Search results for: diurnal temperature cycle model

Authors: Shyamlal Kumawat

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Cloud computing is shifting the approach IT capital are utilized. Cloud computing dynamically delivers convenient, on-demand access to shared pools of software resources, platform and hardware as a service through internet. The cloud computing model—made promising by sophisticated automation, provisioning and virtualization technologies. Users want the ability to access these services including infrastructure resources, how and when they choose. To accommodate this shift in the consumption model technology has to deal with the security, compatibility and trust issues associated with delivering that convenience to application business owners, developers and users. Absent of these issues, trust has attracted extensive attention in Cloud computing as a solution to enhance the security. This paper proposes a trusted computing technology through Standard Resource parameter Based Trust Model in Cloud Computing to select the appropriate cloud service providers. The direct trust of cloud entities is computed on basis of the interaction evidences in past and sustained on its present performances. Various SLA parameters between consumer and provider are considered in trust computation and compliance process. The simulations are performed using CloudSim framework and experimental results show that the proposed model is effective and extensible.

Keywords: cloud, Iaas, Saas, Paas

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Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

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Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

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The rapid growth of telehealth Internet of Things (IoT) devices has raised concerns about energy consumption and efficient data processing. This paper introduces an energy-efficient model that integrates telehealth IoT devices with a fog and cloud computing-based platform, offering a sustainable and robust solution to overcome these challenges. Our model employs fog computing as a localized data processing layer while leveraging cloud computing for resource-intensive tasks, significantly reducing energy consumption. We incorporate adaptive energy-saving strategies. Simulation analysis validates our approach's effectiveness in enhancing energy efficiency for telehealth IoT systems integrated with localized fog nodes and both private and public cloud infrastructures. Future research will focus on further optimization of the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability in other healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

Procedia PDF Downloads 86

Authors: T. Godwin

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A call-taxi system is a type of taxi service where a taxi could be requested through a phone call or mobile app. A schematic functioning of a call-taxi system is modeled using Petri net, which provides the necessary conditions for a taxi to be assigned by a dispatcher to pick a customer as well as the conditions for the taxi to be released by the customer. A Petri net is a graphical modeling tool used to understand sequences, concurrences, and confluences of activities in the working of discrete event systems. It uses tokens on a directed bipartite multi-graph to simulate the activities of a system. The Petri net model is translated into a simulation model and a call-taxi system is simulated. The simulation model helps in evaluating the operation of a call-taxi system based on the fleet size as well as the operating policies for call-taxi assignment and empty call-taxi repositioning. The developed Petri net based simulation model can be used to decide the fleet size as well as the call-taxi assignment policies for a call-taxi system.

Keywords: call-taxi, discrete event system, petri net, simulation modeling

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Authors: Moses Aron, Elias Mwakilama, Jimmy Namangale

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Spending more time on long queues for a basic service remains a common challenge to most developing countries, including Malawi. For health sector in particular, Out-Patient Department (OPD) experiences long queues. This puts the lives of patients at risk. However, using queuing analysis to under the nature of the problems and efficiency of service systems, such problems can be abated. Based on a kind of service, literature proposes different possible queuing models. However, unlike using generalized assumed models proposed by literature, use of real time case study data can help in deeper understanding the particular problem model and how such a model can vary from one day to the other and also from each case to another. As such, this study uses data obtained from one urban HC for BP, Pediatric and General OPD cases to investigate an average queuing time for patients within the system. It seeks to highlight the proper queuing model by investigating the kind of distributions functions over patient’s arrival time, inter-arrival time, waiting time and service time. Comparable with the standard set values by WHO, the study found that patients at this HC spend more waiting times than service times. On model investigation, different days presented different models ranging from an assumed M/M/1, M/M/2 to M/Er/2. As such, through sensitivity analysis, in general, a commonly assumed M/M/1 model failed to fit the data but rather an M/Er/2 demonstrated to fit well. An M/Er/3 model seemed to be good in terms of measuring resource utilization, proposing a need to increase medical personnel at this HC. However, an M/Er/4 showed to cause more idleness of human resources.

Keywords: health care, out-patient department, queuing model, sensitivity analysis

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Authors: Hongbin Yang, Mingxue Liao, Changwen Zheng, Mengyao Kong, Chaohui Liu

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Microfacet-based reflection models are widely used to model light reflections for rough surfaces. Microfacet models have become the standard surface material building block for describing specular components with varying roughness; and yet, while they possess many desirable properties as well as produce convincing results, their design ignores important sources of scattering, which can cause a significant loss of energy. Specifically, they only simulate the single scattering on the microfacets and ignore the subsequent interactions. As the roughness increases, the interaction will become more and more important. So a multiple-scattering microfacet model based on specular V-cavity is presented for this important open problem. However, it spends much unnecessary rendering time because of setting the same number of scatterings for different roughness surfaces. In this paper, we design a geometric attenuation term G to compute the BRDF (Bidirectional reflection distribution function) of multiple scattering of rough surfaces. Moreover, we consider determining the number of scattering by deterministic heuristics for different roughness surfaces. As a result, our model produces a similar appearance of the objects with the state of the art model with significantly improved rendering efficiency. Finally, we derive a multiple scattering BRDF based on the original microfacet framework.

Keywords: bidirectional reflection distribution function, BRDF, geometric attenuation term, multiple scattering, V-cavity model

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Authors: Anshul Ashu

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Computers are applied to the vehicle aerodynamics in two ways. One of two is Computational Fluid Dynamics (CFD) and other is Computer Aided Flow Visualization (CAFV). Out of two CFD is chosen because it shows the result with computer graphics. The simulation of flow field around the vehicle is one of the important CFD applications. The flow field can be solved numerically using panel methods, k-ε method, and direct simulation methods. The spoiler is the tool in vehicle aerodynamics used to minimize unfavorable aerodynamic effects around the vehicle and the parallel spoiler is set of two spoilers which are designed in such a manner that it could effectively reduce the drag. In this study, the standard k-ε model of the simplified version of Bugatti Veyron, Audi R8 and Porsche 911 are used to simulate the external flow field. Flow simulation is done for variable Reynolds number. The flow simulation consists of three different levels, first over the model without a rear spoiler, second for over model with single rear spoiler, and third over the model with parallel rear-spoiler. The second and third level has following parameter: the shape of the spoiler, the angle of attack and attachment position. A thorough analysis of simulations results has been found. And a new parallel spoiler is designed. It shows a little improvement in vehicle aerodynamics with a decrease in vehicle aerodynamic drag and lift. Hence, it leads to good fuel economy and traction force of the model.

Keywords: drag, lift, flow simulation, spoiler

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Authors: Shay Kee Tan, Kok Haur Ng, Jennifer So-Kuen Chan

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This paper extends the conditional autoregressive range (CARR) model to multivariate CARR (MCARR) model and further to the two-stage MCARR-return model to model and forecast volatilities, correlations and returns of multiple financial assets. The first stage model fits the scaled realised Parkinson volatility measures using individual series and their pairwise sums of indices to the MCARR model to obtain in-sample estimates and forecasts of volatilities for these individual and pairwise sum series. Then covariances are calculated to construct the fitted variance-covariance matrix of returns which are imputed into the stage-two return model to capture the heteroskedasticity of assets’ returns. We investigate different choices of mean functions to describe the volatility dynamics. Empirical applications are based on the Standard and Poor 500, Dow Jones Industrial Average and Dow Jones United States Financial Service Indices. Results show that the stage-one MCARR models using asymmetric mean functions give better in-sample model fits than those based on symmetric mean functions. They also provide better out-of-sample volatility forecasts than those using CARR models based on two robust loss functions with the scaled realised open-to-close volatility measure as the proxy for the unobserved true volatility. We also find that the stage-two return models with constant means and multivariate Student-t errors give better in-sample fits than the Baba, Engle, Kraft, and Kroner type of generalized autoregressive conditional heteroskedasticity (BEKK-GARCH) models. The estimates and forecasts of value-at-risk (VaR) and conditional VaR based on the best MCARR-return models for each asset are provided and tested using Kupiec test to confirm the accuracy of the VaR forecasts.

Keywords: range-based volatility, correlation, multivariate CARR-return model, value-at-risk, conditional value-at-risk

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Authors: Masahiro Suzuki, Nobuyuki Okura

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The crosswind effect on ground transportations has been extensively investigated for decades. The effect of tornado, however, has been hardly studied in spite of the fact that even heavy ground vehicles, namely, trains were overturned by tornadoes with casualties in the past. Therefore, aerodynamic effects of the tornado on the train were studied by several approaches in this study. First, an experimental facility was developed to clarify aerodynamic forces acting on a vehicle running through a tornado. Our experimental set-up consists of two apparatus. One is a tornado simulator, and the other is a moving model rig. PIV measurements showed that the tornado simulator can generate a swirling-flow field similar to those of the natural tornadoes. The flow field has the maximum tangential velocity of 7.4 m/s and the vortex core radius of 96 mm. The moving model rig makes a 1/40 scale model train of single-car/three-car unit run thorough the swirling flow with the maximum speed of 4.3 m/s. The model car has 72 pressure ports on its surface to estimate the aerodynamic forces. The experimental results show that the aerodynamic forces vary its magnitude and direction depends on the location of the vehicle in the flow field. Second, the aerodynamic forces on the train were estimated by using Rankin vortex model. The Rankin vortex model is a simple tornado model which widely used in the field of civil engineering. The estimated aerodynamic forces on the middle car were fairly good agreement with the experimental results. Effects of the vortex core radius and the path of the train on the aerodynamic forces were investigated using the Rankin vortex model. The results shows that the side and lift forces increases as the vortex core radius increases, while the yawing moment is maximum when the core radius is 0.3875 times of the car length. Third, a computational simulation was conducted to clarify the flow field around the train. The simulated results qualitatively agreed with the experimental ones.

Keywords: aerodynamic force, experimental method, tornado, train

Procedia PDF Downloads 237

Authors: Titin Handayani, Adi Mulyanto, Fajar Eko Priyanto

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It is generally recognized, that algae could be an interesting option for reducing CO₂ emissions. Based on light and CO₂, algae can be used for the production various economically interesting products. Current algae cultivation techniques, however, still present a number of limitations. Efficient feeding of CO₂, especially on a large scale, is one of them. Current methods for CO₂ feeding to algae cultures rely on the sparging pure CO₂ or directly from flue gas. The limiting factor in this system is the solubility of CO₂ in water, which demands a considerable amount of energy for an effective gas to liquid transfer and leads to losses to the atmosphere. Due to the current ineffective methods for CO₂ introduction into algae ponds very large surface areas would be required for enough ponds to capture a considerable amount of the CO₂. The purpose of this study is to assess technology to capture carbon dioxide (CO₂) emissions generated by industry by utilizing of microalgae Chlorella sp. The microalgae were cultivated in a bioreactor culture pond raceway type. The result is expected to be useful in mitigating the effects of greenhouse gases in reducing the CO₂ emissions. The research activities include: (1) Characterization of boiler flue gas, (2) Operation of culture pond, (3) Sampling and sample analysis. The results of this study showed that the initial assessment absorption of the flue gas by microalgae using 1000 L raceway pond completed by heat exchanger were quite promising. The transfer of CO₂ into the pond culture system was run well. This identified from the success of cooling the boiler flue gas from the temperature of about 200 °C to below ambient temperature. Except for the temperature, the gas bubbles into the culture media were quite fine. Therefore, the contact between the gas and the media was well performed. The efficiency of CO₂ absorption by Chlorella sp reached 6.68 % with an average CO₂ loading of 0.29 g/L/day.

Keywords: Chlorella sp., CO2 emission, heat exchange, microalgae, milk industry, raceway pond

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Authors: K. Petcharaporn, S. Kumchoo

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The acidity (citric acid) is one of the chemical contents that can refer to the internal quality and the maturity index of tomato. The titratable acidity (%TA) can be predicted by a non-destructive method prediction by using the transmittance short wavelength (SW-NIR). Spectroscopy in the wavelength range between 665-955 nm. The set of 167 tomato samples divided into groups of 117 tomatoes sample for training set and 50 tomatoes sample for test set were used to establish the calibration model to predict and measure %TA by partial least squares regression (PLSR) technique. The spectra were pretreated with MSC pretreatment and it gave the optimal result for calibration model as (R = 0.92, RMSEC = 0.03%) and this model obtained high accuracy result to use for %TA prediction in test set as (R = 0.81, RMSEP = 0.05%). From the result of prediction in test set shown that the transmittance SW-NIR spectroscopy technique can be used for a non-destructive method for %TA prediction of tomatoes.

Keywords: tomato, quality, prediction, transmittance, titratable acidity, citric acid

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Authors: Camila da Silva, Simone Belorte de Andrade, Vitor Augusto dos Santos Garcia, Vladimir Ferreira Cabral, J. Vladimir Oliveira Lúcio Cardozo-Filho

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In the present study, the non-catalytic transesterification of soybean oil in continuous mode using supercritical ethanol were investigated. Experiments were performed in a packed-bed tubular reactor (PBTR) and variable studied were reaction temperature (523 K to 598 K), pressure (10 MPa to 20 MPa), oil to ethanol molar ratio (1:10 to 1:40) and water concentration (0 wt% to 10 wt% in ethanol). Results showed that ethyl esters yields obtained in the PBTR were higher (> 20 wt%) than those verified in a tubular reactor (TR), due to improved mass transfer conditions attained in the PBTR. Results demonstrated that temperature, pressure, oil to ethanol molar ratio and water concentration had a positive effect on fatty acid ethyl esters (FAEE) production in the experimental range investigated, with appreciable reaction yields (90 wt%) achieved at 598 K, 20 MPa, oil to ethanol molar ratio of 1:40 and 10 wt% of water concentration.

Keywords: packed bed reactor, ethyl esters, continuous process, catalyst-free process

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Authors: Mohammad Ali Karimi, Hossein Tavallali, Abdolhamid Hatefi-Mehrjardi

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Pollen extract of in vitro plants raised of Citrus aurantium as reducer and stabilizer was assessed for the green synthesis of silver nanoparticles (AgNPs). The synthesis of AgNPs was performed at room temperature assisting in solutions by reduction takes place rapidly for 10 min. Surface plasmon resonance (SPR) peaks in UV–Vis spectra indicated the formation of polydispersive AgNPs. Silver ions concentration, pH, temperature and reaction time were optimized in the synthesis of AgNPs. The nanoparticles obtained were characterized by UV-Vis spectrophotometer, transmission electron microscopy (TEM). X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy techniques. The synthesized AgNPs were mostly spherical in shape with an average size of 15 nm. XRD study shows that the AgNPs are crystalline in nature with face-centered cubic (fcc) geometry. It shows the significant antibacterial efficacy against Gram-positive (Staphylococcus aureus) and Gram-negative bacteria (Escherichia coli) by disk diffusion method using Mueller-Hinton Agar.

Keywords: green synthesis, Citrus aurantium, silver nanoparticles, antibacterial activity

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Authors: Stewart A. Keir, Faik A. Hamad

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This study aims to use both analytical and experimental methods of analysis to examine the accuracy of Computational Fluid Dynamics (CFD) models that can then be used for more complex analyses, accurately representing more elaborate flow phenomena such as internal shockwaves and boundary layers. The geometry used in the analytical study and CFD model is taken from the experimental rig. The analytical study is undertaken using isentropic and adiabatic relationships and the output of the analytical study, the 'shockwave location tool', is created. The results from the analytical study are then used to optimize the redesign an experimental rig for more favorable placement of pressure taps and gain a much better representation of the shockwaves occurring in the divergent section of the nozzle. The CFD model is then optimized through the selection of different parameters, e.g. turbulence models (Spalart-Almaras, Realizable k-epsilon & Standard k-omega) in order to develop an accurate, robust model. The results from the CFD model can then be directly compared to experimental and analytical results in order to gauge the accuracy of each method of analysis. The CFD model will be used to visualize the variation of various parameters such as velocity/Mach number, pressure and turbulence across the shock. The CFD results will be used to investigate the interaction between the shock wave and the boundary layer. The validated model can then be used to modify the nozzle designs which may offer better performance and ease of manufacture and may present feasible improvements to existing high-speed flow applications.

Keywords: CFD, nozzle, fluent, gas dynamics, shock-wave

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Authors: Alexandra-Veronica Luca, Letitia Petrescu

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Steel production is a major contributor to global warming potential. An average value of 1.83 tons of CO₂ is emitted for every ton of steel produced, resulting in over 3.3 Mt of CO₂ emissions each year. The present paper is focused on the investigation and comparison of two O₂ separation methods and two CO₂ capture technologies applicable to iron and steel industry. The O₂ used in steel production comes from an Air Separation Unit (ASU) using distillation or from air separation using membranes. The CO₂ capture technologies are represented by a two-stage membrane separation process and the gas-liquid absorption using methyl di-ethanol amine (MDEA). Process modelling and simulation tools, as well as environmental tools, are used in the present study. The production capacity of the steel mill is 4,000,000 tones/year. In order to compare the two CO₂ capture technologies in terms of efficiency, performance, and sustainability, the following cases have been investigated: Case 1: steel production using O₂ from ASU and no CO₂ capture; Case 2: steel production using O₂ from ASU and gas-liquid absorption for CO₂ capture; Case 3: steel production using O₂ from ASU and membranes for CO₂ capture; Case 4: steel production using O₂ from membrane separation method and gas-liquid absorption for CO₂ capture and Case-5: steel production using membranes for air separation and CO₂ capture. The O₂ separation rate obtained in the distillation technology was about 96%, and about 33% in the membrane technology. Similarly, the O₂ purity resulting in the conventional process (i.e. distillation) is higher compared to the O₂ purity obtained in the membrane unit (e.g., 99.50% vs. 73.66%). The air flow-rate required for membrane separation is about three times higher compared to the air flow-rate for cryogenic distillation (e.g., 549,096.93 kg/h vs. 189,743.82 kg/h). A CO₂ capture rate of 93.97% was obtained in the membrane case, while the CO₂ capture rate for the gas-liquid absorption was 89.97%. A quantity of 6,626.49 kg/h CO₂ with a purity of 95.45% is separated from the total 23,352.83 kg/h flue-gas in the membrane process, while with absorption of 6,173.94 kg/h CO₂ with a purity of 98.79% is obtained from 21,902.04 kg/h flue-gas and 156,041.80 kg/h MDEA is recycled. The simulation results, performed using ChemCAD process simulator software, lead to the conclusion that membrane-based technology can be a suitable alternative for CO₂ removal for steel production. An environmental evaluation using Life Cycle Assessment (LCA) methodology was also performed. Considering the electricity consumption, the performance, and environmental indicators, Case 3 can be considered the most effective. The environmental evaluation, performed using GaBi software, shows that membrane technology can lead to lower environmental emissions if membrane production is based on benzene derived from toluene hydrodealkilation and chlorine and sodium hydroxide are produced using mixed technologies.

Keywords: CO₂ capture, gas-liquid absorption, Life Cycle Assessment, membrane separation, steel production

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Authors: L. Gyansah, Yanfang Shen, Jiqiang Wang, Tianying Xiong

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SiCₚ/ pure Al composites with different SiC fractions (20 wt %, 30 wt %, and 40 wt %) were precisely cold sprayed, followed by hot axial-compression tests at deformation temperatures of 473 K to 673 K, leading to failure of specimens through routine crack propagation in their multiphase. The plastic deformation behaviour with respect to the SiCₚ contents and the deformation temperatures were studied at strain rate 1s-1.As-sprayed and post-failure specimens were analyzed by X-ray computed tomography (XCT), transmission electron microscopy (TEM), and scanning electron microscopy (SEM). Quasi-static thermomechanical testing results revealed that compressive strength (UTS = 228 MPa and 30.4 %) was the highest in the composites that was thermomechanically compressed at 473 K compared to those of the as-sprayed, while the as-sprayed exhibited a compressive strength of 182.8 MPa related to the increment in SiC fraction. Strength—plasticity synergy was promoted by dynamic recrystallization (DRX) through strengthening and refinement of the grains. The DRX degree depends relevantly on retainment of the uniformly ultrafine SiCₚ particulates, the pinning effects of the interfaces promoted by the ultrafine grain structures (UFG), and the higher deformation temperature. Reconstructed X-ray computed tomography data revealed different crack propagation mechanisms. A single-plane shear crack with multi-laminates fracture morphology yields relatively through the as-sprayed and as-deformed at 473 K deposits, while a multiphase plane shear cracks preeminently existed in high temperature deformed deposits resulting in multiphase-interface delaminations. Three pertinent strengthening mechanisms, videlicet, SiCp dispersed strengthening, refined grain strengthening, and dislocation strengthening, existed in the gradient microstructure, and their detailed contributions to the thermomechanical properties were discussed.

Keywords: cold spraying, hot deformation, deformation temperature, thermomechancal properties, SiC/Al composite

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Authors: Titanilla Komenda

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Human-machine-collaboration defines a direct interaction between humans and machines to fulfil specific tasks. Those so-called collaborative machines are used without fencing and interact with humans in predefined workspaces. Even though, human-machine-collaboration enables a flexible adaption to variable degrees of freedom, industrial applications are rarely found. The reasons for this are not technical progress but rather limitations in planning processes ensuring safety for operators. Until now, humans and machines were mainly considered separately in the planning process, focusing on ergonomics and system performance respectively. Within human-machine-collaboration, those aspects must not be seen in isolation from each other but rather need to be analysed in interaction. Furthermore, a simulation model is needed that can validate the system performance and ensure the safety for the operator at any given time. Following on from this, a holistic simulation model is presented, enabling a simulative representation of collaborative tasks – including both, humans and machines. The presented model does not only include a geometry and a motion model of interacting humans and machines but also a numerical behaviour model of humans as well as a Boole’s probabilistic sensor model. With this, error scenarios can be simulated by validating system behaviour in unplanned situations. As these models can be defined on the basis of Failure Mode and Effects Analysis as well as probabilities of errors, the implementation in a collaborative model is discussed and evaluated regarding limitations and simulation times. The functionality of the model is shown on industrial applications by comparing simulation results with video data. The analysis shows the impact of considering human factors in the planning process in contrast to only meeting system performance. In this sense, an optimisation function is presented that meets the trade-off between human and machine factors and aids in a successful and safe realisation of collaborative scenarios.

Keywords: human-machine-system, human-robot-collaboration, safety, simulation

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Authors: Amani Amamou, Sabra Habli, Nejla Mahjoub Saïd, Philippe Bournot, Georges Le Palec

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A counterflowing jet is a particular configuration of turbulent jets issuing into a moving ambient which has not carried much attention in literature compared with jet in a coflow or in a crossflow. This is due to the marked instability of the jet in a counterflow coupled with experimental and theoretical difficulties related to the flow inversion phenomenon. Nevertheless, jets in a counterflow are encountered in many engineering applications which required enhanced mixing as combustion, process and environmental engineering. In this work, we propose to investigate a round turbulent jet flowing into a uniform counterflow stream through a numerical approach. A hydrodynamic and thermal study of a slightly oblique round jets issuing into a uniform counterflow stream is carried out for different jet-to-counterflow velocity ratios ranging between 3.1 and 15. It is found that even a slight inclination of the jet in the vertical direction of the flow affects the structure and the velocity field of the counterflowing jet. In addition, the evolution of passive scalar temperature and pertinent length scales are presented at various velocity ratios, confirming that the flow is sensitive to directional perturbations.

Keywords: jet, counterflow, velocity, temperature, jet inclination

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Authors: Evelyn Marie Richmond, Andrew McBride, Chris Johnston, John Marley

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Background: Good quality patient information resources for orthognathic treatment help to reinforce information delivered during the initial consultation and help patients make informed decisions about their care. The Consultant Orthodontists and a Dental Core Trainee noted limited patient engagement with the British Orthodontic Society (BOS) 'Your Jaw Surgery' online resources and that the existing BOS patient information leaflet (PIL) could be customised and developed to meet local requirements. Aim: The quality improvement project (QIP) aimed to improve patients' understanding of orthognathic treatment by ensuring at least 90% of patients had read the new in-house patient information leaflet (PIL) and a minimum of 50% of patients had accessed the British Orthodontic Society (BOS) 'Your Jaw Surgery' online resources before attending the joint orthognathic multidisciplinary clinic by June 2023. Methods: The QIP was undertaken in the orthodontic department of the School of Dentistry, Belfast. Data was collected prospectively during a 6-month period from January 2023 to June 2023 over 3 Plan, Do, Study, Act (PDSA) cycles. Suitable patients were identified at consultant orthodontic new patient clinics. Following initial consultation for orthognathic treatment, patients were contacted to complete a patient questionnaire. Design: The change ideas were a poster with a QR code directing patients to the BOS 'Your Jaw Surgery' website in consultation areas and a new in-house PIL with a QR code directing patients to the BOS 'Your Jaw Surgery' website. Results: In PDSA cycle 1, 86.7% of patients were verbally directed to the BOS 'Your Jaw Surgery' website, and 53.3% accessed the online resources after their initial consultation. Although 100% of patients reported reading the existing PIL, only 64.3% felt it discussed the risks of orthognathic treatment in sufficient detail. By PDSA cycle 3, 100% of patients reported being directed to the BOS 'Your Jaw Surgery' website, however, only 58.3% engaged with the website. 100% of patients who read the new PIL felt that it discussed the risks of orthognathic treatment in sufficient detail. Conclusion: The slight improvement in access to the BOS 'Your Jaw Surgery' website shows that patients do not necessarily choose to access information online despite its availability. The uptake of the new PIL was greater than reported patient engagement with the BOS 'Your Jaw Surgery' website, which indicates patients still value written information despite the availability of online resources.

Keywords: orthognathic surgery, patient information resources, quality improvement project, risks

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Authors: Juan C. Duran-Alvarez, Daniel Mejia, Rodolfo Zanella

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Heterogeneous photocatalysis is a promising method to achieve the complete degradation and mineralization of organic pollutants in water via their exhaustive oxidation. In order to take this advanced oxidation process towards sustainability, it is necessary to reduce the energy consumption, referred as the light sources and the post-treatment operations. For this, the synthesis of new nanostructures of low band gap semiconductors in the form of thin films is in continuous development. In this work, thin films of the low band gap semiconductor bismuth oxyiodide (BiOI) were synthesized via the Successive Ionic Layer Adsorption and Reaction (SILAR) method. For this, Bi(NO3)3 and KI solutions were prepared, and glass supports were immersed in each solution under strict rate and time immersion conditions. Synthesis was performed at room temperature and a washing step was set prior to each immersion. Thin films with an average thickness below 100 nm were obtained upon a cycle of 30 immersions, as determined by AFM and profilometry measurements. Cubic BiOI nanocrystals with average size of 17 nm and a high orientation to the 001 plane were observed by XRD. In order to optimize the synthesis method, several Bi/I ratios were tested, namely 1/1, 1/5, 1/10, 1/20 and 1/50. The highest crystallinity of the BiOI films was observed when the 1/5 ratio was used in the synthesis. Non-stoichiometric conditions also resulted in the highest uniformity of the thin layers. PVP was used as an additive to improve the adherence of the BiOI thin films to the support. The addition of 0.1 mg/mL of PVP during the washing step resulted in the highest adherence of the thin films. In photocatalysis tests, degradation rate of the antibiotic ciprofloxacin as high as 75% was achieved using visible light (380 to 700 nm) irradiation for 5 h in batch tests. Mineralization of the antibiotic was also observed, although in a lower extent; ~ 30% of the total organic carbon was removed upon 5 h of visible light irradiation. Some ciprofloxacin by-products were identified throughout the reaction; and some of these molecules displayed residual antibiotic activity. In conclusion, it is possible to obtain highly oriented BiOI thin films under ambient conditions via the SILAR method. Non-stoichiometric conditions using PVP additive are necessary to increase the crystallinity and adherence of the films, which are photocatalytically active to remove recalcitrant organic pollutants under visible light irradiation.

Keywords: bismuth oxyhalides, photocatalysis, thin films, water treatment

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Authors: I. F. Ejim, F. L. Kamen

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Aims: In this experiment, algae oil extraction with a combination of n-hexane and ethanol was investigated. The effects of extraction solvent concentration, extraction time and temperature on the yield and quality of oil were studied using Response Surface Methodology (RSM). Experimental Design: Optimization of algae oil extraction using Box-Behnken design was used to generate 17 experimental runs in a three-factor-three-level design where oil yield, specific gravity, acid value and saponification value were evaluated as the response. Result: In this result, a minimum oil yield of 17% and maximum of 44% was realized. The optimum values for yield, specific gravity, acid value and saponification value from the overlay plot were 40.79%, 0.8788, 0.5056 mg KOH/g and 180.78 mg KOH/g respectively with desirability of 0.801. The maximum point prediction was yield 40.79% at solvent concentration 66.68 n-hexane, temperature of 40.0°C and extraction time of 4 hrs. Analysis of Variance (ANOVA) results showed that the linear and quadratic coefficient were all significant at p<0.05. The experiment was validated and results obtained were with the predicted values. Conclusion: Algae oil extraction was successfully optimized using RSM and its quality indicated it is suitable for many industrial uses.

Keywords: algae oil, response surface methodology, optimization, Box-Bohnken, extraction

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Authors: B. L. Avanthi Isaka, P. G. Ranjith

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The development of technically-sound enhanced geothermal systems (EGSs) is identified as a viable solution for world growing energy demand with immense potential, low carbon dioxide emission and importantly, as an environmentally friendly option for renewable energy production. The use of supercritical carbon dioxide (ScCO₂) as the working fluid in EGSs by replacing traditional water-based method is promising due to multiple advantages prevail in ScCO₂-injection for underground reservoir stimulation. The evolution of reservoir stimulation using ScCO₂ and the understanding of the flow behavior of a ScCO₂-stimulated geothermal reservoir is vital in applying ScCO₂-EGSs as a replacement for water-based EGSs. The study is therefore aimed to investigate the flow behavior of a ScCO₂-fractured rock medium at in-situ stress and temperature conditions. A series of permeability tests were conducted for ScCO₂ fractured Harcourt granite rock specimens at 90ºC, under varying confining pressures from 5–60 MPa using the high-pressure and high-temperature tri-axial set up which can simulate deep geological conditions. The permeability of the ScCO₂-fractured rock specimens was compared with that of water-fractured rock specimens. The results show that the permeability of the ScCO₂-fractured rock specimens is one order higher than that of water-fractured rock specimens and the permeability exhibits a non-linear reduction with increasing confining pressure due to the stress-induced fracture closure. Further, the enhanced permeability of the ScCO₂-induced fracture with multiple secondary branches was explained by exploring the CT images of the rock specimens. However, a single plain fracture was induced under water-based fracturing.

Keywords: supercritical carbon dioxide, fracture permeability, granite, enhanced geothermal systems

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Authors: Ali Raouli, Amin Chegenizadeh, Hamid Nikraz

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The Perth metropolitan area and its surrounding regions have been expanding rapidly in recent decades and it is expected that this growth will continue in the years to come. With this rapid growth and the resulting increase in population, consideration should be given to strategic planning and modelling for the future expansion of Perth. The accurate estimation of projected traffic volumes has always been a major concern for the transport modelers and planners. Development of a reliable strategic transport model depends significantly on the inputs data into the model and the calibrated parameters of the model to reflect the existing situation. Trip distribution is the second step in four-step modelling (FSM) which is complex due to its behavioral nature. Gravity model is the most common method for trip distribution. The spatial separation between the Origin and Destination (OD) zones will be reflected in gravity model by applying deterrence functions which provide an opportunity to include people’s behavior in choosing their destinations based on distance, time and cost of their journeys. Deterrence functions play an important role for distribution of the trips within a study area and would simulate the trip distances and therefore should be calibrated for any particular strategic transport model to correctly reflect the trip behavior within the modelling area. This paper aims to review the most common deterrence functions and propose a calibrated deterrence function for work trips within the Perth Metropolitan Area based on the information obtained from the latest available Household data and Perth and Region Travel Survey (PARTS) data. As part of this study, a four-step transport model using EMME software has been developed for Perth Metropolitan Area to assist with the analysis and findings.

Keywords: deterrence function, four-step modelling, origin destination, transport model

Procedia PDF Downloads 168

Authors: Ferdinando Montemari, Antonio Vitale, Nicola Genito, Giovanni Cuciniello

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: flapping dynamics, flight dynamics, system identification, tilt-rotor modeling and simulation

Procedia PDF Downloads 199

Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

Procedia PDF Downloads 33

Authors: Shangerganesh Lingeshwaran

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In this presentation, we have performed numerical simulations for a reaction-diffusion equation with various nonlinear density-dependent diffusion operators and proliferation functions. The mathematical model represented by parabolic partial differential equation is considered to study the invasion of gliomas (the most common type of brain tumors) and to describe the growth of cancer cells and response to their treatment. The unknown quantity of the given reaction-diffusion equation is the density of cancer cells and the mathematical model based on the proliferation and migration of glioma cells. A standard Galerkin finite element method is used to perform the numerical simulations of the given model. Finally, important observations on the each of nonlinear diffusion functions and proliferation functions are presented with the help of computational results.

Keywords: glioma invasion, nonlinear diffusion, reaction-diffusion, finite eleament method

Procedia PDF Downloads 233

Authors: Drew Fockler

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This research examines how to improve an employee’s experience when transferring between departments within an organization. This research includes a historical review of a Canadian retail organization. Based on this historical review, gaps are identified between current and future visions to show where problems with existing training and development practices need to be resolved to reduce front-line employee turnover within an organization. The strategies within this paper support leaders through the LEAD: Listen, Explore, Act and Develop, Change Management Model. The LEAD Change Management Model supports the change process. This research proposes three possible solutions to improve an employee who is transferring between departments. The best solution to resolve the problem of improving an employee moving between departments experience is creating a Training Manager position within the retail store. A Training Manager position could support both employees and leadership with training and development of staff who are moving between departments. Within this research, an implementation plan using the TransX Model was created. The TransX Model is a hybrid of Leader-Member Exchange Theory and Transformational Leadership Theory to facilitate this organizational change within an organization by creating a common vision. Finally, this research provides the next steps as well as future considerations to enhance the training manager role within an organization.

Keywords: employee transfers, employee engagement, human resources, employee induction, TransX model, lead change management model

Procedia PDF Downloads 77

Authors: Alibakhsh Kasaeian, Mohammad Sameti, Zahra Noori, Mona Rastgoo Bahambari

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Nowadays, the parabolic trough solar collector technology has become the most promising large-scale technology among various solar thermal generations. In this paper, a detailed numerical heat transfer model for a parabolic trough collector with nanofluid is presented based on the finite difference approach for which a MATLAB code was developed. The model was used to simulate the performance of a parabolic trough solar collector’s linear receiver, called a heat collector element (HCE). In this model, the heat collector element of the receiver was discretized into several segments in axial directions and energy balances were used for each control volume. All the heat transfer correlations, the thermodynamic equations and the optical properties were considered in details and the set of algebraic equations were solved simultaneously using iterative numerical solutions. The modeling assumptions and limitations are also discussed, along with recommendations for model improvement.

Keywords: heat transfer, nanofluid, numerical analysis, trough

Procedia PDF Downloads 372

Authors: Marcin Zielinski, Marcin Debowski, Paulina Rusanowska, Magda Dudek

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As a result of sonification, the destruction of complex biomass structures results in an increase in the biogas yield from the conditioned material. First, the amount of organic matter released into the solution due to disintegration was determined. This parameter was determined by changes in the carbon content in liquid phase of the conditioned substrate. The amount of carbon in the liquid phase increased with the prolongation of the sonication time to 16 min. Further increase in the duration of sonication did not cause a statistically significant increase in the amount of organic carbon in the liquid phase. The disintegrated material was then used for respirometric measurements for determination of the impact of the conditioning process used on methane fermentation effectiveness. The relationship between the amount of energy introduced into the lignocellulosic substrate and the amount of biogas produced has been demonstrated. Statistically significant increase in the amount of biogas was observed until sonication of 16 min. Further increase in energy in the conditioning process did not significantly increase the production of biogas from the treated substrate. The biogas production from the conditioned substrate was 17% higher than from the reference biomass at that time. The ultrasonic disintegration method did not significantly affect the observed biogas composition. In all series, the methane content in the produced biogas from the conditioned substrate was similar to that obtained with the raw substrate sample (51.1%). Another method of substrate conditioning was hydrothermal depolymerization. This method consists in application of increased temperature and pressure to substrate. These phenomena destroy the structure of the processed material, the release of organic compounds to the solution, which should lead to increase the amount of produced biogas from such treated biomass. The hydrothermal depolymerization was conducted using an innovative microwave heating method. Control measurements were performed using conventional heating. The obtained results indicate the relationship between depolymerization temperature and the amount of biogas. Statistically significant value of the biogas production coefficients increased as the depolymerization temperature increased to 150°C. Further raising the depolymerization temperature to 180°C did not significantly increase the amount of produced biogas in the respirometric tests. As a result of the hydrothermal depolymerization obtained using microwave at 150°C for 20 min, the rate of biogas production from the Sida silage was 780 L/kg VS, which accounted for nearly 50% increase compared to 370 L/kg VS obtained from the same silage but not depolymerised. The study showed that by microwave heating it is possible to effectively depolymerized substrate. Significant differences occurred especially in the temperature range of 130-150ºC. The pre-treatment of Sida hermaphrodita silage (biogas substrate) did not significantly affect the quality of the biogas produced. The methane concentration was about 51.5% on average. The study was carried out in the framework of the project under program BIOSTRATEG funded by the National Centre for Research and Development No. 1/270745/2/NCBR/2015 'Dietary, power, and economic potential of Sida hermaphrodita cultivation on fallow land'.

Keywords: disintegration, biogas, methane fermentation, Virginia fanpetals, biomass

Procedia PDF Downloads 310

Authors: T. Schmitt, J. Rosin, C. Butenweg

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Seismic design of buried pipeline systems for energy and water supply is not only important for plant and operational safety, but in particular for the maintenance of supply infrastructure after an earthquake. Past earthquakes have shown the vulnerability of pipeline systems. After the Kobe earthquake in Japan in 1995 for instance, in some regions the water supply was interrupted for almost two months. The present paper shows special issues of the seismic wave impacts on buried pipelines, describes calculation methods, proposes approaches and gives calculation examples. Buried pipelines are exposed to different effects of seismic impacts. This paper regards the effects of transient displacement differences and resulting tensions within the pipeline due to the wave propagation of the earthquake. Other effects are permanent displacements due to fault rupture displacements at the surface, soil liquefaction, landslides and seismic soil compaction. The presented model can also be used to calculate fault rupture induced displacements. Based on a three-dimensional Finite Element Model parameter studies are performed to show the influence of several parameters such as incoming wave angle, wave velocity, soil depth and selected displacement time histories. In the computer model, the interaction between the pipeline and the surrounding soil is modeled with non-linear soil springs. A propagating wave is simulated affecting the pipeline punctually independently in time and space. The resulting stresses mainly are caused by displacement differences of neighboring pipeline segments and by soil-structure interaction. The calculation examples focus on pipeline bends as the most critical parts. Special attention is given to the calculation of long-distance heat pipeline systems. Here, in regular distances expansion bends are arranged to ensure movements of the pipeline due to high temperature. Such expansion bends are usually designed with small bending radii, which in the event of an earthquake lead to high bending stresses at the cross-section of the pipeline. Therefore, Karman's elasticity factors, as well as the stress intensity factors for curved pipe sections, must be taken into account. The seismic verification of the pipeline for wave propagation in the soil can be achieved by observing normative strain criteria. Finally, an interpretation of the results and recommendations are given taking into account the most critical parameters.

Keywords: buried pipeline, earthquake, seismic impact, transient displacement

Procedia PDF Downloads 187