Search results for: H₂-optimal model reduction

Authors: Rajesh Kumar Meena, Suman Jhajharia, Goutam Chakraborty

Abstract:

Plasmonic silver nanoparticles (Ag NPs) was synthesized by chemical reduction method using Trachyspermum Ammi (TA, Ajwain) seeds extract in aqueous medium and AgNO3 solution at different time interval. Reaction time, and concentration of AgNO3 and TA could accelerate the reduction rate of Ag+ and affect AgNPs size and concentration of NPs. Surface plasmon resonance band centered at 420-430 nm (88.78nm) was recognised as first exitonic peak of UV-Vis absorption spectra of AgNPs that used to calculate the particle size (10-30 nm). FTIR results TA supported AgNPs showed decrease in intensity of peaks at 3394, 1716 and 1618 cm-1 with respect to the plain TA indicating the involvement of O-H, carbonyl group and C=C stretching in formation of TA-AgNPs aggregates. The C-O-C and C-N stretching suggested the presence of many phytochemicals on the surface of the NPs. Impedance study reveals that at low concentration of TA the rate of charge transfer is in TA-AgNPs aggregates, found higher than the higher TA concentration condition that confirms the stability of AgNPs in water. Extract reduce silver ions into silver nanoparticles (NPs) of size 6-50nm. Pronounce effect of the time on Ag NPs concentration and particle size, was exhibited by the system These biogenic Ag NPs are characterized using UV- Vis spectrophotometry (UV-Visible), Fourier transformation infrared (FTIR) and XRD. These studies give us inside view of the most probable mechanism of biosynthesis and optoelectronic properties of the as synthesised Ag NPs.

Keywords: antimicrobial activity, bioreduction, capping agent, silver nanoparticles

Procedia PDF Downloads 326

Authors: Ayoub. El Bourtali, Abdessamed.Najine, Amrou Moussa. Benmoussa

Abstract:

One of the main goals of river engineering is river training, which is defined as controlling and predicting the behavior of a river. It is taking effective measurements to eliminate all related risks and thus improve the river system. In some rivers, the riverbed continues to erode and degrade; therefore, equilibrium will never be reached. Generally, river geometric characteristics and riverbed erosion analysis are some of the most complex but critical topics in river engineering and sediment hydraulics; riverbank erosion is the second answering process in hydrodynamics, which has a major impact on the ecological chain and socio-economic process. This study aims to integrate the new computer technology that can analyze erosion and hydraulic problems through computer simulation and modeling. Choosing the right model remains a difficult and sensitive job for field engineers. This paper makes use of the 5.0.4 version of the HEC-RAS model. The river section is adopted according to the gauged station and the proximity of the adjustment. In this work, we will demonstrate how 2D hydraulic modeling helped clarify the design and cover visuals to set up depth and velocities at riverbanks and throughout advanced structures. The hydrologic engineering center's-river analysis system (HEC-RAS) 2D model was used to create a hydraulic study of the erosion model. The geometric data were generated from the 12.5-meter x 12.5-meter resolution digital elevation model. In addition to showing eroded or overturned river sections, the model output also shows patterns of riverbank changes, which can help us reduce problems caused by erosion.

Keywords: 2D hydraulics model, erosion, floodplain, hydrodynamic, HEC-RAS, riverbed erosion, river morphology, resolution digital data, sediment

Procedia PDF Downloads 189

Authors: H. Jeries, N. Volkova, C. G. Iglesias, M. Najjar, M. Rosenblat, M. Aviram, T. Hayek

Abstract:

Background: Synthetic forms of glucocorticoids (e.g., prednisone, prednisolone) are anti-inflammatory drugs which are widely used in clinical practice. The role of glucocorticoids (GCs) in cardiovascular diseases including atherosclerosis is highly controversial, and their impact on macrophage foam cell formation is still unknown. Our aim was to investigate the effects of prednisone or its active metabolite, prednisolone, on macrophage oxidative stress and lipid metabolism using in-vivo, ex-vivo and in-vitro systems. Methods: The in-vivo study included C57BL/6 mice which were intraperitoneally injected with prednisone or prednisolone (5mg/kg) for 4 weeks, followed by lipid metabolism analyses in the mice aorta, and in peritoneal macrophages (MPM). In the ex-vivo study, we analyzed the effect of serum samples obtained from 9 healthy volunteers before or after treatment with oral prednisone (20mg for 5 days), on J774A.1 macrophage atherogenicity. In-vitro studies were conducted using J774A.1 macrophages, human monocyte derived macrophages (HMDM) and fibroblasts. Cells were incubated with increasing concentrations (0-200 ng/ml) of prednisone or prednisolone, followed by determination of cellular oxidative status, triglyceride and cholesterol metabolism. Results: Prednisone or prednisolone treatment resulted in a significant reduction in triglycerides and mainly in cholesterol cellular accumulation in MPM or in J774A.1 macrophages incubated with human serum. Similar resulted were noted in HMDM or in J774A.1 macrophages which were directly incubated with the GCs. These effects were associated with GCs inhibitory effect on triglycerides and cholesterol biosynthesis rates, throughout downregulation of diacylglycerol acyltransferase1 (DGAT1) expression, and of the sterol regulatory element binding protein (SREBP2) and HMGCR expression, respectively. In parallel to prednisone or prednisolone induced reduction in macrophage triglyceride content, paraoxonase 2 (PON2) expression was significantly upregulated. GCs-induced reduction of cellular triglyceride and cholesterol mass was mediated by the GCs receptors on macrophages since the GCs receptor antagonist (RU 486) abolished these effects. In fibroblasts, unlike macrophages, prednisone or prednisolone showed no anti-atherogenic effects. Conclusions: Prednisone or prednisolone are anti-atherogenic since they protected macrophages from lipid accumulation and foam cell formation.

Keywords: atherosclerosis, cholesterol, foam cell, macrophage, prednisone, prednisolone, triglycerides

Procedia PDF Downloads 145

Authors: Enva Doda

Abstract:

Recent statistical analyses within the European Union (EU) underscore the enduring significance of the Gender Pay Gap in amplifying the Gender Pension Gap, a phenomenon resisting proportional reduction over time. This study meticulously calculates the Pension Gap, scrutinizing contributing variables within diverse pension systems. Furthermore, it investigates whether the "unexplained" segment of the Gender Gap correlates with political institutions, economic systems, historical events, or discrimination, utilizing quantitative methods and the Blinder-Oaxaca Decomposition Method to pinpoint potential discriminatory factors. The descriptive analysis reveals a conspicuous Gender Pension Gap across European nations, displaying notable variation. While an overall reduction in the Gender Gap is observed, the degree of improvement varies among countries. Subsequent analyses will delve into the specific reasons or variables influencing distinct Gender Gap percentages, forming the basis for nuanced policy recommendations. This comprehensive research enriches the ongoing discourse on gender equality and economic equity. By focusing on the root causes of the Pension Gap, the study has the potential to instigate policy adjustments, urging policymakers to reassess systemic structures and contribute to informed decision-making. Emphasizing gender equality as essential for a flourishing and resilient economy, the research aspires to drive positive change on academic and policy fronts.

Keywords: blinder Oaxaca decomposition method, discrimination, gender pension gap, quantitative methods, unexplained gender gap

Procedia PDF Downloads 43

Authors: S. Gao, S. Srirattayawong

Abstract:

In this study, a computational fluid dynamics (CFD) model has been developed for studying the effect of surface roughness profile on the EHL problem. The cylinders contact geometry, meshing and calculation of the conservation of mass and momentum equations are carried out by using the commercial software packages ICEMCFD and ANSYS Fluent. The user defined functions (UDFs) for density, viscosity and elastic deformation of the cylinders as the functions of pressure and temperature have been defined for the CFD model. Three different surface roughness profiles are created and incorporated into the CFD model. It is found that the developed CFD model can predict the characteristics of fluid flow and heat transfer in the EHL problem, including the leading parameters such as the pressure distribution, minimal film thickness, viscosity, and density changes. The obtained results show that the pressure profile at the center of the contact area directly relates to the roughness amplitude. The rough surface with kurtosis value over 3 influences the fluctuated shape of pressure distribution higher than other cases.

Keywords: CFD, EHL, kurtosis, surface roughness

Procedia PDF Downloads 320

Authors: Mende Mensa Sorato, Majid Davari, Abbas Kebriaeezadeh, Nizal Sarrafzadegan, Tamiru Shibru, Behzad Fatemi

Abstract:

Markov model, like cardiovascular disease (CVD) policy model based simulation, is being used for evaluating the cost-effectiveness of hypertension treatment. Stroke, angina, myocardial infarction (MI), cardiac arrest, and all-cause mortality were included in this model. Hypertension is a risk factor for a number of vascular and cardiac complications and CVD outcomes. Objective: This systematic review was conducted to evaluate the comprehensiveness of this model across different regions globally. Methods: We searched articles written in the English language from PubMed/Medline, Ovid/Medline, Embase, Scopus, Web of Science, and Google scholar with a systematic search query. Results: Thirteen cohort studies involving a total of 2,165,770 (1,666,554 hypertensive adult population and 499,226 adults with treatment-resistant hypertension) were included in this scoping review. Hypertension is clearly associated with coronary heart disease (CHD) and stroke mortality, unstable angina, stable angina, MI, heart failure (HF), sudden cardiac death, transient ischemic attack, ischemic stroke, subarachnoid hemorrhage, intracranial hemorrhage, peripheral arterial disease (PAD), and abdominal aortic aneurism (AAA). Association between HF and hypertension is variable across regions. Treatment resistant hypertension is associated with a higher relative risk of developing major cardiovascular events and all-cause mortality when compared with non-resistant hypertension. However, it is not included in the previous CVD policy model. Conclusion: The CVD policy model used can be used in most regions for the evaluation of the cost-effectiveness of hypertension treatment. However, hypertension is highly associated with HF in Latin America, the Caribbean, Eastern Europe, and Sub-Saharan Africa. Therefore, it is important to consider HF in the CVD policy model for evaluating the cost-effectiveness of hypertension treatment in these regions. We do not suggest the inclusion of PAD and AAA in the CVD policy model for evaluating the cost-effectiveness of hypertension treatment due to a lack of sufficient evidence. Researchers should consider the effect of treatment-resistant hypertension either by including it in the basic model or during setting the model assumptions.

Keywords: cardiovascular disease policy model, cost-effectiveness analysis, hypertension, systematic review, twelve major cardiovascular events

Procedia PDF Downloads 71

Authors: Thor Alexis Sazon, Alexander Guzman-Urbina, Yasuhiro Fukushima

Abstract:

This study outlines the method of how to develop a surrogate life cycle model based on fuzzy logic using three fuzzy inference methods: (1) the conventional Fuzzy Inference System (FIS), (2) the hybrid system of Data Analytics and Fuzzy Inference (DAFIS), which uses data clustering for defining the membership functions, and (3) the Adaptive-Neuro Fuzzy Inference System (ANFIS), a combination of fuzzy inference and artificial neural network. These methods were demonstrated with a case study where the Global Warming Potential (GWP) and the Levelized Cost of Energy (LCOE) of solar photovoltaic (PV) were estimated using Solar Irradiation, Module Efficiency, and Performance Ratio as inputs. The effects of using different fuzzy inference types, either Sugeno- or Mamdani-type, and of changing the number of input membership functions to the error between the calibration data and the model-generated outputs were also illustrated. The solution spaces of the three methods were consequently examined with a sensitivity analysis. ANFIS exhibited the lowest error while DAFIS gave slightly lower errors compared to FIS. Increasing the number of input membership functions helped with error reduction in some cases but, at times, resulted in the opposite. Sugeno-type models gave errors that are slightly lower than those of the Mamdani-type. While ANFIS is superior in terms of error minimization, it could generate solutions that are questionable, i.e. the negative GWP values of the Solar PV system when the inputs were all at the upper end of their range. This shows that the applicability of the ANFIS models highly depends on the range of cases at which it was calibrated. FIS and DAFIS generated more intuitive trends in the sensitivity runs. DAFIS demonstrated an optimal design point wherein increasing the input values does not improve the GWP and LCOE anymore. In the absence of data that could be used for calibration, conventional FIS presents a knowledge-based model that could be used for prediction. In the PV case study, conventional FIS generated errors that are just slightly higher than those of DAFIS. The inherent complexity of a Life Cycle study often hinders its widespread use in the industry and policy-making sectors. While the methodology does not guarantee a more accurate result compared to those generated by the Life Cycle Methodology, it does provide a relatively simpler way of generating knowledge- and data-based estimates that could be used during the initial design of a system.

Keywords: solar photovoltaic, fuzzy logic, inference system, artificial neural networks

Procedia PDF Downloads 164

Authors: Shyamlal Kumawat

Abstract:

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

Procedia PDF Downloads 330

Authors: Trapti Sharma, Devesh Kumar Srivastava

Abstract:

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

Procedia PDF Downloads 369

Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

Abstract:

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

Abstract:

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

Procedia PDF Downloads 424

Authors: Moses Aron, Elias Mwakilama, Jimmy Namangale

Abstract:

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

Procedia PDF Downloads 435

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

Abstract:

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

Procedia PDF Downloads 116

Authors: Anshul Ashu

Abstract:

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

Procedia PDF Downloads 500

Authors: Masoud Ghermezi

Abstract:

Studying the sheet metals is one of the most important research areas in the field of metal forming due to their extensive applications in the aerospace industries. A useful method for determining the forming limit of these materials and consequently preventing the rupture of sheet metals during the forming process is the use of the forming limit curve (FLC). In addition to specifying the forming limit, this curve also delineates a boundary for the allowed values of strain in sheet metal forming; these characteristics of the FLC along with its accuracy of computation and wide range of applications have made this curve the basis of research in the present paper. This study presents a new model that not only agrees with the results obtained from the above mentioned theory, but also eliminates its shortcomings. In this theory, like in the M-K theory, a thin sheet with an inhomogeneity as a gradient thickness reduction with a sinusoidal function has been chosen and subjected to two-dimensional stress. Through analytical evaluation, ultimately, a governing differential equation has been obtained. The numerical solution of this equation for the range of positive strains (stretched region) yields the results that agree with the results obtained from M-K theory. Also the solution of this equation for the range of negative strains (tension region) completes the FLC curve. The findings obtained by applying this equation on two alloys with the hardening exponents of 0.4 and 0.24 indicate the validity of the presented equation.

Keywords: sheet metal, metal forming, forming limit curve (FLC), M-K theory

Procedia PDF Downloads 365

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

Abstract:

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

Procedia PDF Downloads 99

Authors: Masahiro Suzuki, Nobuyuki Okura

Abstract:

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 236

Authors: K. Petcharaporn, S. Kumchoo

Abstract:

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

Procedia PDF Downloads 273

Authors: Stewart A. Keir, Faik A. Hamad

Abstract:

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

Procedia PDF Downloads 233

Authors: Titanilla Komenda

Abstract:

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

Procedia PDF Downloads 361

Authors: Zichao Zhang, Yifan Zhao, Samuel Court

Abstract:

The carbon emission problem of the traditional construction industry has long been a pressing issue. With the growing emphasis on environmental protection and advancement of science and technology, the organic integration of digital technology and emission reduction has gradually become a mainstream solution. Among various sophisticated digital technologies, digital twins, which involve creating virtual replicas of physical systems or objects, have gained enormous attention in recent years as tools to improve productivity, optimize management and reduce carbon emissions. However, the relatively high implementation costs including finances, time, and manpower associated with digital twins have limited their widespread adoption. As a result, most of the current applications are primarily concentrated within a few industries. In addition, the creation of digital twins relies on a large amount of data and requires designers to possess exceptional skills in information collection, organization, and analysis. Unfortunately, these capabilities are often lacking in the traditional construction industry. Furthermore, as a relatively new concept, digital twins have different expressions and usage methods across different industries. This lack of standardized practices poses a challenge in creating a high-quality digital twin framework for construction. This paper firstly reviews the current academic studies and industrial practices focused on reducing greenhouse gas emissions in the construction industry using digital twins. Additionally, it identifies the challenges that may be encountered during the design and implementation of a digital twin framework specific to this industry and proposes potential directions for future research. This study shows that digital twins possess substantial potential and significance in enhancing the working environment within the traditional construction industry, particularly in their ability to support decision-making processes. It proves that digital twins can improve the work efficiency and energy utilization of related machinery while helping this industry save energy and reduce emissions. This work will help scholars in this field to better understand the relationship between digital twins and energy conservation and emission reduction, and it also serves as a conceptual reference for practitioners to implement related technologies.

Keywords: digital twins, emission reduction, construction industry, energy saving, life cycle, sustainability

Procedia PDF Downloads 101

Authors: Maryam Kiani

Abstract:

This study focuses on the development of composite nanomaterials based on SiO2 and carbon black for oxygen reduction reaction (ORR) electrocatalysts in batteries and fuel cells. The aim was to explore the potential of these composite materials as efficient catalysts for ORR, which is a critical process in energy conversion devices. The SiO2/carbon black composite nanomaterials were synthesized using a facile and scalable method. The morphology, structure, and electrochemical properties of the materials were characterized using various techniques, including scanning electron microscopy (SEM), X-ray diffraction (XRD), and electrochemical measurements. The results demonstrated that the incorporation of SiO2 into the carbon black matrix enhanced the ORR performance of the composite material. The composite nanomaterials exhibited improved electrocatalytic activity, enhanced stability, and increased durability compared to pure carbon black. The presence of SiO2 facilitated the formation of active sites, improved electron transfer, and increased the surface area available for ORR. This study contributes to the advancement of battery and fuel cell technology by offering a promising approach for the development of high-performance ORR electrocatalysts. The SiO2/carbon black composite nanomaterials show great potential for improving the efficiency and durability of energy conversion devices, leading to more sustainable and efficient energy solutions.

Keywords: oxygen reduction reaction, batteries, fuel cells, electrrocatalyst

Procedia PDF Downloads 117

Authors: Ghada Al-Kafaji, Mohamed Sabry

Abstract:

Mitochondria are the site of cellular respiration and produce energy in the form of adenosine triphosphate (ATP) via oxidative phosphorylation. They are the major source of intracellular reactive oxygen species (ROS) and are also direct target to ROS attack. Oxidative stress and ROS-mediated disruptions of mitochondrial function are major components involved in the pathogenicity of diabetic complications. In this work, the changes in mitochondrial DNA (mtDNA) copy number, biogenesis, gene expression of mtDNA-encoded subunits of electron transport chain (ETC) complexes, and mitochondrial function in response to hyperglycemia-induced ROS and the effect of direct inhibition of ROS on mitochondria were investigated in an in vitro model of diabetic nephropathy using human renal mesangial cells. The cells were exposed to normoglycemic and hyperglycemic conditions in the presence and absence of Mn(III)tetrakis(4-benzoic acid) porphyrin chloride (MnTBAP) or catalase for 1, 4 and 7 days. ROS production was assessed by the confocal microscope and flow cytometry. mtDNA copy number and PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 transcripts, were all analyzed by real-time PCR. PGC-1a, NRF-1, and TFAM, as well as ND2, CYTB, COI, and ATPase 6 proteins, were analyzed by Western blotting. Mitochondrial function was determined by assessing mitochondrial membrane potential and adenosine triphosphate (ATP) levels. Hyperglycemia-induced a significant increase in the production of mitochondrial superoxide and hydrogen peroxide at day 1 (P < 0.05), and this increase remained significantly elevated at days 4 and 7 (P < 0.05). The copy number of mtDNA and expression of PGC-1a, NRF-1, and TFAM as well as ND2, CYTB, CO1 and ATPase 6 increased after one day of hyperglycemia (P < 0.05), with a significant reduction in all those parameters at 4 and 7 days (P < 0.05). The mitochondrial membrane potential decreased progressively at 1 to 7 days of hyperglycemia with the parallel progressive reduction in ATP levels over time (P < 0.05). MnTBAP and catalase treatment of cells cultured under hyperglycemic conditions attenuated ROS production reversed renal mitochondrial oxidative stress and improved mtDNA, mitochondrial biogenesis, and function. These results show that hyperglycemia-induced ROS caused an early increase in mtDNA copy number, mitochondrial biogenesis and mtDNA-encoded gene expression of the ETC subunits in human mesangial cells as a compensatory response to the decline in mitochondrial function, which precede the mtDNA defect and mitochondrial dysfunction with a progressive oxidative response. Protection from ROS-mediated damage to renal mitochondria induced by hyperglycemia may be a novel therapeutic approach for the prevention/treatment of DN.

Keywords: diabetic nephropathy, hyperglycemia, reactive oxygen species, oxidative stress, mtDNA, mitochondrial dysfunction, manganese superoxide dismutase, catalase

Procedia PDF Downloads 247

Authors: Ali Raouli, Amin Chegenizadeh, Hamid Nikraz

Abstract:

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

Abstract:

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: Yuri Boiko, Ci Lin, Iluju Kiringa, Tet Yeap

Abstract:

The performance of a BLDC motor controlled by the Kalman filter-based position-sensorless drive is studied in terms of its dependence on the system’s parameters' variations. The effects of system’s parameters changes on the dynamic behavior of state variables are verified. Simulated is a closed-loop control scheme with a Kalman filter in the feedback line. Distinguished are two separate data sampling modes in analyzing feedback output from the BLDC motor: (1) equal angular separation and (2) equal time intervals. In case (1), the data are collected via equal intervals Δθ of rotor’s angular position θᵢ, i.e., keeping Δθ=const. In case (2), the data collection time points tᵢ are separated by equal sampling time intervals Δt=const. Demonstrated are the effects of the parameters changes on the sensorless control flow, in particular, reduction of the torque ripples, switching spikes, torque load balancing. It is specifically shown that an efficient suppression of commutation induced torque ripples is achievable selection of the sampling rate in the Kalman filter settings above certain critical value. The computational cost of such suppression is shown to be higher for the motors with lower induction values of the windings.

Keywords: BLDC motor, Kalman filter, sensorless drive, state variables, torque ripples reduction, sampling rate

Procedia PDF Downloads 148

Authors: Li Chin Law, Epaminondas Mastorakos, Mohd Roslee Othman, Antonis Trakakis

Abstract:

The paper introduces an alternative concept of carbon capture for shipping by using pre-combustion carbon capture technology (Pre-CCS), which was proven to be less energy intensive than post-combustion carbon capture from the engine exhaust. Energy assessment on amine-based post-combustion CCS on LNG-fuelled ships showed that the energy efficiency of CCS ships reduced from 48% to 36.6%. Then, an energy assessment was carried out to compare the power and heat requirements of the most used hydrogen production methods and carbon capture technologies. Steam methane reformer (SMR) was found to be 20% more energy efficient and achieved a higher methane conversion than auto thermal reaction and methane decomposition. Next, pressure swing adsorber (PSA) has shown a lower energy requirement than membrane separation, cryogenic separation, and amine absorption in pre-combustion carbon capture. Hence, an integrated system combining SMR and PSA (SMR-PSA) with waste heat integration (WHR) was proposed. This optimized SMR-based integrated system has achieved 65% of CO₂ reduction with less than 7-percentage point of energy penalty (41.7% of energy efficiency). Further integration of post-combustion CCS with the SMR-PSA integrated system improved carbon capture rate to 86.3% with 9-percentage points of energy penalty (39% energy efficiency). The proposed system was shown to be able to meet the carbon reduction targets set by International Maritime Organization (IMO) with certain energy penalties.

Keywords: shipping, decarbonisation, alternative fuels, low carbon, hydrogen, carbon capture

Procedia PDF Downloads 78

Authors: Shangerganesh Lingeshwaran

Abstract:

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 232

Authors: Drew Fockler

Abstract:

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: Debabrata Das, Preeti Mishra

Abstract:

A two-phase anaerobic process combining biohydrogen followed by biomethane (biohythane technology) serves as an environment-friendly and economically sustainable approach for the improved valorization of organic wastes. Suitability of the pure cultures like Klebsiela pneumonia, C. freundii, B. coagulan, etc. and mixed acidogenic cultures for the biohydrogen production was already studied. The characteristics of organic wastes play a critical role in biohydrogen production. The choice of an appropriate combination of complementary organic wastes can vastly improve the bioenergy generation besides achieving the significant cost reduction. Suitability and economic viability of using the groundnut deoiled cake (GDOC), mustard deoiled cake (MDOC), distillers’ dried grain with soluble (DDGS) and algal biomass (AB) as a co-substrate were studied for a biohythane production. Results show that maximum gaseous energy of 20.7, 9.3, 16.7 and 15.6 % was recovered using GDOC, MDOC, DDGS and AB in the two stage biohythane production, respectively. Both GDOC and DDGS were found to be better co-substrates as compared to MDOC and AB in terms of hythane production, respectively. The maximum cumulative hydrogen and methane production of 150 and 64 mmol/L were achieved using GDOC. Further, 98 % reduction in substrate input cost (SIC) was achieved using the co-supplementation procedure.

Keywords: Biohythane, algal biomass, distillers’ dried grain with soluble (DDGS), groundnut deoiled cake (GDOC), mustard deoiled cake (MDOC)

Procedia PDF Downloads 200