Search results for: seismic prediction equations

Authors: Yeaji Seok, Myung Kyung Lee

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Background: Even if patients survive after a stroke, stroke patients may experience disability in mobility, sensation, cognition, and speech and language. Stroke patients require rehabilitation for functional recovery and daily life for a considerable time. During rehabilitation, the role of caregivers is important. However, the stroke patients’ quality of life may deteriorate due to family caregivers’ non-preparedness and increased role burden. Purpose: To investigate the prediction of caregivers' preparedness and role burden on stroke patients’ quality of life. Methods: The target population was stroke patients who were hospitalized for rehabilitation and their family care providers. A total of 153 patient-family caregiver dyads were recruited from June to August 2021. Data were collected from self-reported questionnaires and analyzed using descriptive statistics, t-tests, chi-squared test, one-way analysis of variance, Pearson’s correlation coefficients, and multiple regression with SPSS statistics 28 programs. Results: Family caregivers’ preparedness affected stroke patients’ mobility (β = .20, p < 0.05) and character (β = -.084, p < 0.05) and production activities (β = -.197, p < 0.05) in quality of life. The role burden of family caregivers affected language skills (β = .310, p<0.05), visual functions (β=-.357, p < 0.05), thinking skills (β = 0.443, p = 0.05), mood conditions (β = 0.565, p < 0.001), family roles (β = -0.361, p < 0.001), and social roles (β = -0.304, p < 0.001), while the caregivers’ burden of performing self-protection negatively affected patients’ social roles (β = .180, p=.048). In addition, caregivers’ role burden of personal life sacrifice affected patients’ mobility (β = .311, p < 0.05), self-care (β =.232, p < 0.05) and energy (β = .239, p < 0.05). Conclusion: This study indicated that family caregivers' preparedness and role burden affected stroke patients’ quality of life. The results of this study suggested that intervention to improve family caregivers’ preparedness and to reduce role burden should be required for quality of life in stroke patients.

Keywords: quality of life, preparedness, role burden, caregivers, stroke

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Authors: Suwapitch Chalongkulasak, Teerasak E-Kobon, Pramote Chumnanpuen

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Acne vulgaris is a common skin disease mainly caused by the Gram–positive pathogenic bacterium, Propionibacterium acnes. This bacterium stimulates inflammation process in human sebaceous glands. Giant African snail (Achatina fulica) is alien species that rapidly reproduces and seriously damages agricultural products in Thailand. There were several research reports on the medical and pharmaceutical benefits of this snail mucus peptides and proteins. This study aimed to in silico predict multifunctional bioactive peptides from A. fulica mucus peptidome using several bioinformatic tools for determination of antimicrobial (iAMPpred), anti–biofilm (dPABBs), cytotoxic (Toxinpred), cell membrane penetrating (CPPpred) and anti–quorum sensing (QSPpred) peptides. Three candidate peptides with the highest predictive score were selected and re-designed/modified to improve the required activities. Structural and physicochemical properties of six anti–P. acnes (APA) peptide candidates were performed by PEP–FOLD3 program and the five aforementioned tools. All candidates had random coiled structure and were named as APA1–ori, APA2–ori, APA3–ori, APA1–mod, APA2–mod and APA3–mod. To validate the APA activity, these peptide candidates were synthesized and tested against six isolates of P. acnes. The modified APA peptides showed high APA activity on some isolates. Therefore, our biomimetic mucus peptides could be useful for preventing acne vulgaris and further examined on other activities important to medical and pharmaceutical applications.

Keywords: Propionibacterium acnes, Achatina fulica, peptidomes, antibacterial peptides, snail mucus

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Authors: Behrang Tavousi Tehrani, Mohammad-Zaman Kabir

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Shape memory alloys (SMA) are often implemented in smart structures as the active components. Their ability to recover large displacements has been used in many applications, including structural stability/response enhancement and active structural acoustic control. SMA wires or fibers can be embedded with composite cylinders to increase their critical buckling load, improve their load-deflection behavior, and reduce the radial deflections under various thermo-mechanical loadings. This paper presents a semi-analytical investigation on the non-linear load-deflection response of SMA-reinforced composite circular cylindrical shells. The cylinder shells are under uniform external pressure load. Based on first-order shear deformation shell theory (FSDT), the equilibrium equations of the structure are derived. One-dimensional simplified Brinson’s model is used for determining the SMA recovery force due to its simplicity and accuracy. Airy stress function and Galerkin technique are used to obtain non-linear load-deflection curves. The results are verified by comparing them with those in the literature. Several parametric studies are conducted in order to investigate the effect of SMA volume fraction, SMA pre-strain value, and SMA activation temperature on the response of the structure. It is shown that suitable usage of SMA wires results in a considerable enhancement in the load-deflection response of the shell due to the generation of the SMA tensile recovery force.

Keywords: airy stress function, cylindrical shell, Galerkin technique, load-deflection curve, recovery stress, shape memory alloy

Procedia PDF Downloads 187

Authors: Bernard Igoche Igoche, Olumuyiwa Matthew, Peter Bednar, Alexander Gegov

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This study presents an ontology-driven approach for knowledge discovery and validation from admission databases in Nigerian polytechnic institutions. The research aims to address the challenges of extracting meaningful insights from vast amounts of admission data and utilizing them for decision-making and process improvement. The proposed methodology combines the knowledge discovery in databases (KDD) process with a structural causal model (SCM) ontological framework. The admission database of Benue State Polytechnic Ugbokolo (Benpoly) is used as a case study. The KDD process is employed to mine and distill knowledge from the database, while the SCM ontology is designed to identify and validate the important features of the admission process. The SCM validation is performed using the conditional independence test (CIT) criteria, and an algorithm is developed to implement the validation process. The identified features are then used for machine learning (ML) modeling and prediction of admission status. The results demonstrate the adequacy of the SCM ontological framework in representing the admission process and the high predictive accuracies achieved by the ML models, with k-nearest neighbors (KNN) and support vector machine (SVM) achieving 92% accuracy. The study concludes that the proposed ontology-driven approach contributes to the advancement of educational data mining and provides a foundation for future research in this domain.

Keywords: admission databases, educational data mining, machine learning, ontology-driven knowledge discovery, polytechnic education, structural causal model

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Authors: Rupam Saikia, Ashim Kanti Dey

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Sonapur is an intense hilly region on the border of Assam and Meghalaya lying in North-East India and is very near to a seismic fault named as Dauki besides which makes the region seismically active. Besides, these recently two earthquakes of magnitude 6.7 and 6.9 have struck North-East India in January and April 2016. Also, the slope concerned for this study is adjacent to NH 44 which for a long time has been a sole important connecting link to the states of Manipur and Mizoram along with some parts of Assam and so has been a cause of considerable loss to life and property since past decades as there has been several recorded incidents of landslide, road-blocks, etc. mostly during the rainy season which comes into news. Based on this issue this paper reports a static and dynamic slope stability analysis of Sonapur which has been carried out in MIDAS GTS NX. The slope being highly unreachable due to terrain and thick vegetation in-situ test was not feasible considering the current scope available so disturbed soil sample was collected from the site for the determination of strength parameters. The strength parameters were so determined for varying relative density with further variation in water content. The slopes were analyzed considering plane strain condition for three slope heights of 5 m, 10 m and 20 m which were then further categorized based on slope angles 30, 40, 50, 60, and 70 considering the possible extent of steepness. Initially static analysis under dry state was performed then considering the worst case that can develop during rainy season the slopes were analyzed for fully saturated condition along with partial degree of saturation with an increase in the waterfront. Furthermore, dynamic analysis was performed considering the El-Centro Earthquake which had a magnitude of 6.7 and peak ground acceleration of 0.3569g at 2.14 sec for the slope which were found to be safe during static analysis under both dry and fully saturated condition. Some of the conclusions were slopes with inclination above 40 onwards were found to be highly vulnerable for slopes of height 10 m and above even under dry static condition. Maximum horizontal displacement showed an exponential increase with an increase in inclination from 30 to 70. The vulnerability of the slopes was seen to be further increased during rainy season as even slopes of minimal steepness of 30 for height 20 m was seen to be on the verge of failure. Also, during dynamic analysis slopes safe during static analysis were found to be highly vulnerable. Lastly, as a part of the study a comparative study on Strength Reduction Method (SRM) versus Limit Equilibrium Method (LEM) was also carried out and some of the advantages and disadvantages were figured out.

Keywords: dynamic analysis, factor of safety, slope stability, strength reduction method

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Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella

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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.

Keywords: clusterwise regression, pavement management system, performance model, optimization

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Authors: Albert Suryaprawira

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The Nasion-Sella Line (NSL) has been used for several years as a reference line in longitudinal growth study. Therefore this line is considered to be stable not only to evaluate treatment outcome and to predict relapse possibility but also to manage prognosis. This is a radiographic superimposition of an adult male aged 19 years who complained of difficulty in aesthetic, talking and chewing. Patient has a midface hypoplasia profile (concave). He was diagnosed to have a severe Skeletal Class III with Class III malocclusion, increased lower vertical height, and an anterior open bite. A pre-treatment cephalometric radiograph was taken to analyse the skeletal problem and to measure the amount of bone movement and the prediction soft tissue response. A panoramic radiograph was also taken to analyse bone quality, bone abnormality, third molar impaction, etc. Before the surgery, a pre-surgical cephalometric radiograph was taken to re-evaluate the plan and to settle the final amount of bone cut. After the surgery, a post-surgical cephalometric radiograph was taken to confirm the result with the plan. The superimposition using NSL as a reference line between those radiographs was performed to analyse the outcome. It is important to describe the amount of hard and soft tissue movement and to predict the possibility of relapse after the surgery. The patient also needs to understand all the surgical plan, outcome and relapse prevention. The surgical management included maxillary impaction and advancement of Le Fort I osteotomy. The evaluation using NSL as a reference was a very useful method in determining the outcome and prognosis.

Keywords: Nasion-Sella Line, midface hypoplasia, Le Fort 1, maxillary advancement

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Authors: Thien Bach Nguyen, Nhu-Van Nguyen, Phi-Minh Nguyen, Minh Hien Dao

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The external store safe separation evaluation process implementing CFD and MIL-HDBK-1763 is proposed to support the evaluation and compliance of the external store safe separation with the extensive using CFD and the criteria from MIL-HDBK-1763. The criteria of safe separation are researched and investigated for the various standards and handbooks such as MIL-HDBK-1763, MIL-HDBK-244A, AGARD-AG-202 and AGARD-AG-300 to acquire the appropriate and tailored values and limits for the typical applications of external carriages and aircraft fighters. The CFD and 6DOF simulations are extensively used in ANSYS 2023 R1 Software for verification and validation of moving unstructured meshes and solvers by calibrating the position, aerodynamic forces and moments of the existing air-to-ground missile models. The verified CFD and 6DoF simulation separation process is applied and implemented for the investigation of the typical munition separation phenomena and compliance with the tailored requirements of MIL-HDBK-1763. The prediction of munition trajectory parameters under aircraft aerodynamics interference and specified rack unit consideration after munition separation is provided and complied with the tailored requirements to support the safe separation evaluation of improved and newly external store munition before the flight test performed. The proposed process demonstrates the effectiveness and reliability in providing the understanding of the complicated store separation and the reduction of flight test sorties during the improved and new munition development projects by extensively using the CFD and tailoring the existing standards.

Keywords: external store separation, MIL-HDBK-1763, CFD, moving meshes, flight test data, munition.

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Authors: Shidvash Vakilipour, Masoud Mohammadi, Rouzbeh Riazi, Scott Ormiston, Kimia Amiri, Sahar Barati

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An essential component of a finite volume method (FVM) is the advection scheme that estimates values on the cell faces based on the calculated values on the nodes or cell centers. The most widely used advection schemes are upwind schemes. These schemes have been developed in FVM on different kinds of structured and unstructured grids. In this research, the physical influence scheme (PIS) is developed for a cell-centered FVM that uses an implicit coupled solver. Results are compared with the exponential differencing scheme (EDS) and the skew upwind differencing scheme (SUDS). Accuracy of these schemes is evaluated for a lid-driven cavity flow at Re = 1000, 3200, and 5000 and a backward-facing step flow at Re = 800. Simulations show considerable differences between the results of EDS scheme with benchmarks, especially for the lid-driven cavity flow at high Reynolds numbers. These differences occur due to false diffusion. Comparing SUDS and PIS schemes shows relatively close results for the backward-facing step flow and different results in lid-driven cavity flow. The poor results of SUDS in the lid-driven cavity flow can be related to its lack of sensitivity to the pressure difference between cell face and upwind points, which is critical for the prediction of such vortex dominant flows.

Keywords: cell-centered finite volume method, coupled solver, exponential differencing scheme (EDS), physical influence scheme (PIS), pressure weighted interpolation method (PWIM), skew upwind differencing scheme (SUDS)

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Authors: Oleg Ye Sysoyev, Artem Yu Dobryshkin, Nyein Sitt Naing

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Cylindrical shells are widely used in the construction of buildings and structures, as well as in the air structure. Thin-walled casings made of aluminum alloys are an effective substitute for reinforced concrete and steel structures in construction. The correspondence of theoretical calculations and the actual behavior of aluminum alloy structures is to ensure their trouble-free operation. In the laboratory of our university, "Building Constructions" conducted an experimental study to determine the effect of the system of attached masses on the natural oscillations of shallow cylindrical shells of aluminum alloys, the results of which were compared with theoretical calculations. The purpose of the experiment is to measure the free oscillations of an open, sloping cylindrical shell for various variations of the attached masses. Oscillations of an open, slender, thin-walled cylindrical shell, rectangular in plan, were measured using induction accelerometers. The theoretical calculation of the shell was carried out on the basis of the equations of motion of the theory of shallow shells, using the Bubnov-Galerkin method. A significant splitting of the flexural frequency spectrum is found, influenced not only by the systems of attached маsses but also by the values of the wave formation parameters, which depend on the relative geometric dimensions of the shell. The correspondence of analytical and experimental data is found, using the example of an open shell of alloy D19, which allows us to speak about the high quality of the study. A qualitative new analytical solution of the problem of determining the value of the oscillation frequency of the shell, carrying a system of attached masses is shown.

Keywords: open hollow shell, nonlinear oscillations, associated mass, frequency

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Authors: Rafael Zhindon Almeida

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Surface water quality is an important concern for the evaluation and prediction of water quality conditions. The objective of this study is to develop a statistical model that can accurately predict the water quality of the El Macho estuary in the city of Machala, El Oro province. The methodology employed in this study is of a basic type that involves a thorough search for theoretical foundations to improve the understanding of statistical modeling for water quality analysis. The research design is correlational, using a multivariate statistical model involving multiple linear regression and principal component analysis. The results indicate that water quality parameters such as fecal coliforms, biochemical oxygen demand, chemical oxygen demand, iron and dissolved oxygen exceed the allowable limits. The water of the El Macho estuary is determined to be below the required water quality criteria. The multiple linear regression model, based on chemical oxygen demand and total dissolved solids, explains 99.9% of the variance of the dependent variable. In addition, principal component analysis shows that the model has an explanatory power of 86.242%. The study successfully developed a statistical model to evaluate the water quality of the El Macho estuary. The estuary did not meet the water quality criteria, with several parameters exceeding the allowable limits. The multiple linear regression model and principal component analysis provide valuable information on the relationship between the various water quality parameters. The findings of the study emphasize the need for immediate action to improve the water quality of the El Macho estuary to ensure the preservation and protection of this valuable natural resource.

Keywords: statistical modeling, water quality, multiple linear regression, principal components, statistical models

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Authors: Wisdom Robert Duruji, Moses Kanayochukwu Ifoh, Efeoghene Edward Esiemunobo

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This study examines the impact of natural and artificial disasters, lackadaisical and semantic approach in risk management, and mitigation implication for sustainable development goals in Nigeria, from 2009 to 2022. The study utilizes a range of research methods to achieve its objectives. These include literature review, website knowledge, Google search, news media information, academic journals, field-work and on-site observations. These diverse methods allow for a comprehensive analysis on the impact and the implications being study. The study finds that paradigm shift from remediating seismic, flooding, environmental pollution and degradation natural disasters by Nigeria Emergency Management Agency (NEMA), to political and charity organization; has plunged risk reduction strategies to embezzling opportunities. However, this lackadaisical and semantic approach in natural disaster mitigation, invariably replicates artificial disasters in Nigeria through: Boko Haram terrorist organization, Fulani herdsmen and farmers conflicts, political violence, kidnapping for ransom, ethnic conflicts, Religious dichotomy, insurgency, secession protagonists, unknown-gun-men, and banditry. This study also, finds that some Africans still engage in self-imposed slavery through human trafficking, by nefariously stow-away to Europe; through Libya, Sahara desert and Mediterranean sea; in search for job opportunities, due to ineptitude in governance by their leaders; a perilous journey that enhanced artificial disasters in Nigeria. That artificial disaster fatality in Nigeria increased from about 5,655 in 2009 to 114,318 in 2018; and to 157,643 in 2022. However, financial and material loss of about $9.29 billion was incurred in Nigeria due to natural disaster, while about $70.59 billion was accrued due to artificial disaster; from 2009 to 2018. Although disaster risk mitigation and politics can synergistically support sustainable development goals; however, they are different entities, and need for distinct separations in Nigeria, as in reality and perception. This study concluded that referendum should be conducted in Nigeria, to ascertain its current status as a nation. Therefore it is recommended that Nigerian governments should refine its naturally endowed crude oil locally; to end fuel subsidy scam, corruption and poverty in Nigeria!

Keywords: corruption, crude oil, environmental risk analysis, Nigeria, referendum, terrorism

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Authors: A. Bahmanpour, I. Eames, C. Klettner, A. Dimakopoulos

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We develop a new set of diagnostic tools to analyze inundation into a model district using three-dimensional CFD simulations, with a view to generating a database against which to test simpler models. A three-dimensional model of Oregon city with different-sized groups of building next to the coastline is used to run calculations of the movement of a long period wave on the shore. The initial and boundary conditions of the off-shore water are set using a nonlinear inverse method based on Eulerian spatial information matching experimental Eulerian time series measurements of water height. The water movement is followed in time, and this enables the pressure distribution on every surface of each building to be followed in a temporal manner. The three-dimensional numerical data set is validated against published experimental work. In the first instance, we use the dataset as a basis to understand the success of reduced models - including 2D shallow water model and reduced 1D models - to predict water heights, flow velocity and forces. This is because models based on the shallow water equations are known to underestimate drag forces after the initial surge of water. The second component is to identify critical flow features, such as hydraulic jumps and choked states, which are flow regions where dissipation occurs and drag forces are large. Finally, we describe how future tsunami inundation models should be modified to account for the complex effects of buildings through drag and blocking.Financial support from UCL and HR Wallingford is greatly appreciated. The authors would like to thank Professor Daniel Cox and Dr. Hyoungsu Park for providing the data on the Seaside Oregon experiment.

Keywords: computational fluid dynamics, extreme events, loading, tsunami

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Authors: Shivam Patel, Abdullah Y. Usmani

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Physiological flow under rest and exercise conditions in patient-specific cerebral aneurysm models is numerically investigated. A finite-volume based code with BiCGStab as the linear equation solver is used to simulate unsteady three-dimensional flow field through the incompressible Navier-Stokes equations. Flow characteristics are first established in a healthy cerebral artery for both physiological conditions. The effect of saccular aneurysm on cerebral hemodynamics is then explored through a comparative analysis of the velocity distribution, nature of flow patterns, wall pressure and wall shear stress (WSS) against the reference configuration. The efficacy of coil embolization as a potential strategy of surgical intervention is also examined by modelling coil as a homogeneous and isotropic porous medium where the extended Darcy’s law, including Forchheimer and Brinkman terms, is applicable. The Carreau-Yasuda non-Newtonian blood model is incorporated to capture the shear thinning behavior of blood. Rest and exercise conditions correspond to normotensive and hypertensive blood pressures respectively. The results indicate that the fluid impingement on the outer wall of the arterial bend leads to abnormality in the distribution of wall pressure and WSS, which is expected to be the primary cause of the localized aneurysm. Exercise correlates with elevated flow velocity, vortex strength, wall pressure and WSS inside the aneurysm sac. With the insertion of coils in the aneurysm cavity, the flow bypasses the dilatation, leading to a decline in flow velocities and WSS. Particle residence time is observed to be lower under exercise conditions, a factor favorable for arresting plaque deposition and combating atherosclerosis.

Keywords: 3D FVM, Cerebral aneurysm, hypertension, coil embolization, non-Newtonian fluid

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Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil

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The paper is devoted to numerically investigating the influence of the air supply outlets geometry on human comfort inside living looms. A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The work focuses on air flow patterns, thermal behavior in the room with few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angles and velocity. Air supply diffusers locations and numbers were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software “Fluent 6.3” is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well-developed two equation turbulence model. In this work, the so-called standard k-ε turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on ADPI (Air Diffusion Performance Index),the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.

Keywords: thermal comfort, Fanger's model, ADPI, energy effeciency

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Authors: F. Q. Shao, W. Q. Wang, Y. Yin, T. P. Yu, D. B. Zou, J. M. Ouyang

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The Radiation Pressure Acceleration (RPA) mechanism is very promising in laser-driven ion acceleration because of high laser-ion energy conversion efficiency. Although some experiments have shown the characteristics of RPA, the energy of ions is quite limited. The ion energy obtained in experiments is only several MeV/u, which is much lower than theoretical prediction. One possible limiting factor is the transverse instability incited in the RPA process. The transverse instability is basically considered as the Rayleigh-Taylor (RT) instability, which is a kind of interfacial instability and occurs when a light fluid pushes against a heavy fluid. Multi-dimensional particle-in-cell (PIC) simulations show that the onset of transverse instability will destroy the acceleration process and broaden the energy spectrum of fast ions during the RPA dominant ion acceleration processes. The evidence of the RT instability driven by radiation pressure has been observed in a laser-foil interaction experiment in a typical RPA regime, and the dominant scale of RT instability is close to the laser wavelength. The development of transverse instability in the radiation-pressure-acceleration dominant laser-foil interaction is numerically examined by two-dimensional particle-in-cell simulations. When a laser interacts with a foil with modulated surface, the internal instability is quickly incited and it develops. The linear growth and saturation of the transverse instability are observed, and the growth rate is numerically diagnosed. In order to optimize interaction parameters, a method of information entropy is put forward to describe the chaotic degree of the transverse instability. With moderate modulation, the transverse instability shows a low chaotic degree and a quasi-monoenergetic proton beam is produced.

Keywords: information entropy, radiation pressure acceleration, Rayleigh-Taylor instability, transverse instability

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Authors: Kebede Gamo Sebehanie, Olu Emmanuel Femi, Alberto Velázquez Del Rosario, Abubeker Yimam Ali, Gudeta Jafo Muleta

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Water pollution is one of the most serious worldwide issues today. Among water pollution, heavy metals are becoming a concern to the environment and human health due to their non-biodegradability and bioaccumulation. In this study, a magnetite-cellulose nanocomposite derived from renewable resources is employed for hexavalent chromium elimination by adsorption. Magnetite nanoparticles were synthesized directly from iron ore using solvent extraction and co-precipitation technique. Cellulose nanofiber was extracted from sugarcane bagasse using the alkaline treatment and acid hydrolysis method. Before and after the adsorption process, the MNPs-CNF composites were evaluated using X-ray diffraction (XRD), Scanning electron microscope (SEM), Fourier transform infrared (FTIR), and Vibrator sample magnetometer (VSM), and Thermogravimetric analysis (TGA). The impacts of several parameters such as pH, contact time, initial pollutant concentration, and adsorbent dose on adsorption efficiency and capacity were examined. The kinetic and isotherm adsorption of Cr (VI) was also studied. The highest removal was obtained at pH 3, and it took 80 minutes to establish adsorption equilibrium. The Langmuir and Freundlich isotherm models were used, and the experimental data fit well with the Langmuir model, which has a maximum adsorption capacity of 8.27 mg/g. The kinetic study of the adsorption process using pseudo-first-order and pseudo-second-order equations revealed that the pseudo-second-order equation was more suited for representing the adsorption kinetic data. Based on the findings, pure MNPs and MNPs-CNF nanocomposites could be used as effective adsorbents for the removal of Cr (VI) from wastewater.

Keywords: magnetite-cellulose nanocomposite, hexavalent chromium, adsorption, sugarcane bagasse

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Authors: W. Hamaidia, T. Zebbiche

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This paper presents the design of axisymmetric supersonic nozzles, in order to accelerate a supersonic flow to the desired Mach number and that having a small weight, in the same time gives a high thrust. The concerned nozzle gives a parallel and uniform flow at the exit section. The nozzle is divided into subsonic and supersonic regions. The supersonic portion is independent to the upstream conditions of the sonic line. The subsonic portion is used to give a sonic flow at the throat. In this case, nozzle gives a uniform and parallel flow at the exit section. It’s named by minimum length Nozzle. The study is done at high temperature, lower than the dissociation threshold of the molecules, in order to improve the aerodynamic performances. Our aim consists of improving the performances both by the increase of exit Mach number and the thrust coefficient and by reduction of the nozzle's mass. The variation of the specific heats with the temperature is considered. The design is made by the Method of Characteristics. The finite differences method with predictor-corrector algorithm is used to make the numerical resolution of the obtained nonlinear algebraic equations. The application is for air. All the obtained results depend on three parameters which are exit Mach number, the stagnation temperature, the chosen mesh in characteristics. A numerical simulation of nozzle through Computational Fluid Dynamics-FASTRAN was done to determine and to confirm the necessary design parameters.

Keywords: flux supersonic flow, axisymmetric minimum length nozzle, high temperature, method of characteristics, calorically imperfect gas, finite difference method, trust coefficient, mass of the nozzle, specific heat at constant pressure, air, error

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Authors: Mounir Baccar, Amel Gammoudi, Abdelhak Ayadi

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The efficient mixing of highly viscous fluids is required for many industries such as food, polymers or paints production. The homogeneity is a challenging operation for this fluids type since they operate at low Reynolds number to reduce the required power of the used impellers. Particularly, close-clearance impellers, mainly helical ribbons, are chosen for highly viscous fluids agitated in laminar regime which is currently heated through vessel wall. Indeed, they are characterized by high shear strains closer to the vessel wall, which causes a disturbing thermal boundary layer and ensures the homogenization of the bulk volume by axial and radial vortices. The hydrodynamic and thermal behaviors of Newtonian fluids in vessels agitated by helical ribbon impellers, has been mostly studied by many researchers. However, rarely researchers investigated numerically the agitation of yield stress fluid by means of helical ribbon impellers. This paper aims to study the effect of the Double Helical Ribbon (DHR) stirrers on both the hydrodynamic and the thermal behaviors of yield stress fluids treated in a cylindrical vessel by means of numerical simulation approach. For this purpose, continuity, momentum, and thermal equations were solved by means of 3D finite volume technique. The effect of Oldroyd (Od) and Reynolds (Re) numbers on the power (Po) and Nusselt (Nu) numbers for the mentioned stirrer type have been studied. Also, the velocity and thermal fields, the dissipation function and the apparent viscosity have been presented in different (r-z) and (r-θ) planes.

Keywords: Bingham fluid, Hydrodynamic and thermal behavior, helical ribbon, mixing, numerical modelling

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Authors: Pavel A. Strizhak, Geniy V. Kuznetsov, Ivan S. Voytkov, Dmitri V. Antonov

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This paper presents the results of experiments carried out at a specialized test site for establishing macroscopic patterns of heat and mass transfer processes at localizing model combustion sources of ground forest fires with the use of barrier lines in the form of a wetted lay of material in front of the zone of flame burning and thermal decomposition. The experiments were performed using needles, leaves, twigs, and mixtures thereof. The dimensions of the model combustion source and the ranges of heat release correspond well to the real conditions of ground forest fires. The main attention is paid to the complex analysis of the effect of dispersion of water aerosol (concentration and size of droplets) used to form the barrier line. It is shown that effective conditions for localization and subsequent suppression of flame combustion and thermal decomposition of forest fuel can be achieved by creating a group of barrier lines with different wetting width and depth of the material. Relative indicators of the effectiveness of one and combined barrier lines were established, taking into account all the main characteristics of the processes of suppressing burning and thermal decomposition of forest combustible materials. We performed the prediction of the necessary and sufficient parameters of barrier lines (water volume, width, and depth of the wetted lay of the material, specific irrigation density) for combustion sources with different dimensions, corresponding to the real fire extinguishing practice.

Keywords: forest fire, barrier water lines, pyrolysis front, flame front

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Authors: Goksel Ezgi Guzey, Bihrat Onoz

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The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region.

Keywords: hydrology, streamflow estimation, climate change, hydrologic modeling, HBV, hydropower

Procedia PDF Downloads 124

Authors: Gulcan Ozerim, Gunay Anlas

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In shape memory alloys, upon loading, stress increases around crack tip and a martensitic phase transformation occurs in early stages. In many studies the stress distribution in the vicinity of the crack tip is represented by using linear elastic fracture mechanics (LEFM) although the pseudo-elastic behavior results in a nonlinear stress-strain relation. In this study, the HRR singularity (Hutchinson, Rice and Rosengren), that uses Rice’s path independent J-integral, is tried to formulate the stress distribution around the crack tip. In HRR approach, the Ramberg-Osgood model for the stress-strain relation of power-law hardening materials is used to represent the elastic-plastic behavior. Although it is recoverable, the inelastic portion of the deformation in martensitic transformation (up to the end of transformation) resembles to that of plastic deformation. To determine the constants of the Ramberg-Osgood equation, the material’s response is simulated in ABAQUS using a UMAT based on ZM (Zaki-Moumni) thermo-mechanically coupled model, and the stress-strain curve of the material is plotted. An edge cracked shape memory alloy (Nitinol) plate is loaded quasi-statically under mode I and modeled using ABAQUS; the opening stress values ahead of the cracked tip are calculated. The stresses are also evaluated using the asymptotic equations of both LEFM and HRR. The results show that in the transformation zone around the crack tip, the stress values are much better represented when the HRR singularity is used although the J-integral does not show path independent behavior. For the nodes very close to the crack tip, the HRR singularity is not valid due to the non-proportional loading effect and high-stress values that go beyond the transformation finish stress.

Keywords: crack, HRR singularity, shape memory alloys, stress distribution

Procedia PDF Downloads 323

Authors: Pranav Ajmera, Amit Kharat, Tanveer Gupte, Richa Pant, Viraj Kulkarni, Vinay Duddalwar, Purnachandra Lamghare

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The cardiothoracic ratio (CTR) is the ratio of the diameter of the heart to the diameter of the thorax. An abnormal CTR, that is, a value greater than 0.55, is often an indicator of an underlying pathological condition. The accurate prediction of an abnormal CTR from chest X-rays (CXRs) aids in the early diagnosis of clinical conditions. We propose a deep learning-based model for automatic CTR calculation that can assist the radiologist with the diagnosis of cardiomegaly and optimize the radiology flow. The study population included 1012 posteroanterior (PA) CXRs from a single institution. The Attention U-Net deep learning (DL) architecture was used for the automatic calculation of CTR. A CTR of 0.55 was used as a cut-off to categorize the condition as cardiomegaly present or absent. An observer performance test was conducted to assess the radiologist's performance in diagnosing cardiomegaly with and without artificial intelligence (AI) assistance. The Attention U-Net model was highly specific in calculating the CTR. The model exhibited a sensitivity of 0.80 [95% CI: 0.75, 0.85], precision of 0.99 [95% CI: 0.98, 1], and a F1 score of 0.88 [95% CI: 0.85, 0.91]. During the analysis, we observed that 51 out of 1012 samples were misclassified by the model when compared to annotations made by the expert radiologist. We further observed that the sensitivity of the reviewing radiologist in identifying cardiomegaly increased from 40.50% to 88.4% when aided by the AI-generated CTR. Our segmentation-based AI model demonstrated high specificity and sensitivity for CTR calculation. The performance of the radiologist on the observer performance test improved significantly with AI assistance. A DL-based segmentation model for rapid quantification of CTR can therefore have significant potential to be used in clinical workflows.

Keywords: cardiomegaly, deep learning, chest radiograph, artificial intelligence, cardiothoracic ratio

Procedia PDF Downloads 95

Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

Procedia PDF Downloads 58

Authors: Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

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The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Nokoue Lake in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Nokoue Lake, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué Lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

Keywords: forecasting, long short-term memory cell, recurrent artificial neural network, Nokoué lake

Procedia PDF Downloads 60

Authors: Filimonova Alexanra

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Inviscid incompressible fluid flows are considered. The object of the study is a vortex parquet – a structure consisting of distributed vortex spots of different directions, occupying the entire plane. The main attention is paid to the study of advection processes of passive particles in the corresponding velocity field. The dynamics of the vortex structures is considered in a rectangular region under the assumption that periodic boundary conditions are imposed on the stream function. Numerical algorithms are based on the solution of the initial-boundary value problem for nonstationary Euler equations in terms of vorticity and stream function. For this, the spectral-vortex meshless method is used. It is based on the approximation of the stream function by the Fourier series cut and the approximation of the vorticity field by the least-squares method from its values in marker particles. A vortex configuration, consisting of four vortex patches is investigated. Results of a numerical study of the dynamics and interaction of the structure are presented. The influence of the patch radius and the relative position of positively and negatively directed patches on the processes of interaction and mixing is studied. The obtained results correspond to the following possible scenarios: the initial configuration does not change over time; the initial configuration forms a new structure, which is maintained for longer times; the initial configuration returns to its initial state after a certain period of time. The processes of mass transfer of vorticity by liquid particles on a plane were calculated and analyzed. The results of a numerical analysis of the particles dynamics and trajectories on the entire plane and the field of local Lyapunov exponents are presented.

Keywords: ideal fluid, meshless methods, vortex structures in liquids, vortex parquet.

Procedia PDF Downloads 61

Authors: Erifyli Tsagkari, Stephanie Connelly, Zhaowei Liu, Andrew McBride, William Sloan

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Biofilms play an essential role in treating water in biofiltration systems. The biofilm morphology and function are inextricably linked to the hydrodynamics of flow through a filter, and yet engineers rarely explicitly engineer this interaction. We develop a system that links computer simulation and 3-D printing to optimize and rapidly prototype filter media to optimize biofilm function with the hypothesis that biofilm function is intimately linked to the flow passing through the filter. A computational model that numerically solves the incompressible time-dependent Navier Stokes equations coupled to a model for biofilm growth and function is developed. The model is imbedded in an optimization algorithm that allows the model domain to adapt until criteria on biofilm functioning are met. This is applied to optimize the shape of filter media in a simple flow channel to promote biofilm formation. The computer code links directly to a 3-D printer, and this allows us to prototype the design rapidly. Its validity is tested in flow visualization experiments and by microscopy. As proof of concept, the code was constrained to explore a small range of potential filter media, where the medium acts as an obstacle in the flow that sheds a von Karman vortex street that was found to enhance the deposition of bacteria on surfaces downstream. The flow visualization and microscopy in the 3-D printed realization of the flow channel validated the predictions of the model and hence its potential as a design tool. Overall, it is shown that the combination of our computational model and the 3-D printing can be effectively used as a design tool to prototype filter media to optimize biofilm formation.

Keywords: biofilm, biofilter, computational model, von karman vortices, 3-D printing.

Procedia PDF Downloads 137

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as vital physiological signs, images, and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision-making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful in influencing the judgement of clinical sentiment in ICU clinical notes. This paper introduces two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of clinical transformer models that can reliably predict clinical sentiment for notes of COVID patients in the ICU. We train the model on clinical notes for COVID-19 patients, a type of notes that were not previously seen by clinicalBERT, and Bio_Discharge_Summary_BERT. The model, which was based on clinicalBERT achieves higher predictive accuracy (Acc 93.33%, AUC 0.98, and precision 0.96 ). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and precision 0.92 ).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation

Procedia PDF Downloads 200

Authors: R. Unnikrishnan, K. Shankar

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In the case of high-speed fighter aircrafts, seat ejection is designed mainly for the safety of the pilot in case of an emergency. Strong windblast due to the high velocity of flight is one main difficulty in clearing the tail of the aircraft. Excessive G-forces generated, immobilizes the pilot from escape. In most of the cases, seats are ejected out of the aircrafts by explosives or by rocket motors attached to the bottom of the seat. Ejection forces are primarily in the vertical direction with the objective of attaining the maximum possible velocity in a specified period of time. The safe ejection parameters are studied to estimate the critical time of ejection for various geometries and velocities of flight. An equivalent analytical 2-dimensional biomechanical model of the human spine has been modelled consisting of vertebrae and intervertebral discs with a lumped mass approach. The 24 vertebrae, which consists of the cervical, thoracic and lumbar regions, in addition to the head mass and the pelvis has been designed as 26 rigid structures and the intervertebral discs are assumed as 25 flexible joint structures. The rigid structures are modelled as mass elements and the flexible joints as spring and damper elements. Here, the motions are restricted only in the mid-sagittal plane to form a 26 degree of freedom system. The equations of motions are derived for translational movement of the spinal column. An ejection force with a linearly increasing acceleration profile is applied as vertical base excitation on to the pelvis. The dynamic vibrational response of each vertebra in time-domain is estimated.

Keywords: biomechanical model, lumped mass, seat ejection, vibrational response

Procedia PDF Downloads 228

Authors: Vivek Upadhayay, Siddharth Deshmukh

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In recent years utilization of renewable energy sources has increased majorly because of the increase in global warming concerns. Organization these days are generally operated by Micro grid or smart grid on a small level. Power optimization and optimal load tripping is possible in a smart grid based industry. In any plant or industry loads can be divided into different categories based on their importance to the plant and power requirement pattern in the working days. Coming up with an idea to divide loads in different such categories and providing different power management algorithm to each category of load can reduce the power cost and can come handy in balancing stability and reliability of power. An objective function is defined which is subjected to a variable that we are supposed to minimize. Constraint equations are formed taking difference between the power usages pattern of present day and same day of previous week. By considering the objectives of minimal load tripping and optimal power distribution the proposed problem formulation is a multi-object optimization problem. Through normalization of each objective function, the multi-objective optimization is transformed to single-objective optimization. As a result we are getting the optimized values of power required to each load for present day by use of the past values of the required power for the same day of last week. It is quite a demand response scheduling of power. These minimized values then will be distributed to each load through an algorithm used to optimize the power distribution at a greater depth. In case of power storage exceeding the power requirement, profit can be made by selling exceeding power to the main grid.

Keywords: power flow optimization, power trading enhancement, smart grid, multi-object optimization

Procedia PDF Downloads 520