Search results for: diurnal temperature cycle model

Authors: Jalal Abdulkareem Sultan, Abdulhakeem Luqman Hasan

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With the development of health care systems competition, hospitals face more and more pressures. Meanwhile, resource allocation has a vital effect on achieving competitive advantages in hospitals. Selecting the appropriate number of beds is one of the most important sections in hospital management. However, in real situation, bed allocation selection is a multiple objective problem about different items with vagueness and randomness of the data. It is very complex. Hence, research about bed allocation problem is relatively scarce under considering multiple departments, nursing hours, and stochastic information about arrival and service of patients. In this paper, we develop a fuzzy multiobjective bed allocation model for overcoming uncertainty and multiple departments. Fuzzy objectives and weights are simultaneously applied to help the managers to select the suitable beds about different departments. The proposed model is solved by using Artificial Bee Colony (ABC), which is a very effective algorithm. The paper describes an application of the model, dealing with a public hospital in Iraq. The results related that fuzzy multi-objective model was presented suitable framework for bed allocation and optimum use.

Keywords: bed allocation problem, fuzzy logic, artificial bee colony, multi-objective optimization

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Authors: Pavel Zlabek, Vaclav Mentl

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The fatigue crack growth rate evaluation is a basic experimental characteristic when assessment o f the remaining lifetime is needed. Within the repair welding technology project, the crack growth rate at cyclic loading was measured in base and weld metals and in the situation when cracks were initiated in base metal and grew into the weld metal through heat-affected zone and back to the base metal. Two welding technologies were applied and specimens in as-welded state and after heat treatment were tested. Fatigue crack growth rate measurement was performed on CrMoV pressure vessel steel and the tests were performed at room temperature. The crack growth rate was measured on CCT test specimens (see figure) for both the base and weld metals and also in the case of crack subsequent transition through all the weld zones. A 500 kN MTS controlled electro-hydraulic testing machine and Model 632.13C-20 MTS extensometer were used to perform the tests.

Keywords: cracks, fatigue, steels, weldments

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Authors: Tariq Ahmad Safapuri, Saghir Ahmad, Farhana Allai

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The present study was conducted to evaluate the effect dehydration techniques (polyhouse and tray drying), different treatment (SHMP, SHMP+ salt, salt + turmeric), different packaging material (HDPE, combination film), and different packaging methods (air, vacuum, CO2 Flush) on quality of dehydrated buffalo meat during ambient temperature storage. The quality measuring parameters included physico-chemical characteristics i.e. pH, rehydration ratio, moisture content and microbiological characteristics viz total plate content. It was found that the treatment of (SHMP, SHMP + salt, salt + turmeric increased the pH. Moisture Content of dehydrated meat samples were found in between 7.20% and 5.54%.the rehydration ratio of salt+ turmeric treated sample was found to be highest and lowest for controlled meat sample. the bacterial count log TPC/g of salt + turmeric and tray dried was lowest i.e. 1.80.During ambient temperature storage ,there was no considerable change in pH of dehydrated sample till 150 days. however the moisture content of samples increased in different packaging system in different manner. The highest moisture rise was found in case of controlled meat sample HDPE/air packed while the lowest increase was reported for SHMP+ Salt treated Packed by vacuum in combination film packed sample. Rehydration ratio was found considerably affected in case of HDPE and air packed sample dehydrated in polyhouse after 150 days of ambient storage. While there was a very little change in the rehydration ratio of meat samples packed in combination film CO2 flush system. The TPC was found under safe limit even after 150 days of storage. The microbial count was found to be lowest for salt+ turmeric treated samples after 150 days of storage.

Keywords: ambient temperature, dehydration technique, rehydration ratio, SHMP (sodium hexa meta phosphate), HDPE (high density polyethelene)

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Authors: Muhammad Idrees, Masroor Abro, Sikandar Almani

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Presently, the increasing CO₂ concentration in the atmosphere has been taken as one of the major challenges faced by the modern world. The average CO₂ in the atmosphere reached the highest value of 414.72 ppm in 2021, as reported in a conference of the parties (COP26). This study focuses on (i) the comparative study of MEA, NaOH, Acetic acid, and Na₂CO₃ in terms of their CO₂ capture performance, (ii) the significance of adding various frothing agents achieving improved absorption capacity of Na₂CO₃ and (iii) the overall economic evaluation of process with the help of Aspen Plus. The results obtained suggest that the addition of frothing agents significantly increased the absorption rate of dilute sodium carbonate such that from 45% to 99.9%. The effect of temperature, pressure and flow rate of liquid and flue gas streams on CO₂ absorption capacity was also investigated. It was found that the absorption capacity of Na₂CO₃ decreased with increasing temperature of the liquid stream and decreasing flow rate of the liquid stream and pressure of the gas stream.

Keywords: CO₂, absorbents, frothing agents, process simulation

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Authors: Tiffany Gallagher, Sheila Bennett

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Based on data from a larger study, this research is based in a small school district in Ontario, Canada, that has made a transition from self-contained classes for students with exceptionalities to inclusive classroom placements for all students with their age-appropriate peers. The school board aided this transition by hiring Inclusion Coaches with a background in special education to work alongside teachers as partners and inform their inclusive practice. Based on qualitative data from four focus groups conducted with Inclusion Coaches, as well as four blog-style reflections collected at various points over two years, six principles of inclusive practice were identified for coaches. The six principles form a model during transition: pre-requisite, process, precipice, promotion, proof, and promise. These principles are encapsulated in a visual model of a spiraling staircase displaying the conditions that exist prior to coaching, during coaching interactions and considerations for the sustainability of coaching. These six principles are re-iterative and should be re-visited each time a coaching interaction is initiated. Exploring inclusion coaching as a model emulates coaching in other contexts and allows us to examine an established process through a new lens. This research becomes increasingly important as more school boards transition toward inclusive classrooms, The Six ‘P’ Model: Principles of Inclusive Practice for Inclusion Coaches allows for a unique look into a scaffolding model of building educator capacity in an inclusive setting.

Keywords: capacity building, coaching, inclusion, special education

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Authors: Kang Lin Peng

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Space tourism emerged in 2001 and became famous in 2021, following the development of space technology. The space market is twisted because of the excess demand. Space tourism is currently rare and extremely expensive, with biased luxury product pricing, which is the seller’s market that consumers can not bargain with. Spaceship companies such as Virgin Galactic, Blue Origin, and Space X have been charged space tourism prices from 200 thousand to 55 million depending on various heights in space. There should be a reasonable price based on a fair basis. This study aims to derive a spacetime pricing model, which is different from the general pricing model on the earth’s surface. We apply general relativity theory to deduct the mathematical formula for the space tourism pricing model, which covers the traditional time-independent model. In the future, the price of space travel will be different from current flight travel when space travel is measured in lightyear units. The pricing of general commodities mainly considers the general equilibrium of supply and demand. The pricing model considers risks and returns with the dependent time variable as acceptable when commodities are on the earth’s surface, called flat spacetime. Current economic theories based on the independent time scale in the flat spacetime do not consider the curvature of spacetime. Current flight services flying the height of 6, 12, and 19 kilometers are charging with a pricing model that measures time coordinate independently. However, the emergence of space tourism is flying heights above 100 to 550 kilometers that have enlarged the spacetime curvature, which means tourists will escape from a zero curvature on the earth’s surface to the large curvature of space. Different spacetime spans should be considered in the pricing model of space travel to echo general relativity theory. Intuitively, this spacetime commodity needs to consider changing the spacetime curvature from the earth to space. We can assume the value of each spacetime curvature unit corresponding to the gradient change of each Ricci or energy-momentum tensor. Then we know how much to spend by integrating the spacetime from the earth to space. The concept is adding a price p component corresponding to the general relativity theory. The space travel pricing model degenerates into a time-independent model, which becomes a model of traditional commodity pricing. The contribution is that the deriving of the space tourism pricing model will be a breakthrough in philosophical and practical issues for space travel. The results of the space tourism pricing model extend the traditional time-independent flat spacetime mode. The pricing model embedded spacetime as the general relativity theory can better reflect the rationality and accuracy of space travel on the universal scale. The universal scale from independent-time scale to spacetime scale will bring a brand-new pricing concept for space traveling commodities. Fair and efficient spacetime economics will also bring to humans’ travel when we can travel in lightyear units in the future.

Keywords: space tourism, spacetime pricing model, general relativity theory, spacetime curvature

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Authors: A. Katsman, L. Bloch, Y. Etinger, Y. Kauffmann, B. Pokroy

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Various nanosized amorphous alumina thin films in the range of (2.4 - 63.1) nm were deposited onto amorphous carbon and amorphous Si3N4 membrane grids. Transmission electron microscopy (TEM), electron energy loss spectroscopy (EELS), X-ray photoelectron spectroscopy (XPS) and differential scanning calorimetry (DSC) techniques were used to probe the size effect on the short range order and the amorphous to crystalline phase transition temperature. It was found that the short-range order changes as a function of size: the fraction of tetrahedral Al sites is greater in thinner amorphous films. This result correlates with the change of amorphous alumina density with the film thickness demonstrated by the reflectivity experiments: the thinner amorphous films have the less density. These effects are discussed in terms of surface reconstruction of the amorphous alumina films. The average atomic binding energy in the thin film layer decreases with decease of the thickness, while the average O-Al interatomic distance increases. The reconstruction of amorphous alumina is induced by the surface reconstruction, and the short range order changes being dependent on the density. Decrease of the surface energy during reconstruction is the driving force of the alumina reconstruction (density change) followed by relaxation process (short range order change). The amorphous to crystalline phase transition temperature measured by DSC rises with the decrease in thickness from 997.6°C for 13.9 nm to 1020.4 °C for 2.7 nm thick. This effect was attributed to the different film densities: formation of nanovoids preceding and accompanying crystallization process influences the crystallization rate, and by these means, the temperature of crystallization peak.

Keywords: amorphous alumina, density, short range order, size effect

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Authors: A. Guemache, M. Omari

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Oxides with formula Ca1-xSrx MnO3 (0≤x≤0.2) were synthesized using co-precipitation method. The identification of the obtained phase was carried out using infrared spectroscopy and X-ray diffraction. Thermogravimetric and differential analysis was permitted to characterize different transformations of precursors which take place during one heating cycle. The study of electrochemical behavior was carried out by cyclic voltammetry and impedance spectroscopy. The obtained results show that apparent catalytic activity improved when increasing the concentration of strontium. Anodic current densities varies from 1.3 to 5.9 mA/cm2 at the rate scan of 20 mV.s-1 and a potential 0.8 V for oxides with composition x=0 to 0.2.

Keywords: oxide, co-precipitation, electrochemical properties, cathode-type

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Authors: Champika S. Kariyawasam

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The distribution of gorse (Ulex europaeus) plants in South Australia has been modelled using 126 presence-only location data as a function of seven climate parameters. The predicted range of U. europaeus is mainly along the Mount Lofty Ranges in the Adelaide Hills and on Kangaroo Island. Annual precipitation and yearly average aridity index appeared to be the highest contributing variables to the final model formulation. The Jackknife procedure was employed to identify the contribution of different variables to gorse model outputs and response curves were used to predict changes with changing environmental variables. Based on this analysis, it was revealed that the combined effect of one or more variables could make a completely different impact to the original variables on their own to the model prediction. This work also demonstrates the need for a careful approach when selecting environmental variables for projecting correlative models to climatically distinct area. Maxent acts as a robust model when projecting the fitted species distribution model to another area with changing climatic conditions, whereas the generalized linear model, bioclim, and domain models to be less robust in this regard. These findings are important not only for predicting and managing invasive alien gorse in South Australia and Sri Lanka but also in other countries of the invasive range.

Keywords: invasive species, Maxent, species distribution modelling, Ulex europaeus

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Authors: Huijuan Liu, Fukun Li, Hao Yuan

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The bolted spherical node is a common type of joint in space steel structures. The bolt-sphere joint portion almost always controls the bearing capacity of the bolted spherical node. The investigation of the bearing performance and progressive failure in service often requires high-fidelity numerical models. This paper focuses on the constitutive models of bolt steel and sphere steel used in China’s space structure construction. The elastoplastic model is determined by a standard tensile test and calibrated Voce saturated hardening rule. The ductile damage is found dominant based on the fractography analysis. Then Rice-Tracey ductile fracture rule is selected and the model parameters are calibrated based on tensile tests of notched specimens. These calibrated material models can benefit research or engineering work in similar fields.

Keywords: bolt-sphere joint, steel, constitutive model, ductile damage, model calibration

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Authors: Anaam H. Al-ShaikhAli, Mansour A. Al-Herz

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The research leverages the proven HS-FCC technology to directly crack crude oils into petrochemical building blocks. Crude oils were subjected to an optimized hydro-processing process where metal contaminants and sulfur were reduced to an acceptable level for feeding the crudes into the HS-FCC technology. The hydro-processing is achieved through a fixed-bed reactor which is composed of 3 layers of catalysts. The crude oil is passed through a dementalization catalyst followed by a desulfurization catalyst and finally a de-aromatization catalyst. The hydroprocessing was conducted at an optimized liquid hourly space velocity (LHSV), temperature, and pressure for an optimal reduction of metals and sulfur from the crudes. The hydro-processed crudes were then fed into a micro activity testing (MAT) unit to simulate the HS-FCC technology. The catalytic cracking of crude oils was conducted over tailored catalyst formulations under an optimized catalyst/oil ratio and cracking temperature for optimal production of total light olefins.

Keywords: petrochemical, catalytic cracking, catalyst synthesis, HS-FCC technology

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Authors: João F. A. Martos, Felipe J. Costa, Sergio N. P. Laiton, Bruno C. Lima, Israel S. Rêgo, Paulo P. G. Toro

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Nowadays, the scramjet is a topic that has attracted the attention of several scientific communities (USA, Australia, Germany, France, Japan, India, China, Russia), that are investing in this in this type of propulsion system due its interest to facilitate access to space and reach hypersonic speed, who have invested in this type of propulsion due to the interest in facilitating access to space. The Brazilian hypersonic scramjet aerospace vehicle 14-X B is a technological demonstrator of a hypersonic airbreathing propulsion system based on the supersonic combustion (scramjet) intended to be tested in flight into the Earth's atmosphere at 30 km altitude and Mach number 7. The 14-X B has been designed at the Prof. Henry T. Nagamatsu Laboratory of Aerothermodynamics and Hypersonics of the Institute for Advanced Studies (IEAv) in Brazil. The IEAv Hypersonic Shock Tunnel, named T3, is a ground-test facility able to reproduce the flight conditions as the Mach number as well as pressure and temperature in the test section close to those encountered during the test flight of the vehicle 14-X B into design conditions. A 1-m long stainless steel 14-X B model was experimentally investigated at T3 Hypersonic Shock Tunnel, for freestream Mach number 7. Static pressure measurements along the lower surface of the 14-X B model, along with high-speed schlieren photographs taken from the 5.5° leading edge and the 14.5° deflection compression ramp, provided experimental data that were compared to the analytical-theoretical solutions and the computational fluid dynamics (CFD) simulations. The results show a good qualitative agreement, and in consequence demonstrating the importance of these methods in the project of the 14-X B hypersonic aerospace vehicle.

Keywords: 14-X, CFD, hypersonic, hypersonic shock tunnel, scramjet

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Authors: Shweta Kumari, Parmjit S. Panesar, Manab B. Bera

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The hydrolysis of lactose using β-galactosidase is one of the most promising biotechnological applications, which has wide range of potential applications in food processing industries. However, due to intracellular location of the yeast enzyme, and expensive extraction methods, the industrial applications of enzymatic hydrolysis processes are being hampered. The use of permeabilization technique can help to overcome the problems associated with enzyme extraction and purification of yeast cells and to develop the economically viable process for the utilization of whole cell biocatalysts in food industries. In the present investigation, standardization of permeabilization process of novel yeast isolate was carried out using a statistical model approach known as Response Surface Methodology (RSM) to achieve maximal b-galactosidase activity. The optimum operating conditions for permeabilization process for optimal β-galactosidase activity obtained by RSM were 1:1 ratio of toluene (25%, v/v) and ethanol (50%, v/v), 25.0 oC temperature and treatment time of 12 min, which displayed enzyme activity of 1.71 IU /mg DW.

Keywords: β-galactosidase, optimization, permeabilization, response surface methodology, yeast

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Authors: Longqing Li

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The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.

Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting

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Authors: Bo Hu, Shibo Wang, Haoyang Zhang, Jie Shi

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With the development of sonar detection technology, the acoustic stealth technology of underwater vehicles is facing severe challenges. The underwater acoustic coating is developing towards the direction of low-frequency absorption capability and broad absorption frequency bandwidth. In this paper, an acoustic model of underwater acoustic coating of composite material embedded with periodical steel structure is presented. The model has multiple high absorption peaks in the frequency range of 1kHz-8kHz, where achieves high sound absorption and broad bandwidth performance. It is found that the frequencies of the absorption peaks are related to the classic half-wavelength transmission principle. The sound absorption performance of the acoustic model is investigated by the finite element method using COMSOL software. The sound absorption mechanism of the proposed model is explained by the distributions of the displacement vector field. The influence of geometric parameters of periodical steel structure, including thickness and distance, on the sound absorption ability of the proposed model are further discussed. The acoustic model proposed in this study provides an idea for the design of underwater low-frequency broadband acoustic coating, and the results shows the possibility and feasibility for practical underwater application.

Keywords: acoustic coating, composite material, broad frequency bandwidth, sound absorption performance

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Aynur Aker, Hasan Kaya

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In recent years, the use of the aluminum based alloys in the industry and technology are increasing. Alloying elements in aluminum have further been improving the strength and stiffness properties that provide superior compared to other metals. In this study, investigation of physical properties (microstructure, microhardness, tensile strength, electrical conductivity and thermal properties) in the Al-12.6wt.%Si-%2wt.Ni ternary alloy were investigated. Al-Si-Ni alloy was prepared in a graphite crucible under vacuum atmosphere. The samples were directionally solidified upwards with different growth rate (V) at constant temperature gradient G (7.73 K/mm). The microstructures (flake spacings, λ), microhardness (HV), ultimate tensile strength, electrical resistivity and thermal properties enthalpy of fusion and specific heat and melting temperature) of the samples were measured. Influence of the growth rate and flake spacings on microhardness, ultimate tensile strength and electrical resistivity were investigated and relationships between them were experimentally obtained by using regression analysis. According to results, λ values decrease with increasing V, but microhardness, ultimate tensile strength, electrical resistivity values increase with increasing V. Variations of electrical resistivity for cast samples with the temperature in the range of 300-1200 K were also measured by using a standard dc four-point probe technique. The enthalpy of fusion and specific heat for the same alloy was also determined by means of differential scanning calorimeter (DSC) from heating trace during the transformation from liquid to solid. The results obtained in this work were compared with the previous similar experimental results obtained for binary and ternary alloys.

Keywords: electrical resistivity, enthalpy, microhardness, solidification, tensile stress

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Authors: Hasan Kaya

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Effect of lead content on the microstructure, mechanical (microhardness, ultimate tensile strength) and electrical resistivity properties of Al–Si eutectic alloys has been investigated. Al–12.6 Si–xSn (x=1, 2, 4, 6 and 8 wt. %) were prepared using metals of 99.99% high purity in the vacuum atmosphere. These alloys were directionally solidified under constant temperature gradient (5.50 K/mm) and growth rate (8.25 μm/s) by using a Bridgman–type directional solidification furnace. Eutectic spacing, microhardness, ultimate tensile strength and electrical resistivity were expressed as functions of the composition by using a linear regression analysis. The dependency of the eutectic spacing, microhardness, tensile strength and electrical resistivity on the composition (Sn content) were determined. According to experimental results, the microhardness, ultimate tensile strength and electrical resistivity of the solidified samples increase with increasing the Sn content, but decrease eutectic spacing. Variation of electrical resistivity with the temperature in the range of 300-500 K for studied alloys was also measured by using a standard d.c. four-point probe technique.

Keywords: content elements, solidification, microhardness, strength

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Changshan Zhang, Zhijin Yu, Shixing Fan

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A comprehensive hazard evaluation for coal self-heating in composite long-wall gobs is heavily dependent on computational simulation. In this study, the spatial distributions of cracks which caused significant air leakage were simulated by universal distinct element code (UDEC) simulation. Based on the main routes of air leakage and characteristics of coal self-heating, a computational fluid dynamics (CFD) modeling was conducted to model the coal spontaneous combustion dangerous area in composite long-wall gobs. The results included the oxygen concentration distributions and temperature profiles showed that the numerical approach is validated by comparison with the test data. Furthermore, under the conditions of specific engineering, the major locations where some techniques for extinguishing and preventing long-wall gob fires need to be put into practice were also examined.

Keywords: computational simulation, UDEC simulation, coal self-heating, CFD modeling, long-wall gobs

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Kannapha Amaruchkul

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We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

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Authors: Felipe J. Costa, João F. A. Martos, Ronaldo L. Cardoso, Israel S. Rêgo, Marco A. S. Minucci, Antonio C. Oliveira, Paulo G. P. Toro

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The Prof. Henry T. Nagamatsu Laboratory of Aerothermodynamics and Hypersonics, at the Institute for Advanced Studies designed the Brazilian 14-X Hypersonic Aerospace Vehicle, which is a technological demonstrator endowed with two innovative technologies: waverider technology, to obtain lift from conical shockwave during the hypersonic flight; and uses hypersonic airbreathing propulsion system called scramjet that is based on supersonic combustion, to perform flights on Earth's atmosphere at 30 km altitude at Mach numbers 7 and 10. The scramjet is an aeronautical engine without moving parts that promote compression and deceleration of freestream atmospheric air at the inlet through the conical/oblique shockwaves generated during the hypersonic flight. During high speed flight, the shock waves and the viscous forces yield the phenomenon called aerodynamic heating, where this physical meaning is the friction between the fluid filaments and the body or compression at the stagnation regions of the leading edge that converts the kinetic energy into heat within a thin layer of air which blankets the body. The temperature of this layer increases with the square of the speed. This high temperature is concentrated in the boundary-layer, where heat will flow readily from the boundary-layer to the hypersonic aerospace vehicle structure. Fay and Riddell and Eckert methods are applied to the stagnation point and to the flat plate segments in order to calculate the aerodynamic heating. On the understanding of the aerodynamic heating it is important to analyze the heat conduction transfer to the 14-X waverider internal structure. ANSYS Workbench software provides the Thermal Numerical Analysis, using Finite Element Method of the 14-X waverider unpowered scramjet at 30 km altitude at Mach number 7 and 10 in terms of temperature and heat flux. Finally, it is possible to verify if the internal temperature complies with the requirements for embedded systems, and, if is necessary to do modifications on the structure in terms of wall thickness and materials.

Keywords: aerodynamic heating, hypersonic, scramjet, thermal analysis

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Authors: O. Ojeda Mena, Y. Cressault, P. Teulet, J. P. Gonnet, D. F. N. Santos, MD. Cunha, M. S. Benilov

Abstract:

The assumption of plasma in local thermal equilibrium (LTE) is commonly used to perform electric arc simulations for industrial applications. This assumption allows to model the arc using a set of magneto-hydromagnetic equations that can be solved with a computational fluid dynamic code. However, the LTE description is only valid in the arc column, whereas in the regions close to the electrodes the plasma deviates from the LTE state. The importance of these near-electrode regions is non-trivial since they define the energy and current transfer between the arc and the electrodes. Therefore, any accurate modelling of the arc must include a good description of the arc-electrode phenomena. Due to the modelling complexity and computational cost of solving the near-electrode layers, a simplified description of the arc-electrode interaction was developed in a previous work to study a steady high-pressure arc discharge, where the near-electrode regions are introduced at the interface between arc and electrode as boundary conditions. The present work proposes a similar approach to simulate the arc ignition in a free-burning arc configuration following an LTE description of the plasma. To obtain the transient evolution of the arc characteristics, appropriate boundary conditions for both the near-cathode and the near-anode regions are used based on recent publications. The arc-cathode interaction is modeled using a non-linear surface heating approach considering the secondary electron emission. On the other hand, the interaction between the arc and the anode is taken into account by means of the heating voltage approach. From the numerical modelling, three main stages can be identified during the arc ignition. Initially, a glow discharge is observed, where the cold non-thermionic cathode is uniformly heated at its surface and the near-cathode voltage drop is in the order of a few hundred volts. Next, a spot with high temperature is formed at the cathode tip followed by a sudden decrease of the near-cathode voltage drop, marking the glow-to-arc discharge transition. During this stage, the LTE plasma also presents an important increase of the temperature in the region adjacent to the hot spot. Finally, the near-cathode voltage drop stabilizes at a few volts and both the electrode and plasma temperatures reach the steady solution. The results after some seconds are similar to those presented for thermionic cathodes.

Keywords: arc-electrode interaction, thermal plasmas, electric arc simulation, cold electrodes

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Authors: Moustafa Osman Mohammed

Abstract:

This paper is mapping air quality model to engineering the industrial system that ultimately utilized in extensive range of energy systems, distribution resources, and end-user technologies. The model is determining long-range transport patterns contribution as area source can either traced from 48 hrs backward trajectory model or remotely described from background measurements data in those days. The trajectory model will be run within stable conditions and quite constant parameters of the atmospheric pressure at the most time of the year. Air parcel trajectory is necessary for estimating the long-range transport of pollutants and other chemical species. It provides a better understanding of airflow patterns. Since a large amount of meteorological data and a great number of calculations are required to drive trajectory, it will be very useful to apply HYPSLIT model to locate areas and boundaries influence air quality at regional location of Windsor. 2–days backward trajectories model at high and low concentration measurements below and upward the benchmark which was areas influence air quality measurement levels. The benchmark level will be considered as 30 (μg/m3) as the moderate level for Ontario region. Thereby, air quality model is incorporating a midpoint concept between biotic and abiotic components to broaden the scope of quantification impact. The later outcomes’ theories of environmental obligation suggest either a recommendation or a decision of what is a legislative should be achieved in mitigation measures of air emission impact ultimately.

Keywords: air quality, management systems, environmental impact assessment, industrial ecology, climate change

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

Abstract:

The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Andrei Contan, Richard Torkar

Abstract:

Aim: The process of test automation and its practices in industry have to be better understood, both for the industry itself and for the research community. Method: We conducted a quantitative industry survey by asking IT professionals to answer questions related to the area of test automation. Results: Test automation needs and practices vary greatly between organizations at different stages of the software development life cycle. Conclusions: Most of the findings are general test automation challenges and are specific to small- to medium-sized companies, developing software applications in the web, desktop or mobile domain.

Keywords: survey, testing, test automation, status of test automation

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Authors: K. D. Mandal, Anil Kumar Mourya, Ankur Khare

Abstract:

Ceramics of 0.6 CaCu3TiO12 – 0.2 Bi2/3Cu3TiO12 – 0.2 Y2/3Cu3TiO12 (i.e. 0.6CCTO-0.2BCTO-0.2 YCTO) were prepared via semi - wet route. The phase structure of the sample was identified by X-Ray diffraction. The micro structure of the sample was observed by SEM, which displays grains of different shapes having diameter in range of 2 µm–4 µm. We have studied the frequency and temperature dependence of permittivity and impedance of the compound with LCR Meter in the range of 100 Hz–1 MHz and 300–500 K. The material shows its highest dielectric constant (428000) at 100 Hz and 368 K. The material shows Debye–like relaxation and their dielectric constant are independent of frequency and temperature over a wide range. The sample shows two electrical responses in impedance formalism, indicating that there are two distinct contributions. We attribute them to grain and grain boundaries in the ceramic sample and explain the dielectric behaviors by Maxwell–Wagner relaxation arising at the interfaces between grain and their boundaries.

Keywords: complex perovskite, ceramics composite, impedance study, SEM

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

Abstract:

This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Woranittha Kritsarikan

Abstract:

Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as electrical and medical devices and account for 13.5 % of the permanent magnet’s market. Since its typical composition of 29 - 32 % Nd, 64.2 – 68.5 % Fe and 1 – 1.2 % B contains a significant amount of rare earth metals and will be subjected to shortages in the future. Domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social, environmental impacts toward the circular economy. Most research works focus on recycling the magnet wastes, both from the manufacturing process and end of life. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as the types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd₂O₃) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550 - 800 ᵒC to enable selective leaching of neodymium in the subsequent leaching step using H₂SO₄ at 2.5 M over 24 hours. The leachate was then subjected to drying and roasting at 700 – 800 ᵒC prior to precipitation by oxalic acid and calcination to obtain neodymium oxide as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to the increasing amount of hematite (Fe₂O₃) as the main composition with a smaller amount of magnetite (Fe3O4) found. Peaks of neodymium oxide (Nd₂O₃) were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO₃) was present and its XRD peaks were pronounced at higher oxidative roasting temperature. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form hematite as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of magnetite was still detected by XRD. The higher roasting temperature at 800 ᵒC resulted in a greater Fe2O3 to Nd2(SO4)3 ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 ᵒC followed by acid leaching and roasting at 800 ᵒC gave the optimum condition for further steps of precipitation and calcination to finally achieve neodymium oxide.

Keywords: NdFeB magnet waste, oxidative roasting, recycling, selective leaching

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