidification

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Authors: Shayla He

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Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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Authors: Hassan Alsada

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Tank overfill accidents are major concerns for industries handling large volumes of hydrocarbons. Buncefield, Jaipur, Puerto Rico, and West Virginia are just a few accidents with catastrophic consequences. Thus, it is very important for any industry to take the right safety measures for overfill prevention. Moreover, one of the main causative factors in the overfill accidents was inadequate risk analysis and, subsequently, inadequate design. This study aims to provide a full assessment in accordance with the Functional safety standard: “IEC 615 11 – Safety instrumented systems for the process industry” to the tank overfill scenario according to the standard’s Safety Life Cycle (SLC), which includes: the analysis phase, the implementation phase, and the operation phase. The paper discusses in depth the tank overfills Independent Protection Layers (IPLs) with systematic analysis to avoid the safety risks of under-design and the financial risk of facility overdesign. The result shows a clear and systematic assessment in compliance with the standards that can help to assist existing tank overfilling setup or a guide to support designing new storage facilities overfill protection.

Keywords: IEC 61511, PHA, LOPA, process safety, safety, health, environment, safety instrumented systems, safety instrumented function, functional safety, safety life cycle

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Authors: Ilqar Ramazanli

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The matrix completion problem has been studied broadly under many underlying conditions. The problem has been explored under adaptive or non-adaptive, exact or estimation, single-phase or multi-phase, and many other categories. In most of these cases, the observation cost of each entry is uniform and has the same cost across the columns. However, in many real-life scenarios, we could expect elements from distinct columns or distinct positions to have a different cost. In this paper, we explore this generalization under adaptive conditions. We approach the problem under two different cost models. The first one is that entries from different columns have different observation costs, but within the same column, each entry has a uniform cost. The second one is any two entry has different observation cost, despite being the same or different columns. We provide complexity analysis of our algorithms and provide tightness guarantees.

Keywords: matroid optimization, matrix completion, linear algebra, algorithms

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Authors: Nikhil Kumar, Aparna Singh

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Microstructural development when annealed at different temperatures in a high aluminum and manganese light weight steel has been examined. The FCC matrix of the manganese (Mn)-rich and nickel (Ni)-rich areas in the studied Fe-Mn-Al-Ni-C-light weight steel have been found to contain anti phase domains. In the Mn-rich region short order range of domains manifested by the diffuse scattering in the electron diffraction patterns was observed. Domains in the Ni-rich region were found to be arranged periodically validated through lattice imaging. The nature of these domains can be tuned with annealing temperature resulting in profound influence in the mechanical properties.

Keywords: Anti-phase domain boundaries, BCC, FCC, Light Weight Steel

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Authors: Jaehyug Lee, Tae-Ho Song

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Vacuum insulation panel (VIP) can achieve very low thermal conductivity by evacuating its inner space. Heat transfer in the core materials of highly-evacuated VIP occurs by conduction through the solid structure and radiation through the pore. The effect of various scattering modes in combined conduction-radiation in VIP is investigated through numerical analysis. The discrete ordinates interpolation method (DOIM) incorporated with the commercial code FLUENT® is employed. It is found that backward scattering is more effective in reducing the total heat transfer while isotropic scattering is almost identical with pure absorbing/emitting case of the same optical thickness. For a purely scattering medium, the results agree well with additive solution with diffusion approximation, while a modified term is added in the effect of optical thickness to backward scattering is employed. For other scattering phase functions, it is also confirmed that backwardly scattering phase function gives a lower effective thermal conductivity. Thus, the materials with backward scattering properties, with radiation shields are desirable to lower the thermal conductivity of VIPs.

Keywords: combined conduction and radiation, discrete ordinates interpolation method, scattering phase function, vacuum insulation panel

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Authors: Y. K. Leong, J. C. W. Lan, H. S. Loh, P. L. Show

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Being biodegradable, non-toxic, renewable and have similar or better properties as commercial plastics, polyhydroxy alkanoates (PHAs) can be a potential game changer in the polymer industry. PHAs are the biodegradable polymer produced by bacteria, which are in interest as a sustainable alternative to petrochemical-derived plastics; however, its commercial value has significantly limited by high production and recovery cost of PHA. Aqueous two-phase system (ATPS) offers different chemical and physical environments, which contains about 80-90% water delivers an excellent environment for partitioning of cells, cell organelles and biologically active substances. Extractive bioconversion via ATPS allows the integration of PHA upstream fermentation and downstream purification process, which reduces production steps and time, thus lead to cost reduction. The ability of Ralstonia eutropha to grow under different ATPS conditions was investigated for its potential to be used in a bioconversion system. Changes in tie-line length (TLL) and a volume ratio (Vr) were shown to have an effect on PHA partition coefficient. High PHA recovery yield of 65% with a relatively high purity of 73% was obtained in PEG 6000/Sodium sulphate system with 42.6 wt/wt % TLL and 1.25 Vr. Extractive bioconversion via ATPS is an attractive approach for the combination of PHA production and recovery process.

Keywords: aqueous two-phase system, extractive bioconversion, polyhydroxy alkanoates, purification

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Authors: Ming-Kwei Lee, Chih-Feng Yen

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The electrical characteristics of liquid phase deposited silicon oxynitride film on ammonium sulfide treated p-type (100) gallium arsenide substrate were investigated. Hydrofluosilicic acid, ammonia and boric acid aqueous solutions were used as precursors. The electrical characteristics of silicon oxynitride film are much improved on gallium arsenide substrate with ammonium sulfide treatment. With post-metallization annealing, hydrogen ions can further passivate defects in SiON/GaAs film and interface. The leakage currents can reach 7.1 × 10-8 and 1.8 × 10-7 at ± 2 V. The dielectric constant and effective oxide charges are 5.6 and -5.3 × 1010 C/cm2, respectively. The hysteresis offset of hysteresis loop is merely 0.09 V.

Keywords: liquid phase deposition, SiON, GaAs, PMA, (NH4)2S

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Authors: M. Khalid, G. N. Singh

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In this paper, we have considered the problem of estimation for population mean, on current (second) occasion in the presence of random non response in two-occasion successive sampling under two phase set-up. Modified exponential type estimators have been proposed, and their properties are studied under the assumptions that numbers of sampling units follow a distribution due to random non response situations. The performances of the proposed estimators are compared with linear combinations of two estimators, (a) sample mean estimator for fresh sample and (b) ratio estimator for matched sample under the complete response situations. Results are demonstrated through empirical studies which present the effectiveness of the proposed estimators. Suitable recommendations have been made to the survey practitioners.

Keywords: successive sampling, random non-response, auxiliary variable, bias, mean square error

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Authors: Avoseh Funmilola, Osman Khalid, Wayne Nelson, Paramespri Naidoo, Deresh Ramjugernath

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The increasing global atmospheric temperature is of great concern and this has led to the development of technologies to reduce the emission of greenhouse gases into the atmosphere. Flue gas emissions from fossil fuel combustion are major sources of greenhouse gases. One of the ways to reduce the emission of CO₂ from flue gases is by post combustion capture process and this can be done by absorbing the gas into suitable chemical solvents before emitting the gas into the atmosphere. Alkanolamines are promising solvents for this capture process. Vapour liquid equilibrium of CO₂-alkanolamine systems is often represented by CO₂ loading and partial pressure of CO₂ without considering the liquid phase. The liquid phase of this system is a complex one comprising of 9 species. Online analysis of the process is important to monitor the concentrations of the liquid phase reacting and product species. Liquid phase analysis of CO₂-diethanolamine (DEA) solution was performed by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy. A robust Calibration was performed for the CO₂-aqueous DEA system prior to an online monitoring experiment. The partial least square regression method was used for the analysis of the calibration spectra obtained. The models obtained were used for prediction of DEA and CO₂ concentrations in the online monitoring experiment. The experiment was performed with a newly built recirculating experimental set up in the laboratory. The set up consist of a 750 ml equilibrium cell and ATR-FTIR liquid flow cell. Measurements were performed at 400°C. The results obtained indicated that the FTIR spectroscopy combined with Partial least square method is an effective tool for online monitoring of speciation.

Keywords: ATR-FTIR, CO₂ capture, online analysis, PLS regression

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Authors: Christin Koch, Andreas Winkel, Martin Kahlmeyer, Stefan Böhm

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Due to environmental regulations on greenhouse gas emissions and the depletion of fossil fuels, there is an increasing interest in electric vehicles.To maximize their driving range, batteries with high storage capacities are needed. In most electric cars, rechargeable lithium-ion batteries are used because of their high energy density. However, it has to be taken into account that these batteries generate a large amount of heat during the charge and discharge processes. This leads to a decrease in a lifetime and damage to the battery cells when the temperature exceeds the defined operating range. To ensure an efficient performance of the battery cells, reliable thermal management is required. Currently, the cooling is achieved by heat sinks (e.g., cooling plates) bonded to the battery cells with a thermally conductive adhesive (TCA) that directs the heat away from the components. Especially when large amounts of heat have to be dissipated spontaneously due to peak loads, the principle of heat conduction is not sufficient, so attention must be paid to the mechanism of heat storage. An efficient method to store thermal energy is the use of phase change materials (PCM). Through an isothermal phase change, PCM can briefly absorb or release thermal energy at a constant temperature. If the phase change takes place in the transition from solid to liquid, heat is stored during melting and is released to the ambient during the freezing process upon cooling. The presented work displays the great potential of thermally conductive adhesives filled with microencapsulated PCM to limit peak temperatures in battery systems. The encapsulation of the PCM avoids the effects of aging (e.g., migration) and chemical reactions between the PCM and the adhesive matrix components. In this study, microencapsulation has been carried out by in situ polymerization. The microencapsulated PCM was characterized by FT-IR spectroscopy, and the thermal properties were measured by DSC and laser flash method. The mechanical properties, electrical and thermal conductivity, and adhesive toughness of the TCA/PCM composite were also investigated.

Keywords: phase change material, microencapsulation, adhesive bonding, thermal management

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Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique for the incompressible two-phase flow simulations. This technique is known as observable method due to the understanding of observability that any feature smaller than the actual resolution (physical or numerical), i.e., the size of wire in hotwire anemometry or the grid size in numerical simulations, is not able to be captured or observed. Differ from most regularization techniques that applies on the numerical discretization, the observable method is employed at PDE level during the derivation of equations. Difficulties in the simulation and analysis of realistic fluid flow often result from discontinuities (or near-discontinuities) in the calculated fluid properties or state. Accurately capturing these discontinuities is especially crucial when simulating flows involving shocks, turbulence or sharp interfaces. Over the past several years, the properties of this new regularization technique have been investigated that show the capability of simultaneously regularizing shocks and turbulence. The observable method has been performed on the direct numerical simulations of shocks and turbulence where the discontinuities are successfully regularized and flow features are well captured. In the current paper, the observable method will be extended to two-phase interfacial flows. Multiphase flows share the similar features with shocks and turbulence that is the nonlinear irregularity caused by the nonlinear terms in the governing equations, namely, Euler equations. In the direct numerical simulation of two-phase flows, the interfaces are usually treated as the smooth transition of the properties from one fluid phase to the other. However, in high Reynolds number or low viscosity flows, the nonlinear terms will generate smaller scales which will sharpen the interface, causing discontinuities. Many numerical methods for two-phase flows fail at high Reynolds number case while some others depend on the numerical diffusion from spatial discretization. The observable method regularizes this nonlinear mechanism by filtering the convective terms and this process is inviscid. The filtering effect is controlled by an observable scale which is usually about a grid length. Single rising bubble and Rayleigh-Taylor instability are studied, in particular, to examine the performance of the observable method. A pseudo-spectral method is used for spatial discretization which will not introduce numerical diffusion, and a Total Variation Diminishing (TVD) Runge Kutta method is applied for time integration. The observable incompressible Euler equations are solved for these two problems. In rising bubble problem, the terminal velocity and shape of the bubble are particularly examined and compared with experiments and other numerical results. In the Rayleigh-Taylor instability, the shape of the interface are studied for different observable scale and the spike and bubble velocities, as well as positions (under a proper observable scale), are compared with other simulation results. The results indicate that this regularization technique can potentially regularize the sharp interface in the two-phase flow simulations

Keywords: Euler equations, incompressible flow simulation, inviscid regularization technique, two-phase flow

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Authors: Hyery Kang, Dong-Yeun Koh, Yun-Ho Ahn, Huen Lee

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Determination of the behavior of clathrate hydrate with inhibitor in the THz region will provide useful information about hydrate plug control in the upstream of the oil and gas industry. In this study, terahertz time-domain spectroscopy (THz-TDS) revealed the inhibition of the THF clathrate hydrate system with dosage of polyvinylpyrrolidone (PVP) with three different molecular weights. Distinct footprints of phase transition in the THz region (0.4–2.2 THz) were analyzed and absorption coefficients and real part of refractive indices are obtained in the temperature range of 253 K to 288 K. Along with the optical properties, ring breathing and stretching modes for different molecular weights of PVP in THF hydrate are analyzed by Raman spectroscopy.

Keywords: clathrate hydrate, terahertz spectroscopy, tetrahydrofuran, inhibitor

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Authors: R. Dubey, M. Sarwan, S. Singh

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We have investigated the phase transition pressure and associated volume collapse in Sm1– X EuX S alloy (0≤x≤1) which shows transition from discontinuous to continuous as x is reduced. The calculated results from present approach are in good agreement with experimental data available for the end point members (x=0 and x=1). The results for the alloy counter parts are also in fair agreement with experimental data generated from the vegard’s law. An improved interaction potential model has been developed which includes coulomb, three body interaction, polarizability effect and overlap repulsive interaction operative up to second neighbor ions. It is found that the inclusion of polarizability effect has improved our results.

Keywords: elastic constants, high pressure, phase transition, rare earth compound

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Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Morteza Hadi

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This research investigates the potential enhancement of the rollability of Cu-Ge-Ni alloy through the mitigation of microstructural and compositional inhomogeneities via two distinct heat treatment methods: homogenization and solution treatment. To achieve this objective, the alloy with the desired composition was fabricated using a vacuum arc remelting furnace (VAR), followed by sample preparation for microstructural, compositional, and heat treatment analyses at varying temperatures and durations. Characterization was conducted employing optical and scanning electron microscopy (SEM), X-ray diffraction (XRD), and Vickers hardness testing. The results obtained indicate that a minimum duration of 10 hours is necessary for adequate homogenization of the alloy at 750°C. This heat treatment effectively removes coarse dendrites from the casting microstructure and significantly reduces elemental separations. However, despite these improvements, the presence of a second phase with markedly different hardness from the matrix results in poor rolling ability for the alloy. The optimal time for solution treatment at various temperatures was determined, with the most effective cycle identified as 750°C for 2 hours, followed by rapid quenching in water. This process induces the formation of a single-phase microstructure and complete elimination of the second  phase, as confirmed by X-ray diffraction analysis. Results demonstrate a reduction in hardness by 30 Vickers, and the elimination of microstructural unevenness enables successful thickness reduction by up to 50% through rolling without encountering cracking.

Keywords: Cu-Ge-Ni alloy, homogenization. solution treatment, rollability

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Authors: Jonas Kristiansen Nøland, Karina Hjelmervik, Urban Lundin

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The thyristor bridge rectifier is often used for control of excitation equipment for synchronous generators. However, on the rotating shaft of brushless exciters, the diode bridge rectifier is mostly used. The step response of a conventional brushless rotating excitation system is slow compared to static excitation systems. This paper investigates the performance of different thyristor-controlled rectification topologies applied on the shaft of a 6-phase PMG exciter connected to a synchronous generator. One of the important issues is the steady-state torque ripple produced by the thyristor bridges.

Keywords: brushless exciters, rotating exciters, permanent magnet machines, synchronous generators

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Authors: Juan Xia, Jiaxu Yan, Ze Xiang Shen

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The tuneable interlayer interactions in two-dimensional (2D) transition metal dichlcogenides (TMDs) offer an exciting platform for exploring new physics and applications by material variety, thickness, stacking sequence, electromagnetic filed, and stress/strain. Compared with the five methods mentioned above, high pressure is a clean and powerful tool to induce dramatic changes in lattice parameters and physical properties for 2D TMD materials. For instance, high pressure can strengthen the van der Waals interactions along c-axis and shorten the covalent bonds in atomic plane, leading to the typical first-order structural transition (2Hc to 2Ha for MoS2), or metallization. In particular, in the case of WTe₂, its unique symmetry endows the significant anisotropy and the corresponding unexpected properties including the giant magnetoresistance, pressure-induced superconductivity and Weyl semimetal states. Upon increasing pressure, the Raman peaks for WTe₂ at ~120 cm⁻¹, are gradually red-shifted and totally suppressed above 10 GPa, attributed to the possible structural instability of orthorhombic Td phase under high pressure and phase transition to a new monoclinic T' phase with inversion symmetry. Distinct electronic structures near Fermi level between the Td and T' phases may pave a feasible way to achieve the Weyl state tuning in one material without doping.

Keywords: 2D TMDs, electronic property, high pressure, first-principles calculations

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Authors: Yi Zheng

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Improving formability and mechanical properties have always been one of the challenges in the field of additive manufacturing (AM) of nickel-based superalloys. In this work, the effect of a coaxially coupled alternating magnetic field (AMF) on surface morphology and mechanical properties of plasma arc-based additive manufactured Inconel 718 deposit were investigated. Results show that the Lorentz force induced by AMF strongly alters the flow behavior of the plasma jet and the molten pool, suppressing the tendency of the liquid metal in the molten pool to flow down on the two sides face of the deposit, which in turn remarkably improved the surface accuracy of the thin-walled deposit. Furthermore, the electromagnetic stirring induced by AMF can effectively enhance the convection between the dendrites, which could not only contribute to the formation of finer dendrites but also alleviate the enrichment of the elements (i.e., Nb and Mo) at the solid-liquid interface and inhibits the precipitation of Laves phase. The smallest primary dendritic arm spacing (~13 μm) and lowest Laves phases area fraction (3.12%) were witnessed in the bottom region of the AMF-assisted deposit. The mechanical test confirmed that the deposit's micro-hardness and tensile properties were moderately improved compared with the counterpart without AMF.

Keywords: additive manufacturing, inconel 718, alternating magnetic field, laves phase

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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: Ria Forner

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Introduction: Due to increases in the SNR at 7T and above, it becomes more favourable to make use of X-nuclear imaging. Integrated body coils tuned to 120MHz for 31P, 79MHz for 23Na, and 75 MHz for 13C at 7T were simulated with a human male, female, or child body model to assess strategies of use for metabolic MR imaging in the body. Methods: B1 and SAR efficiencies in the heart, liver, spleen, and kidneys were assessed using numerical simulations over the three frequencies with phase shimming. Results: B1+ efficiency is highly variable over the different organs, particularly for the highest frequency; however, local SAR efficiency remains relatively constant over the frequencies in all subjects. Although the optimal phase settings vary, one generic phase setting can be identified for each frequency at which the penalty in B1+ is at a max of 10%. Discussion: The simulations provide practical strategies for power optimization, B1 management, and maintaining safety. As expected, the B1 field is similar at 75MHz and 79MHz, but reduced at 120MHz. However, the B1 remains relatively constant when normalised by the square root of the peak local SAR. This is in contradiction to generalized SAR considerations of 1H MRI at different field strengths, which is defined by global SAR instead. Conclusion: Although the B1 decreases with frequency, SAR efficiency remains constant throughout the investigated frequency range. It is possible to shim the body coil to obtain a maximum of 10% extra B1+ in a specific organ in a body when compared to a generic setting.

Keywords: birdcage, multi-nuclear, B1 shimming, 7 Tesla MRI, liver, kidneys, heart, spleen

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Authors: Chen Wang, Jared Evans, Yan Asmann

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With the quick evolvement of next-generation sequencing techniques, whole-exome or exome-panel data have become a cost-effective way for detection of small exonic mutations, but there has been a growing desire to accurately detect copy number variations (CNVs) as well. In order to address this research and clinical needs, we developed a sequencing coverage pattern-based method not only for copy number detections, data integrity checks, CNV calling, and visualization reports. The developed methodologies include complete automation to increase usability, genome content-coverage bias correction, CNV segmentation, data quality reports, and publication quality images. Automatic identification and removal of poor quality outlier samples were made automatically. Multiple experimental batches were routinely detected and further reduced for a clean subset of samples before analysis. Algorithm improvements were also made to improve somatic CNV detection as well as germline CNV detection in trio family. Additionally, a set of utilities was included to facilitate users for producing CNV plots in focused genes of interest. We demonstrate the somatic CNV enhancements by accurately detecting CNVs in whole exome-wide data from the cancer genome atlas cancer samples and a lymphoma case study with paired tumor and normal samples. We also showed our efficient reuses of existing exome sequencing data, for improved germline CNV calling in a family of the trio from the phase-III study of 1000 Genome to detect CNVs with various modes of inheritance. The performance of the developed method is evaluated by comparing CNV calling results with results from other orthogonal copy number platforms. Through our case studies, reuses of exome sequencing data for calling CNVs have several noticeable functionalities, including a better quality control for exome sequencing data, improved joint analysis with single nucleotide variant calls, and novel genomic discovery of under-utilized existing whole exome and custom exome panel data.

Keywords: bioinformatics, computational genetics, copy number variations, data reuse, exome sequencing, next generation sequencing

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Authors: Raza Abdulla Saeed

Abstract:

In this study, the three-dimensional cavitating turbulent flow in a complete Francis turbine is simulated using mixture model for cavity/liquid two-phase flows. Numerical analysis is carried out using ANSYS CFX software release 12, and standard k-ε turbulence model is adopted for this analysis. The computational fluid domain consist of spiral casing, stay vanes, guide vanes, runner and draft tube. The computational domain is discretized with a three-dimensional mesh system of unstructured tetrahedron mesh. The finite volume method (FVM) is used to solve the governing equations of the mixture model. Results of cavitation on the runner’s blades under three different boundary conditions are presented and discussed. From the numerical results it has been found that the numerical method was successfully applied to simulate the cavitating two-phase turbulent flow through a Francis turbine, and also cavitation is clearly predicted in the form of water vapor formation inside the turbine. By comparison the numerical prediction results with a real runner; it’s shown that the region of higher volume fraction obtained by simulation is consistent with the region of runner cavitation damage.

Keywords: computational fluid dynamics, hydraulic francis turbine, numerical simulation, two-phase mixture cavitation model

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Authors: Ping Ren, Mao Wen, Kan Zhang, Weitao Zheng

Abstract:

The improvement of comprehensive properties including hardness, toughness, wear, and corrosion resistance in the transition metal carbides/nitrides TMCN films, especially avoiding the trade-off between hardness and toughness, is strongly required to adapt to various applications. Although incorporating ductile metal DM phase into the TMCN via thermally-induced phase separation has been emerged as an effective approach to toughen TMCN-based films, the DM is just limited to some soft ductile metal (i.e. Cu, Ag, Au immiscibility with the TMCN. Moreover, hardness is highly sensitive to soft DM content and can be significantly worsened. Hence, a novel preparation method should be attempted to broaden the DM selection and assemble much more ordered nanocomposite structure for improving the comprehensive properties. Here, we provide a new strategy, by activating solid-state dewetting during layered deposition, to accomplish the self-assembly of ordered TaC@Ta core-shell-like nanocomposite film consisting of TaC nanocrystalline encapsulated with thin pseudocrystal Ta tissue. That results in the superhard (~45.1 GPa) dominated by Orowan strengthening mechanism and high toughness attributed to indenter-induced phase transformation from the pseudocrystal to body-centered cubic Ta, together with the drastically enhanced wear and corrosion resistance. Furthermore, very thin pseudocrystal Ta encapsulated layer (~1.5 nm) in the TaC@Ta core-shell-like structure helps for promoting the formation of lubricious TaOₓ Magnéli phase during sliding, thereby further dropping the coefficient of friction. Apparently, solid-state dewetting may provide a new route to construct ordered TMC(N)@TM core-shell-like nanocomposite capable of combining superhard, high toughness, low friction, superior wear with corrosion resistance.

Keywords: corrosion, nanocomposite film, solid-state dewetting, tribology

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Authors: Osman Adiguzel

Abstract:

Shape-memory alloys are a new class of functional materials with a peculiar property known as shape memory effect. These alloys return to a previously defined shape on heating after deformation in low temperature product phase region and take place in a class of functional materials due to this property. The origin of this phenomenon lies in the fact that the material changes its internal crystalline structure with changing temperature. Shape memory effect is based on martensitic transitions, which govern the remarkable changes in internal crystalline structure of materials. Martensitic transformation, which is a solid state phase transformation, occurs in thermal manner in material on cooling from high temperature parent phase region. This transformation is governed by changes in the crystalline structure of the material. Shape memory alloys cycle between original and deformed shapes in bulk level on heating and cooling, and can be used as a thermal actuator or temperature-sensitive elements due to this property. Martensitic transformations usually occur with the cooperative movement of atoms by means of lattice invariant shears. The ordered parent phase structures turn into twinned structures with this movement in crystallographic manner in thermal induced case. The twinned martensites turn into the twinned or oriented martensite by stressing the material at low temperature martensitic phase condition. The detwinned martensite turns into the parent phase structure on first heating, first cycle, and parent phase structures turn into the twinned and detwinned structures respectively in irreversible and reversible memory cases. On the other hand, shape memory materials are very important and useful in many interdisciplinary fields such as medicine, pharmacy, bioengineering, metallurgy and many engineering fields. The choice of material as well as actuator and sensor to combine it with the host structure is very essential to develop main materials and structures. Copper based alloys exhibit this property in metastable beta-phase region, which has bcc-based structures at high temperature parent phase field, and these structures martensitically turn into layered complex structures with lattice twinning following two ordered reactions on cooling. Martensitic transition occurs as self-accommodated martensite with inhomogeneous shears, lattice invariant shears which occur in two opposite directions, <110 > -type directions on the {110}-type plane of austenite matrix which is basal plane of martensite. This kind of shear can be called as {110}<110> -type mode and gives rise to the formation of layered structures, like 3R, 9R or 18R depending on the stacking sequences on the close-packed planes of the ordered lattice. In the present contribution, x-ray diffraction and transmission electron microscopy (TEM) studies were carried out on two copper based alloys which have the chemical compositions in weight; Cu-26.1%Zn 4%Al and Cu-11%Al-6%Mn. X-ray diffraction profiles and electron diffraction patterns reveal that both alloys exhibit super lattice reflections inherited from parent phase due to the displacive character of martensitic transformation. X-ray diffractograms taken in a long time interval show that locations and intensities of diffraction peaks change with the aging time at room temperature. In particular, some of the successive peak pairs providing a special relation between Miller indices come close each other.

Keywords: Shape memory effect, martensite, twinning, detwinning, self-accommodation, layered structures

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Authors: Viviana Ventre, Giacomo Di Tollo, Roberta Martino

Abstract:

The portfolio selection problem includes the evaluation of many criteria that are difficult to compare directly and is characterized by uncertain elements. The portfolio selection problem can be modeled as a group decision problem in which several experts are invited to present their assessment. In this context, it is important to study and analyze the process of reaching a consensus among group members. Indeed, due to the various diversities among experts, reaching consensus is not necessarily always simple and easily achievable. Moreover, the concept of consensus is accompanied by the concept of false consensus, which is particularly interesting in the dynamics of group decision-making processes. False consensus can alter the evaluation and selection phase of the alternative and is the consequence of the decision maker's inability to recognize that his preferences are conditioned by subjective structures. The present work aims to investigate the dynamics of consensus attainment in a group decision problem in which equivalent portfolios are proposed. In particular, the study aims to analyze the impact of the subjective structure of the decision-maker during the evaluation and selection phase of the alternatives. Therefore, the experimental framework is divided into three phases. In the first phase, experts are sent to evaluate the characteristics of all portfolios individually, without peer comparison, arriving independently at the selection of the preferred portfolio. The experts' evaluations are used to obtain individual Analytical Hierarchical Processes that define the weight that each expert gives to all criteria with respect to the proposed alternatives. This step provides insight into how the decision maker's decision process develops, step by step, from goal analysis to alternative selection. The second phase includes the description of the decision maker's state through Markov chains. In fact, the individual weights obtained in the first phase can be reviewed and described as transition weights from one state to another. Thus, with the construction of the individual transition matrices, the possible next state of the expert is determined from the individual weights at the end of the first phase. Finally, the experts meet, and the process of reaching consensus is analyzed by considering the single individual state obtained at the previous stage and the false consensus bias. The work contributes to the study of the impact of subjective structures, quantified through the Analytical Hierarchical Process, and how they combine with the false consensus bias in group decision-making dynamics and the consensus reaching process in problems involving the selection of equivalent portfolios.

Keywords: analytical hierarchical process, consensus building, false consensus effect, markov chains, portfolio selection problem

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Authors: Mookyada Mankrut, Manit Nithitanakul

Abstract:

An increase in the amount of atmospheric carbon dioxide (CO2) resulting from anthropogenic CO2 emission has been a concerned problem so far. Adsorption using porous materials is feasible way to reduce the content of CO2 emission into the atmosphere due to several advantages: low energy consumption in regeneration process, low-cost raw materials and, high CO2 adsorption capacity. In this work, the porous poly(divinylbenzene) (poly(DVB)) support was synthesized under high internal phase emulsion (HIPE) polymerization then modified with polyethyleneimine (PEI) by using solution plasma process. These porous polymers were then used as adsorbents for CO2 adsorption study. All samples were characterized by some techniques: Fourier transform infrared spectroscopy (FT-IR), scanning electron spectroscopy (SEM), water contact angle measurement and, surface area analyzer. The results of FT-IR and a decrease in contact angle, pore volume and, surface area of PEI-loaded materials demonstrated that surface of poly(DVB) support was modified. In other words, amine groups were introduced to poly(DVB) surface. In addition, not only the outer surface of poly(DVB) adsorbent was modified, but also the inner structure as shown by FT-IR study. As a result, PEI-loaded materials exhibited higher adsorption capacity, comparing with those of the unmodified poly(DVB) support.

Keywords: polyHIPEs, CO2 adsorption, solution plasma process, high internal phase emulsion

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Authors: Min Yu, Olivier T. Picot, Theo Graves Saunders, Ivo Dlouhy, Amit Mahajan, Michael J. Reece

Abstract:

Graphene was successfully introduced into a polymer-derived silicon oxycarbide (SiOC) matrix by phase transfer of graphene oxide (GO) from an aqueous (GO dispersed in water) to an organic phase (copolymer as SiOC precursor in diethyl ether). With GO concentrations increasing up to 2 vol%, graphene-containing flakes self-assembled into a lamellar structure in the matrix leading to composite with the anisotropic property. Spark plasma sintering (SPS) was applied to densify the composites with four different GO concentrations (0, 0.5, 1 and 2 vol%) up to ~2.3 g/cm3. The fracture toughness of SiOC-2 vol% GO composites was significantly increased by ~91% (from 0.70 to 1.34 MPa·m¹/²), at the expense of a decrease in the flexural strength (from 85MPa to 55MPa), compared to SiOC-0 vol% GO composites. Moreover, the electrical conductivity in the perpendicular direction (σ┴=3×10⁻¹ S/cm) in SiOC-2 vol% GO composite was two orders of magnitude higher than the parallel direction (σ║=4.7×10⁻³ S/cm) owing to the self-assembled lamellar structure of graphene in the SiOC matrix. The composites exhibited increased electrical conductivity (σ┴) from 8.4×10⁻³ to 3×10⁻¹ S/cm, with the increasing GO content from 0.5 to 2 vol%. The SiOC-2 vol% GO composites further showed the better electrochemical performance of oxygen reduction reaction (ORR) than pure graphene, exhibiting a similar onset potential (~0.75V vs. RHE) and more positive half-wave potential (~0.6V vs. RHE).

Keywords: composite, fracture toughness, flexural strength, electrical conductivity, electrochemical performance

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