Search results for: accidents predictions

Authors: Cleyton S. Stampa

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This paper addresses the perspectives of using low melting point metals (LMPMs) as phase change materials (PCMs) in latent thermal energy storage (LTES) units, through a numerical approach. This is a new class of PCMs that has been one of the most prospective alternatives to be considered in LTES, due to these materials present high thermal conductivity and elevated heat of fusion, per unit volume. The chosen type of LTES consists of several horizontal parallel slabs filled with PCM. The heat transfer fluid (HTF) circulates through the channel formed between each two consecutive slabs on a laminar regime through forced convection. The study deals with the LTES charging process (heat-storing) by using pure gallium as PCM, and it considers heat conduction in the solid phase during melting driven by natural convection in the melt. The transient heat transfer problem is analyzed in one arbitrary slab under the influence of the HTF. The mathematical model to simulate the isothermal phase change is based on a volume-averaged enthalpy method, which is successfully verified by comparing its predictions with experimental data from works available in the pertinent literature. Regarding the convective heat transfer problem in the HTF, it is assumed that the flow is thermally developing, whereas the velocity profile is already fully developed. The study aims to learn about the effect of the solid subcooling in the melting rate through comparisons with the melting process of the solid in which it starts to melt from its fusion temperature. In order to best understand this effect in a metallic compound, as it is the case of pure gallium, the study also evaluates under the same conditions established for the gallium, the melting process of commercial paraffin wax (organic compound) and of the calcium chloride hexahydrate (CaCl₂ 6H₂O-inorganic compound). In the present work, it is adopted the best options that have been established by several researchers in their parametric studies with respect to this type of LTES, which lead to high values of thermal efficiency. To do so, concerning with the geometric aspects, one considers a gap of the channel formed by two consecutive slabs, thickness and length of the slab. About the HTF, one considers the type of fluid, the mass flow rate, and inlet temperature.

Keywords: flat slab, heat storing, pure metal, solid subcooling

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Authors: Paul E. Jose

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A new self-report measure named the General Emotion Regulation Measure (GERM) assesses four key goals for experiencing broad valenced groups of emotions: 1) trying to experience positive emotions (e.g., joy, pride, liking a person); 2) trying to avoid experiencing positive emotions; 3) trying to experience negative emotions (e.g., anger, anxiety, contempt); and 4) trying to avoid experiencing negative emotions. Although individual differences in GERM motives have been identified, evidence of validity with common mood outcomes is lacking. In the present study, whether GERM motives predict self-reported subjective happiness and depressive symptoms (CES-D) was tested with a community sample of 833 young adults. It was predicted that the GERM motive of trying to experience positive emotions would positively predict subjective happiness, and analogously trying to experience negative emotions would predict depressive symptoms. An initial path model was constructed in which the four GERM motives predicted both subjective happiness and depressive symptoms. The fully saturated model included three non-significant paths, which were subsequently pruned, and a good fitting model was obtained (CFI = 1.00; RMR = .007). Two GERM motives significantly predicted subjective happiness: 1) trying to experience positive emotions ( = .38, p < .001) and 2) trying to avoid experiencing positive emotions ( = -.48, p <.001). Thus, individuals who reported high levels of trying to experience positive emotions reported high levels of happiness, and individuals who reported low levels of trying to avoid experiencing positive emotions also reported high levels of happiness. Three GERM motives significantly predicted depressive symptoms: 1) trying to avoid experiencing positive emotions ( = .20, p <.001); 2) trying to experience negative emotions ( = .15, p <.001); and 3) trying to experience positive emotions (= -.07, p <.001). In agreement with predictions, trying to experience positive emotions was positively associated with subjective happiness and trying to experience negative emotions was positively associated with depressive symptoms. In essence, these two valenced mood states seem to be sustained by trying to experience similarly valenced emotions. However, the three other significant paths in the model indicated that emotional motives play a complicated role in supporting both positive and negative mood states. For subjective happiness, the GERM motive of not trying to avoid positive emotions, i.e., not avoiding happiness, was also a strong predictor of happiness. Thus, people who report being the happiest are those individuals who not only strive to experience positive emotions but also are not ambivalent about them. The pattern for depressive symptoms was more nuanced. Individuals who reported higher depressive symptoms also reported higher levels of avoiding positive emotions and trying to experience negative emotions. The strongest predictor for depressed mood was avoiding positive emotions, which would suggest that happiness aversion or fear of happiness is an important motive for dysphoric people. Future work should determine whether these patterns of association are similar among clinically depressed people, and longitudinal data are needed to determine temporal relationships between motives and mood states.

Keywords: emotions motives, depression, subjective happiness, path model

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Authors: Sanjay K. Behera, Debasish Saha, Paramesh Gadige, Ranjini Bandyopadhyay

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The zero shear viscosity (η₀) of a suspension of hard sphere colloids characterized by a significant polydispersity (≈10%) increases with increase in volume fraction (ϕ) and shows a dramatic increase at ϕ=ϕg with the system entering a colloidal glassy state. Fragility which is the measure of the rapidity of approach of these suspensions towards the glassy state is sensitive to its size polydispersity and stiffness of the particles. Soft poly(N-isopropylacrylamide) (PNIPAM) particles deform in the presence of neighboring particles at volume fraction above the random close packing volume fraction of undeformed monodisperse spheres. Softness, therefore, enhances the packing efficiency of these particles. In this study PNIPAM particles of a nearly constant swelling ratio and with polydispersities varying over a wide range (7.4%-48.9%) are synthesized to study the effects of polydispersity on the dynamics of suspensions of soft PNIPAM colloidal particles. The size and polydispersity of these particles are characterized using dynamic light scattering (DLS) and scanning electron microscopy (SEM). As these particles are deformable, their packing in aqueous suspensions is quantified in terms of effective volume fraction (ϕeff). The zero shear viscosity (η₀) data of these colloidal suspensions, estimated from rheometric experiments as a function of the effective volume fraction ϕeff of the suspensions, increases with increase in ϕeff and shows a dramatic increase at ϕeff = ϕ₀. The data for η₀ as a function of ϕeff fits well to the Vogel-Fulcher-Tammann equation. It is observed that increasing polydispersity results in increasingly fragile supercooled liquid-like behavior, with the parameter ϕ₀, extracted from the fits to the VFT equation shifting towards higher ϕeff. The observed increase in fragility is attributed to the prevalence of dynamical heterogeneities (DHs) in these polydisperse suspensions, while the simultaneous shift in ϕ₀ is ascribed to the decoupling of the dynamics of the smallest and largest particles. Finally, it is observed that the intrinsic nonlinearity of these suspensions, estimated at the third harmonic near ϕ₀ in Fourier transform oscillatory rheological experiments, increases with increase in polydispersity. These results are in agreement with theoretical predictions and simulation results for polydisperse hard sphere colloidal glasses and clearly demonstrate that jammed suspensions of polydisperse colloidal particles can be effectively fluidized with increasing polydispersity. Suspensions of these particles are therefore excellent candidates for detailed experimental studies of the effects of polydispersity on the dynamics of glass formation.

Keywords: dynamical heterogeneity, effective volume fraction, fragility, intrinsic nonlinearity

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Authors: Anjula Negi, D. T. V. Raghu Ramaswamy, Rajneesh Sareen

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Road infrastructure is emphatically one of the top most critical infrastructure to the Indian economy. Road network in the country of around 3.3 million km is the second largest in the world. Nationwide statistics released by Ministry of Road, Transport and Highways reveal that every minute an accident happens and one death every 3.7 minutes. This reported scale in terms of safety is a matter of grave concern, and economically represents a national loss of 3% to the GDP. Union Budget 2016-17 has allocated USD 12 billion annually for development and strengthening of roads, an increase of 56% from last year. Thus, highlighting the importance of roads as critical infrastructure. National highway alone represent only 1.7% of the total road linkages, however, carry over 40% of traffic. Further, trends analysed from 2002 -2011 on national highways, indicate that in less than a decade, a 22 % increase in accidents have been reported, but, 68% increase in death fatalities. Paramount inference is that accident severity has increased with time. Over these years many measures to increase road safety, lessening damage to physical assets, reducing vulnerabilities leading to a build-up for resilient road infrastructure have been taken. In the context of national highway development program, policy makers proposed implementation of around 20 % of such road length on PPP mode. These roads were taken up on high-density traffic considerations and for qualitative implementation. In order to understand resilience impacts and safety parameters, enshrined in various PPP concession agreements executed with the private sector partners, such highway specific projects would be appraised. This research paper would attempt to assess such safety measures taken and the possible reasons behind an increase in accident severity through these PPP case study projects. Delving further on safety features to understand policy measures adopted in these cases and an introspection on reasons of severity, whether an outcome of increased speeds, faulty road design and geometrics, driver negligence, or due to lack of discipline in following lane traffic with increased speed. Assessment exercise would study these aspects hitherto to PPP and post PPP project structures, based on literature review and opinion surveys with sectoral experts. On the way forward, it is understood that the Ministry of Road, Transport and Highway’s estimate for strengthening the national highway network is USD 77 billion within next five years. The outcome of this paper would provide an understanding of resilience measures adopted, possible options for accessible and safe road network and its expansion to policy makers for possible policy initiatives and funding allocation in securing critical infrastructure.

Keywords: national highways, policy, PPP, safety

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Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

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Authors: Richard Sogah

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The significance of transport infrastructure investments for economic growth and development has been central to the World Bank’s strategy for poverty reduction. Among the conventional surface transport infrastructures, road infrastructure is significant in facilitating the movement of human capital goods and services. When transport projects (i.e., roads, super-highways) are implemented, they come along with some negative social values (costs), such as increased noise and air pollution for local residents living near these facilities, displaced individuals, etc. However, these projects also facilitate better utilization of existing capital stock and generate other observable benefits that can be easily quantified. For example, the improvement or construction of roads creates employment, stimulates revenue generation (toll), reduces vehicle operating costs and accidents, increases accessibility, trade expansion, safety improvement, etc. Aside from these benefits, travel time savings (TTSs) which are the major economic benefits of urban and inter-urban transport projects and therefore integral in the economic assessment of transport projects, are often overlooked and omitted when estimating the benefits of transport projects, especially in developing countries. The absence of current and reliable domestic travel data and the inability of replicated models from the developed world to capture the actual value of travel time savings due to the large unemployment, underemployment, and other labor-induced distortions has contributed to the failure to assign value to travel time savings when estimating the benefits of transport schemes in developing countries. This omission of the value of travel time savings from the benefits of transport projects in developing countries poses problems for investors and stakeholders to either accept or dismiss projects based on schemes that favor reduced vehicular operating costs and other parameters rather than those that ease congestion, increase average speed, facilitate walking and handloading, and thus save travel time. Given the complex reality in the estimation of the value of travel time savings and the presence of widespread informal labour activities in Sub-Saharan Africa, we construct a “nationally ranked distribution of time values” and estimate the value of travel time savings based on the area beneath the distribution. Compared with other approaches, our method captures both formal sector workers and individuals/people who work outside the formal sector and hence changes in their time allocation occur in the informal economy and household production activities. The dataset for the estimations is sourced from the World Bank, the International Labour Organization, etc.

Keywords: road infrastructure, transport projects, travel time savings, congestion, Sub-Sahara Africa

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Authors: W. Meron Mebrahtu, R. Absi

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Velocity distribution in turbulent open-channel flows is organized in a complex manner. This is due to the large spatial and temporal variability of fluid motion resulting from the free-surface turbulent flow condition. This phenomenon is complicated further due to the complex geometry of channels and the presence of solids transported. Thus, several efforts were made to understand the phenomenon and obtain accurate mathematical models that are suitable for engineering applications. However, predictions are inaccurate because oversimplified assumptions are involved in modeling this complex phenomenon. Therefore, the aim of this work is to study velocity distribution profiles and obtain simple, more accurate, and predictive mathematical models. Particular focus will be made on the acceptable simplification of the general transport equations and an accurate representation of eddy viscosity. Wide rectangular open-channel seems suitable to begin the study; other assumptions are smooth-wall, and sediment-free flow under steady and uniform flow conditions. These assumptions will allow examining the effect of the bottom wall and the free surface only, which is a necessary step before dealing with more complex flow scenarios. For this flow condition, two ordinary differential equations are obtained for velocity profiles; from the Reynolds-averaged Navier-Stokes (RANS) equation and equilibrium consideration between turbulent kinetic energy (TKE) production and dissipation. Then different analytic models for eddy viscosity, TKE, and mixing length were assessed. Computation results for velocity profiles were compared to experimental data for different flow conditions and the well-known linear, log, and log-wake laws. Results show that the model based on the RANS equation provides more accurate velocity profiles. In the viscous sublayer and buffer layer, the method based on Prandtl’s eddy viscosity model and Van Driest mixing length give a more precise result. For the log layer and outer region, a mixing length equation derived from Von Karman’s similarity hypothesis provides the best agreement with measured data except near the free surface where an additional correction based on a damping function for eddy viscosity is used. This method allows more accurate velocity profiles with the same value of the damping coefficient that is valid under different flow conditions. This work continues with investigating narrow channels, complex geometries, and the effect of solids transported in sewers.

Keywords: accuracy, eddy viscosity, sewers, velocity profile

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Authors: Ciara Pienaar, J. W. Odendaal, J. Joubert, J. C. Smit

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Radar cross section (RCS) of dielectric objects play an important role in many applications, such as low observability technology development, drone detection, and monitoring as well as coastal surveillance. Various materials are used to construct the targets of interest such as metal, wood, composite materials, radar absorbent materials, and other dielectrics. Since simulated datasets are increasingly being used to supplement infield measurements, as it is more cost effective and a larger variety of targets can be simulated, it is important to have a high level of confidence in the predicted results. Confidence can be attained through validation. Various computational electromagnetic (CEM) methods are capable of predicting the RCS of dielectric targets. This study will extend previous studies by validating full-wave and asymptotic RCS simulations of dielectric targets with measured data. The paper will provide measured RCS data of a number of canonical dielectric targets exhibiting different material properties. As stated previously, these measurements are used to validate numerous CEM methods. The dielectric properties are accurately characterized to reduce the uncertainties in the simulations. Finally, an analysis of the sensitivity of oblique and normal incidence scattering predictions to material characteristics is also presented. In this paper, the ability of several CEM methods, including method of moments (MoM), and physical optics (PO), to calculate the RCS of dielectrics were validated with measured data. A few dielectrics, exhibiting different material properties, were selected and several canonical targets, such as flat plates and cylinders, were manufactured. The RCS of these dielectric targets were measured in a compact range at the University of Pretoria, South Africa, over a frequency range of 2 to 18 GHz and a 360° azimuth angle sweep. This study also investigated the effect of slight variations in the material properties on the calculated RCS results, by varying the material properties within a realistic tolerance range and comparing the calculated RCS results. Interesting measured and simulated results have been obtained. Large discrepancies were observed between the different methods as well as the measured data. It was also observed that the accuracy of the RCS data of the dielectrics can be frequency and angle dependent. The simulated RCS for some of these materials also exhibit high sensitivity to variations in the material properties. Comparison graphs between the measured and simulation RCS datasets will be presented and the validation thereof will be discussed. Finally, the effect that small tolerances in the material properties have on the calculated RCS results will be shown. Thus the importance of accurate dielectric material properties for validation purposes will be discussed.

Keywords: asymptotic, CEM, dielectric scattering, full-wave, measurements, radar cross section, validation

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Authors: Visith Siriphuwanun, Yodying Punjasawadwong, Suwinai Saengyo, Kittipan Rerkasem

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Objective: To determine incidences and factors associated with perioperative cardiac arrest in trauma patients who received anesthesia for emergency surgery. Design and setting: Retrospective cohort study in trauma patients during anesthesia for emergency surgery at a university hospital in northern Thailand country. Patients and methods: This study was permitted by the medical ethical committee, Faculty of Medicine at Maharaj Nakorn Chiang Mai Hospital, Thailand. We clarified data of 19,683 trauma patients receiving anesthesia within a decade between January 2007 to March 2016. The data analyzed patient characteristics, traumas surgery procedures, anesthesia information such as ASA physical status classification, anesthesia techniques, anesthetic drugs, location of anesthesia performed, and cardiac arrest outcomes. This study excluded the data of trauma patients who had received local anesthesia by surgeons or monitoring anesthesia care (MAC) and the patient which missing more information. The factor associated with perioperative cardiac arrest was identified with univariate analyses. Multiple regressions model for risk ratio (RR) and 95% confidence intervals (CI) were used to conduct factors correlated with perioperative cardiac arrest. The multicollinearity of all variables was examined by bivariate correlation matrix. A stepwise algorithm was chosen at a p-value less than 0.02 was selected to further multivariate analysis. A P-value of less than 0.05 was concluded as statistically significant. Measurements and results: The occurrence of perioperative cardiac arrest in trauma patients receiving anesthesia for emergency surgery was 170.04 per 10,000 cases. Factors associated with perioperative cardiac arrest in trauma patients were age being more than 65 years (RR=1.41, CI=1.02–1.96, p=0.039), ASA physical status 3 or higher (RR=4.19–21.58, p < 0.001), sites of surgery (intracranial, intrathoracic, upper intra-abdominal, and major vascular, each p < 0.001), cardiopulmonary comorbidities (RR=1.55, CI=1.10–2.17, p < 0.012), hemodynamic instability with shock prior to receiving anesthesia (RR=1.60, CI=1.21–2.11, p < 0.001) , special techniques for surgery such as cardiopulmonary bypass (CPB) and hypotensive techniques (RR=5.55, CI=2.01–15.36, p=0.001; RR=6.24, CI=2.21–17.58, p=0.001, respectively), and patients who had a history of being alcoholic (RR=5.27, CI=4.09–6.79, p < 0.001). Conclusion: Incidence of perioperative cardiac arrest in trauma patients receiving anesthesia for emergency surgery was very high and correlated with many factors, especially age of patient and cardiopulmonary comorbidities, patient having a history of alcoholic addiction, increasing ASA physical status, preoperative shock, special techniques for surgery, and sites of surgery including brain, thorax, abdomen, and major vascular region. Anesthesiologists and multidisciplinary teams in pre- and perioperative periods should remain alert for warning signs of pre-cardiac arrest and be quick to manage the high-risk group of surgical trauma patients. Furthermore, a healthcare policy should be promoted for protecting against accidents in high-risk groups of the population as well.

Keywords: perioperative cardiac arrest, trauma patients, emergency surgery, anesthesia, factors risk, incidence

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Authors: Roberta Martino, Viviana Ventre

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From a theoretical point of view, the relationship between the risk associated with an investment and the expected value are directly proportional, in the sense that the market allows a greater result to those who are willing to take a greater risk. However, empirical evidence proves that this relationship is distorted in the minds of investors and is perceived exactly the opposite. To deepen and understand the discrepancy between the actual actions of the investor and the theoretical predictions, this paper analyzes the essential parameters used for the valuation of financial assets with greater attention to two elements: probability and the passage of time. Although these may seem at first glance to be two distinct elements, they are closely related. In particular, the error in the theoretical description of the relationship between risk and return lies in the failure to consider the impatience that is generated in the decision-maker when events that have not yet happened occur in the decision-making context. In this context, probability loses its objective meaning and in relation to the psychological aspects of the investor, it can only be understood as the degree of confidence that the investor has in the occurrence or non-occurrence of an event. Moreover, the concept of objective probability does not consider the inter-temporality that characterizes financial activities and does not consider the condition of limited cognitive capacity of the decision maker. Cognitive psychology has made it possible to understand that the mind acts with a compromise between quality and effort when faced with very complex choices. To evaluate an event that has not yet happened, it is necessary to imagine that it happens in your head. This projection into the future requires a cognitive effort and is what differentiates choices under conditions of risk and choices under conditions of uncertainty. In fact, since the receipt of the outcome in choices under risk conditions is imminent, the mechanism of self-projection into the future is not necessary to imagine the consequence of the choice and the decision makers dwell on the objective analysis of possibilities. Financial activities, on the other hand, develop over time and the objective probability is too static to consider the anticipatory emotions that the self-projection mechanism generates in the investor. Assuming that uncertainty is inherent in valuations of events that have not yet occurred, the focus must shift from risk management to uncertainty management. Only in this way the intertemporal dimension of the decision-making environment and the haste generated by the financial market can be cautioned and considered. The work considers an extension of the prospectus theory with the temporal component with the aim of providing a description of the attitude towards risk with respect to the passage of time.

Keywords: impatience, risk aversion, subjective probability, uncertainty

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Authors: Dana R. Thomson, Catherine Linard, Sabine Vanhuysse, Jessica E. Steele, Michal Shimoni, Jose Siri, Waleska Caiaffa, Megumi Rosenberg, Eleonore Wolff, Tais Grippa, Stefanos Georganos, Helen Elsey

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The Sustainable Development Goals (SDGs) and Urban Health Equity Assessment and Response Tool (Urban HEART) identify dozens of key indicators to help local decision-makers prioritize and track inequalities in health outcomes. However, presentations and discussions at the International Conference on Urban Health (ICUH) 2017 suggested that additional indicators are needed to make decisions and policies. A local decision-maker may realize that malaria or road accidents are a top priority. However, s/he needs additional health determinant indicators, for example about standing water or traffic, to address the priority and reduce inequalities. Health determinants reflect the physical and social environments that influence health outcomes often at community- and societal-levels and include such indicators as access to quality health facilities, access to safe parks, traffic density, location of slum areas, air pollution, social exclusion, and social networks. Indicator identification and disaggregation are necessarily constrained by available datasets – typically collected about households and individuals in surveys, censuses, and administrative records. Continued advancements in earth observation, data storage, computing and mobile technologies mean that new sources of health determinants indicators derived from 'big data' are becoming available at fine geographic scale. Big data includes high-resolution satellite imagery and aggregated, anonymized mobile phone data. While big data are themselves not representative of the population (e.g., satellite images depict the physical environment), they can provide information about population density, wealth, mobility, and social environments with tremendous detail and accuracy when combined with population-representative survey, census, administrative and health system data. The aim of this paper is to (1) flag to data scientists important indicators needed by health decision-makers at the city and sub-city scale - ideally free and publicly available, and (2) summarize for local decision-makers new datasets that can be generated from big data, with layperson descriptions of difficulties in generating them. We include SDGs and Urban HEART indicators, as well as indicators mentioned by decision-makers attending ICUH 2017.

Keywords: health determinant, health outcome, mobile phone, remote sensing, satellite imagery, SDG, urban HEART

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Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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Authors: Champika Amarasinghe

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Introduction: Covid 19 pandemic was badly hit to the Sri Lankan economy during the year 2021. More than 65% of the Sri Lankan work force is engaged with small and medium scale businesses which no doubt that they had to struggle for their survival and business continuity during the pandemic. Objective: To assess the association of adherence to the new norms during the Covid 19 pandemic and maintenance of healthy working environmental conditions for business continuity. A cross sectional study was carried out to assess the OSH status and adequacy of Covid 19 preventive strategies among the 200 SME’S in selected two districts in Sri Lanka. These two districts were selected considering the highest availability of SME’s. Sample size was calculated, and probability propionate to size was used to select the SME’s which were registered with the small and medium scale development authority. An interviewer administrated questionnaire was used to collect the data, and OSH risk assessment was carried out by a team of experts to assess the OSH status in these industries. Results: According to the findings, more than 90% of the employees in these industries had a moderate awareness related to COVID 19 disease and preventive strategies such as the importance of Mask use, hand sainting practices, and distance maintenance, but the only forty percent of them were adhered to implementation of these practices. Furthermore, only thirty five percent of the employees and employers in these SME’s new the reasons behind the new norms, which may be the reason for reluctance to implement these strategies and reluctance to adhering to the new norms in this sector. The OSH risk assessment findings revealed that the working environmental organization while maintaining the distance between two employees was poor due to the inadequacy of space in these entities. More than fifty five percent of the SME’s had proper ventilation and lighting facilities. More than eighty five percent of these SME’s had poor electrical safety measures. Furthermore, eighty two percent of them had not maintained fire safety measures. Eighty five percent of them were exposed to heigh noise levels and chemicals where they were not using any personal protectives nor any other engineering controls were not imposed. Floor conditions were poor, and they were not maintaining the occupational accident nor occupational disease diseases. Conclusions: Based on the findings, proper awareness sessions were carried out by NIOSH. Six physical training sessions and continues online trainings were carried out to overcome these issues, which made a drastic change in their working environments and ended up with hundred percent implementation of the Covid 19 preventive strategies, which intern improved the worker participation in the businesses. Reduced absentees and improved business opportunities, and continued their businesses without any interruption during the third episode of Covid 19 in Sri Lanka.

Keywords: working environment, Covid 19, occupational diseases, occupational accidents

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Authors: Anuruddha Jayasuriya, Thanakorn Pheeraphan

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In this paper, a review of different mathematical models which can be used as prediction tools to assess the time to crack reinforced concrete (RC) due to corrosion is investigated. This investigation leads to an experimental study to validate a selected prediction model. Most of these mathematical models depend upon the mechanical behaviors, chemical behaviors, electrochemical behaviors or geometric aspects of the RC members during a corrosion process. The experimental program is designed to verify the accuracy of a well-selected mathematical model from a rigorous literature study. Fundamentally, the experimental program exemplifies both one-dimensional chloride diffusion using RC squared slab elements of 500 mm by 500 mm and two-dimensional chloride diffusion using RC squared column elements of 225 mm by 225 mm by 500 mm. Each set consists of three water-to-cement ratios (w/c); 0.4, 0.5, 0.6 and two cover depths; 25 mm and 50 mm. 12 mm bars are used for column elements and 16 mm bars are used for slab elements. All the samples are subjected to accelerated chloride corrosion in a chloride bath of 5% (w/w) sodium chloride (NaCl) solution. Based on a pre-screening of different models, it is clear that the well-selected mathematical model had included mechanical properties, chemical and electrochemical properties, nature of corrosion whether it is accelerated or natural, and the amount of porous area that rust products can accommodate before exerting expansive pressure on the surrounding concrete. The experimental results have shown that the selected model for both one-dimensional and two-dimensional chloride diffusion had ±20% and ±10% respective accuracies compared to the experimental output. The half-cell potential readings are also used to see the corrosion probability, and experimental results have shown that the mass loss is proportional to the negative half-cell potential readings that are obtained. Additionally, a statistical analysis is carried out in order to determine the most influential factor that affects the time to corrode the reinforcement in the concrete due to chloride diffusion. The factors considered for this analysis are w/c, bar diameter, and cover depth. The analysis is accomplished by using Minitab statistical software, and it showed that cover depth is the significant effect on the time to crack the concrete from chloride induced corrosion than other factors considered. Thus, the time predictions can be illustrated through the selected mathematical model as it covers a wide range of factors affecting the corrosion process, and it can be used to predetermine the durability concern of RC structures that are vulnerable to chloride exposure. And eventually, it is further concluded that cover thickness plays a vital role in durability in terms of chloride diffusion.

Keywords: accelerated corrosion, chloride diffusion, corrosion cracks, passivation layer, reinforcement corrosion

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Authors: Mark Ashton Newman, Richard Blagrove, Jonathan Folland

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The force-velocity profile of an individual has been shown to influence success in ballistic movements, independent of the individuals' maximal power output; therefore, effective and accurate evaluation of an individual’s F-V characteristics and not solely maximal power output is important. The relatively narrow range of loads typically utilised during force-velocity profiling protocols due to the difficulty in obtaining force data at high velocities may bring into question the accuracy of the F-V slope along with predictions pertaining to the maximum force that the system can produce at a velocity of null (F₀) and the theoretical maximum velocity against no load (V₀). As such, the reliability of the slope of the force-velocity profile, as well as V₀, has been shown to be relatively poor in comparison to F₀ and maximal power, and it has been recommended to assess velocity at loads closer to both F₀ and V₀. The aim of the present study was to assess the relative and absolute reliability of an instrumented novel leg press machine which enables the assessment of force and velocity data at loads equivalent to ≤ 10% of one repetition maximum (1RM) through to 1RM during a ballistic leg press movement. The reliability of maximal and mean force, velocity, and power, as well as the respective force-velocity and power-velocity relationships and the linearity of the force-velocity relationship, were evaluated. Sixteen male strength-trained individuals (23.6 ± 4.1 years; 177.1 ± 7.0 cm; 80.0 ± 10.8 kg) attended four sessions; during the initial visit, participants were familiarised with the leg press, modified to include a mounted force plate (Type SP3949, Force Logic, Berkshire, UK) and a Micro-Epsilon WDS-2500-P96 linear positional transducer (LPT) (Micro-Epsilon, Merseyside, UK). Peak isometric force (IsoMax) and a dynamic 1RM, both from a starting position of 81% leg length, were recorded for the dominant leg. Visits two to four saw the participants carry out the leg press movement at loads equivalent to ≤ 10%, 30%, 50%, 70%, and 90% 1RM. IsoMax was recorded during each testing visit prior to dynamic F-V profiling repetitions. The novel leg press machine used in the present study appears to be a reliable tool for measuring F and V-related variables across a range of loads, including velocities closer to V₀ when compared to some of the findings within the published literature. Both linear and polynomial models demonstrated good to excellent levels of reliability for SFV and F₀ respectively, with reliability for V₀ being good using a linear model but poor using a 2nd order polynomial model. As such, a polynomial regression model may be most appropriate when using a similar unilateral leg press setup to predict maximal force production capabilities due to only a 5% difference between F₀ and obtained IsoMax values with a linear model being best suited to predict V₀.

Keywords: force-velocity, leg-press, power-velocity, profiling, reliability

Procedia PDF Downloads 31

Authors: A. G. Akhundov

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Issues of obtaining unbiased data on the status of pipeline systems of oil- and oil product transportation become especially important when laying and operating pipelines under severe nature and climatic conditions. The essential attention is paid here to researching exogenous processes and their impact on linear facilities of the pipeline system. Reliable operation of pipelines under severe nature and climatic conditions, timely planning and implementation of compensating measures are only possible if operation conditions of pipeline systems are regularly monitored, and changes of permafrost soil and hydrological operation conditions are accounted for. One of the main reasons for emergency situations to appear is the geodynamic factor. Emergency situations are proved by the experience to occur within areas characterized by certain conditions of the environment and to develop according to similar scenarios depending on active processes. The analysis of natural and technical systems of main pipelines at different stages of monitoring gives a possibility of making a forecast of the change dynamics. The integration of GIS technologies, traditional means of geotechnical monitoring (in-line inspection, geodetic methods, field observations), and remote methods (aero-visual inspection, aero photo shooting, air and ground laser scanning) provides the most efficient solution of the problem. The united environment of geo information system (GIS) is a comfortable way to implement the monitoring system on the main pipelines since it provides means to describe a complex natural and technical system and every element thereof with any set of parameters. Such GIS enables a comfortable simulation of main pipelines (both in 2D and 3D), the analysis of situations and selection of recommendations to prevent negative natural or man-made processes and to mitigate their consequences. The specifics of such systems include: a multi-dimensions simulation of facilities in the pipeline system, math modelling of the processes to be observed, and the use of efficient numeric algorithms and software packets for forecasting and analyzing. We see one of the most interesting possibilities of using the monitoring results as generating of up-to-date 3D models of a facility and the surrounding area on the basis of aero laser scanning, data of aerophotoshooting, and data of in-line inspection and instrument measurements. The resulting 3D model shall be the basis of the information system providing means to store and process data of geotechnical observations with references to the facilities of the main pipeline; to plan compensating measures, and to control their implementation. The use of GISs for geotechnical monitoring of pipeline systems is aimed at improving the reliability of their operation, reducing the probability of negative events (accidents and disasters), and at mitigation of consequences thereof if they still are to occur.

Keywords: databases, 3D GIS, geotechnical monitoring, pipelines, laser scaning

Procedia PDF Downloads 167

Authors: Ahmed Borg, Elsa Aristodemou, Attia Attia

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Well control involves managing the circulating drilling fluid within the wells and avoiding kicks and blowouts as these can lead to losses in human life and drilling facilities. Current practices for good control incorporate predictions of pressure losses through computational models. Developing a realistic hydraulic model for a good control problem is a very complicated process due to the existence of a complex multiphase region, which usually contains a non-Newtonian drilling fluid and the miscibility of formation gas in drilling fluid. The current approaches assume an inaccurate flow fluid model within the well, which leads to incorrect pressure loss calculations. To overcome this problem, researchers have been considering the more complex two-phase fluid flow models. However, even these more sophisticated two-phase models are unsuitable for applications where pressure dynamics are important, such as in managed pressure drilling. This study aims to develop and implement new fluid flow models that take into consideration the miscibility of fluids as well as their non-Newtonian properties for enabling realistic kick treatment. furthermore, a corresponding numerical solution method is built with an enriched data bank. The research work considers and implements models that take into consideration the effect of two phases in kick treatment for well control in conventional drilling. In this work, a corresponding numerical solution method is built with an enriched data bank. Software STARCCM+ for the computational studies to study the important parameters to describe wellbore multiphase flow, the mass flow rate, volumetric fraction, and velocity of each phase. Results showed that based on the analysis of these simulation studies, a coarser full-scale model of the wellbore, including chemical modeling established. The focus of the investigations was put on the near drill bit section. This inflow area shows certain characteristics that are dominated by the inflow conditions of the gas as well as by the configuration of the mud stream entering the annulus. Without considering the gas solubility effect, the bottom hole pressure could be underestimated by 4.2%, while the bottom hole temperature is overestimated by 3.2%. and without considering the heat transfer effect, the bottom hole pressure could be overestimated by 11.4% under steady flow conditions. Besides, larger reservoir pressure leads to a larger gas fraction in the wellbore. However, reservoir pressure has a minor effect on the steady wellbore temperature. Also as choke pressure increases, less gas will exist in the annulus in the form of free gas.

Keywords: multiphase flow, well- control, STARCCM+, petroleum engineering and gas technology, computational fluid dynamic

Procedia PDF Downloads 96

Authors: Luciana S. Almeida

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Nanotechnology has revolutionized the world of science and technology bringing great expectations due to its great potential of application in the most varied industrial sectors. The same characteristics that make nanoparticles interesting from the point of view of the technological application, these may be undesirable when released into the environment. The small size of nanoparticles facilitates their diffusion and transport in the atmosphere, water, and soil and facilitates the entry and accumulation of nanoparticles in living cells. The main objective of this study is to evaluate the environmental regulatory process of nanomaterials in the Brazilian scenario. Three specific objectives were outlined. The first is to carry out a global scientometric study, in a research platform, with the purpose of identifying the main lines of study of nanomaterials in the environmental area. The second is to verify how environmental agencies in other countries have been working on this issue by means of a bibliographic review. And the third is to carry out an assessment of the Brazilian Nanotechnology Draft Law 6741/2013 with the state environmental agencies. This last one has the aim of identifying the knowledge of the subject by the environmental agencies and necessary resources available in the country for the implementation of the Policy. A questionnaire will be used as a tool for this evaluation to identify the operational elements and build indicators through the Environment of Evaluation Application, a computational application developed for the development of questionnaires. At the end will be verified the need to propose changes in the Draft Law of the National Nanotechnology Policy. Initial studies, in relation to the first specific objective, have already identified that Brazil stands out in the production of scientific publications in the area of nanotechnology, although the minority is in studies focused on environmental impact studies. Regarding the general panorama of other countries, some findings have also been raised. The United States has included the nanoform of the substances in an existing program in the EPA (Environmental Protection Agency), the TSCA (Toxic Substances Control Act). The European Union issued a draft of a document amending Regulation 1907/2006 of the European Parliament and Council to cover the nanoform of substances. Both programs are based on the study and identification of environmental risks associated with nanomaterials taking into consideration the product life cycle. In relation to Brazil, regarding the third specific objective, it is notable that the country does not have any regulations applicable to nanostructures, although there is a Draft Law in progress. In this document, it is possible to identify some requirements related to the environment, such as environmental inspection and licensing; industrial waste management; notification of accidents and application of sanctions. However, it is not known if these requirements are sufficient for the prevention of environmental impacts and if national environmental agencies will know how to apply them correctly. This study intends to serve as a basis for future actions regarding environmental management applied to the use of nanotechnology in Brazil.

Keywords: environment; management; nanotecnology; politics

Procedia PDF Downloads 98

Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

Procedia PDF Downloads 42

Authors: Martin Pellon Consunji

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Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

Procedia PDF Downloads 98

Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Within agent-based modeling, opinion dynamics is the field that focuses on modeling people's opinions. In this prolific field, most of the literature is dedicated to the exploration of the two 'degrees of freedom' and how they impact the model’s properties (e.g., the average final opinion, the number of final clusters, etc.). These degrees of freedom are (1) the interaction rule, which determines how agents update their own opinion, and (2) the network topology, which defines the possible interaction among agents. In this work, we show that the third degree of freedom exists. This can be used to change a model's output up to 100% of its initial value or to transform two models (both from the literature) into each other. Since opinion dynamics models are representations of the real world, it is fundamental to understand how people’s opinions can be measured. Even for abstract models (i.e., not intended for the fitting of real-world data), it is important to understand if the way of numerically representing opinions is unique; and, if this is not the case, how the model dynamics would change by using different representations. The process of measuring opinions is non-trivial as it requires transforming real-world opinion (e.g., supporting most of the liberal ideals) to a number. Such a process is usually not discussed in opinion dynamics literature, but it has been intensively studied in a subfield of psychology called psychometrics. In psychometrics, opinion scales can be converted into each other, similarly to how meters can be converted to feet. Indeed, psychometrics routinely uses both linear and non-linear transformations of opinion scales. Here, we analyze how this transformation affects opinion dynamics models. We analyze this effect by using mathematical modeling and then validating our analysis with agent-based simulations. Firstly, we study the case of perfect scales. In this way, we show that scale transformations affect the model’s dynamics up to a qualitative level. This means that if two researchers use the same opinion dynamics model and even the same dataset, they could make totally different predictions just because they followed different renormalization processes. A similar situation appears if two different scales are used to measure opinions even on the same population. This effect may be as strong as providing an uncertainty of 100% on the simulation’s output (i.e., all results are possible). Still, by using perfect scales, we show that scales transformations can be used to perfectly transform one model to another. We test this using two models from the standard literature. Finally, we test the effect of scale transformation in the case of finite precision using a 7-points Likert scale. In this way, we show how a relatively small-scale transformation introduces both changes at the qualitative level (i.e., the most shared opinion at the end of the simulation) and in the number of opinion clusters. Thus, scale transformation appears to be a third degree of freedom of opinion dynamics models. This result deeply impacts both theoretical research on models' properties and on the application of models on real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

Procedia PDF Downloads 104

Authors: Karolina Ordon, Sandrine Coste, Malgorzata Makowska-Janusik, Abdelhadi Kassiba

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Photocatalytic processes play key role in the production of a new source of energy (as hydrogen), design of self-cleaning surfaces or for the environment preservation. The most challenging task deals with the purification of water distinguished by high efficiency. In the mentioned process, organic pollutants in solutions are decomposed to the simple, non-toxic compounds as H2O and CO2. The most known photocatalytic materials are ZnO, CdS and TiO2 semiconductors with a particular involvement of TiO2 as an efficient photocatalysts even with a high band gap equal to 3.2 eV which exploit only UV radiation from solar emitted spectrum. However, promising material with visible light induced photoactivity was searched through the monoclinic polytype of BiVO4 which has energy gap about 2.4 eV. As required in heterogeneous photocatalysis, the high contact surface is required. Also, BiVO4 as photocatalyst can be optimized by increasing its surface area by achieving the mesoporous structure synthesize. The main goal of the present work consists in the synthesis and characterization of BiVO4 mesoporous thin film. The synthesis method based on sol-gel was carried out using a standard surfactants such as P123 and F127. The thin film was deposited by spin and dip coating method. Then, the structural analysis of the obtained material was performed thanks to X-ray diffraction (XRD) and Raman spectroscopy. The surface of resulting structure was investigated using a scanning electron microscopy (SEM). The computer simulations based on modeling the optical and electronic properties of bulk BiVO4 by using DFT (density functional theory) methodology were carried out. The semiempirical parameterized method PM6 was used to compute the physical properties of BiVO4 nanostructures. The Raman and IR absorption spectra were also measured for synthesized mesoporous material, and the results were compared with the theoretical predictions. The simulations of nanostructured BiVO4 have pointed out the occurrence of quantum confinement for nanosized clusters leading to widening of the band gap. This result overcame the relevance of nanosized objects to harvest wide part of the solar spectrum. Also, a balance was searched experimentally through the mesoporous nature of the films devoted to enhancing the contact surface as required for heterogeneous catalysis without to lower the nanocrystallite size under some critical sizes inducing an increased band gap. The present contribution will discuss the relevant features of the mesoporous films with respect to their photocatalytic responses.

Keywords: bismuth vanadate, photocatalysis, thin film, quantum-chemical calculations

Procedia PDF Downloads 306

Authors: Chun-Liang Wu, Kai-Ping Shaw, Cheng-Ping Yu, Wu-Chien Chien, Hsiao-Ting Chen, Shao-Huang Wu

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Objective: This study analyzed three criminal judicial cases. We applied the patterned injuries of the rider to demonstrate the facts of each accident, reconstruct the scenes, and pursue the truth. Methods: Case analysis, a method that collects evidence and reasons the results in judicial procedures, then the importance of the pattern of injury as evidence will be compared and evaluated. The patterned injuries analysis method is to compare the collision situation between an object and human body injuries to determine whether the characteristics can reproduce the unique pattern of injury. Result: Case 1: Two motorcycles, A and B, head-on collided; rider A dead, and rider B was accused. During the prosecutor’s investigation, the defendant learned that rider A had an 80 mm open wound on his neck. During the court trial, the defendant requested copies of the case file and found out that rider A had a large contusion on his chest wall, and the cause of death was traumatic hemothorax and abdominal wall contusion. The defendant compared all the evidence at the scene and determined that the injury was obviously not caused by the collision of the body or the motorcycle of rider B but that rider was out of control and injured himself when he crossed the double yellow line. In this case, the defendant was innocent in the High Court judgment in April 2022. Case 2: Motorcycles C and D head-on crashed, and rider C died of massive abdominal bleeding. The prosecutor decided that rider C was driving under the influence (DUI), but rider D was negligent and sued rider D. The defendant requested the copies’ file and found the special phenomenon that the front wheel of motorcycle C was turned left. The defendant’s injuries were a left facial bone fracture, a left femur fracture, and other injuries on the left side. The injuries were of human-vehicle separation and human-vehicle collision, which proved that rider C suddenly turned left when the two motorcycles approached, knocked down motorcycle D, and the defendant flew forward. Case 3: Motorcycle E and F’s rear end collided, the front rider E was sentenced to 3 months, and the rear rider F sued rider E for more than 7 million N.T. The defendant found in the copies’ file that the injury of rider F was the left tibial platform fracture, etc., and then proved that rider F made the collision with his left knee, causing motorcycle E to fall out of control. This evidence was accepted by the court and is still on trial. Conclusion: The application of patterned injuries in the reconstruction of a motorcycle accident could discover the truth and provide the basis for judicial justice. The cases and methods could be the reference for the policy of preventing traffic accident casualties.

Keywords: judicial evidence, patterned injuries analysis, accident reconstruction, fatal motorcycle injuries

Procedia PDF Downloads 54

Authors: Sanjeev Sinha, Samir Saurav

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The rapid growth of urban areas in India has led to transportation challenges like traffic congestion and an increase in accidents. Despite efforts by state governments and local administrations to improve urban transport, the surge in private vehicles has worsened the situation. Patna, located in Bihar State, is an example of the trend of increasing reliance on private motor vehicles, resulting in vehicular congestion and emissions. The existing transportation infrastructure is inadequate to meet future travel demands, and there has been a notable increase in the share of private vehicles in the city. Additionally, there has been a surge in economic activities in the region, which has increased the demand for improved travel convenience and connectivity. To address these challenges, a study was conducted to assess the most suitable transit mode for the proposed transit corridor outlined in the Comprehensive Mobility Plan (CMP) for Patna. The study covered four stages: developing screening criteria, evaluating parameters for various alternatives, qualitative and quantitative evaluations of alternatives, and implementation options for the most viable alternative. The study suggests that a mass transit system such as a metro rail is necessary to enhance Patna's urban public transport system. The New Metro Policy 2017 outlines specific prerequisites for submitting a Metro Rail Project Proposal to the Ministry of Housing and Urban Affairs (MoHUA), including the preparation of a CMP, the formation of an Urban Metropolitan Transport Authority (UMTA), the creation of an Alternative Analysis Report, the development of a Detailed Project Report, a Multi-Modal Integration Plan, and a Transit-Oriented Development (TOD) Plan. In 2018, the Comprehensive Mobility Plan for Patna was prepared, setting the stage for the subsequent steps in the metro rail project proposal. The results indicated that from the screening and analysis of qualitative parameters for different alternative modes in Patna, it is inferred that the Metro Rail and Monorail score 82.25 and 70.50, respectively, on a scale of 100. Based on the initial analysis and alternative evaluation in the form of quantitative analysis, the Metro Rail System significantly outperformed the Monorail system. The Metro Rail System has a positive Economic Net Present Value (ENPV) at a 14% internal rate of return, while the Monorail has a negative value. In conclusion, the study recommends choosing metro rail over monorail for the proposed transit corridor in Patna. However, the lack of broad-based technical expertise may result in implementation delays and increased costs for monorail.

Keywords: comprehensive mobility plan, alternative analysis, mobility corridors, mass transit system

Procedia PDF Downloads 87

Authors: Muteb Alotaibi, Graham Clarke, Nick Malleson

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The Hajj religious festival at Mina in Saudi Arabia has always presented the opportunity for injuries or deaths. For example, in 1990, a stampede killed 1426 pilgrims, whilst in 1997, 343 people were killed and 1500 injured due to a fire fuelled by high winds sweeping through the tent city in Mina.Many more minor incidents have occurred since then. It is predicted that 5 million pilgrims will soon perform the ritual at Mina (which is, in effect, a temporary city built each year in the desert), which might lead in the future to severe congestion and accidents unless the research is conducted on actions that contribute positively to improving the management of the crowd and facilitating the flow of pilgrims safely and securely. To help prevent further disasters, it is important to first plan better, more accessible locations for emergency services across Mina to ensure a good service for pilgrims. In this paper, we first use a Location Allocation Model (LAM) within a network GIS to examine the optimal locations for key services in the temporary city of Mina. This has been undertaken in relation to the location and movement of the pilgrims during the six day religious festival. The results of various what-if scenarios have been compared against the current location of services. A major argument is that planners should be flexible and locate facilities at different locations throughout the day and night. The use of location-allocation models in this type of comparative static mode has rarely been operationalised in the literature. Second, we model pilgrim movements and behaviours along with the most crowded parts of the network. This has been modelled using an agent-based model. This model allows planners to understand the key bottlenecks in the network and at what usage levels the paths become critically congested. Thus the paper has important implications and recommendations for future disaster planning strategies. This will enable planners to see at what stage in the movements of pilgrims problems occur in terms of potential crushes and trampling incidents. The main application of this research was only customised for pedestrians as the concentration only for pedestrians who move to Jamarat via foot. Further, the network in the middle of Mina was only dedicated for pedestrians for safety, so no Buses, trains and private cars were allowed in this area to prevent the congestion within this network. Initially, this research focus on Mina city as ‘temporary city’ and also about service provision in temporary cities, which is not highlighted in literature so far. Further, it is the first study which use the dynamic demand to optimise the services in the case of day and night time. Moreover, it is the first study which link the location allocation model for optimising services with ABM to find out whether or not the service location is located in the proper location in which it’s not affecting on crowd movement in mainstream flow where some pilgrims need to have health services.

Keywords: ABM, crowd management, hajj, temporary city

Procedia PDF Downloads 102

Authors: Adisorn Banhan, Toansakul Santiboon, Prasong Saihong

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Using the Socio-Scientific Issues-Based Learning Method is to compare of the blended instruction of STEM education with a sample consisted of 84 students in 2 classes at the 11th grade level in Sarakham Pittayakhom School. The 2-instructional models were managed of five instructional lesson plans in the context of electronic wave issue. These research procedures were designed of each instructional method through two groups, the 40-experimental student group was designed for the instructional STEM education (STEMe) and 40-controlling student group was administered with the Socio-Scientific Issues-Based Learning (SSIBL) methods. Associations between students’ learning achievements of each instructional method and their science attitudes of their predictions to their exploring activities toward physics with the STEMe and SSIBL methods were compared. The Measuring Reasonable Ethics Test (MRET) was assessed students’ reasonable ethics with the STEMe and SSIBL instructional design methods on two each group. Using the pretest and posttest technique to monitor and evaluate students’ performances of their reasonable ethics on electromagnetic wave issue in the STEMe and SSIBL instructional classes were examined. Students were observed and gained experience with the phenomena being studied with the Socio-Scientific Issues-Based Learning method Model. To support with the STEM that it was not just teaching about Science, Technology, Engineering, and Mathematics; it is a culture that needs to be cultivated to help create a problem solving, creative, critical thinking workforce for tomorrow in physics. Students’ attitudes were assessed with the Test Of Physics-Related Attitude (TOPRA) modified from the original Test Of Science-Related Attitude (TOSRA). Comparisons between students’ learning achievements of their different instructional methods on the STEMe and SSIBL were analyzed. Associations between students’ performances the STEMe and SSIBL instructional design methods of their reasonable ethics and their science attitudes toward physics were associated. These findings have found that the efficiency of the SSIBL and the STEMe innovations were based on criteria of the IOC value higher than evidence as 80/80 standard level. Statistically significant of students’ learning achievements to their later outcomes on the controlling and experimental groups with the SSIBL and STEMe were differentiated between students’ learning achievements at the .05 level. To compare between students’ reasonable ethics with the SSIBL and STEMe of students’ responses to their instructional activities in the STEMe is higher than the SSIBL instructional methods. Associations between students’ later learning achievements with the SSIBL and STEMe, the predictive efficiency values of the R2 indicate that 67% and 75% for the SSIBL, and indicate that 74% and 81% for the STEMe of the variances were attributable to their developing reasonable ethics and science attitudes toward physics, consequently.

Keywords: socio-scientific issues-based learning method, STEM education, science attitudes, measurement, reasonable ethics, physics classes

Procedia PDF Downloads 264

Authors: Seema Dhariwal, Kiran Maan, Ruchi Baghel, Apoorva Sharma, Poonam Rana

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Introduction: Traumatic brain injury (TBI) is defined as the temporary or permanent alteration in brain function and pathology caused by an external mechanical force. It represents the leading cause of mortality and morbidity among children and youth individuals. Various models of TBI in rodents have been developed in the laboratory to mimic the scenario of injury. Blast overpressure injury is common among civilians and military personnel, followed by accidents or explosive devices. In addition to this, the lateral Controlled cortical impact (CCI) model mimics the blunt, penetrating injury. Method: In the present study, we have developed two different mild TBI models using blast and CCI injury. In the blast model, helium gas was used to create an overpressure of 130 kPa (±5) via a shock tube, and CCI injury was induced with an impact depth of 1.5mm to create diffusive and focal injury, respectively. C57BL/6J male mice (10-12 weeks) were divided into three groups: (1) control, (2) Blast treated, (3) CCI treated, and were exposed to different injury models. Serum was collected on Day1 and day7, followed by biphasic extraction using MTBE/Methanol/Water. Prepared samples were separated on Charged Surface Hybrid (CSH) C18 column and acquired on UHPLC-Q-TOF-MS using ESI probe with inhouse optimized parameters and method. MS peak list was generated using Markerview TM. Data were normalized, Pareto-scaled, and log-transformed, followed by multivariate and univariate analysis in metaboanalyst. Result and discussion: Untargeted profiling of lipids generated extensive data features, which were annotated through LIPID MAPS® based on their m/z and were further confirmed based on their fragment pattern by LipidBlast. There is the final annotation of 269 features in the positive and 182 features in the negative mode of ionization. PCA and PLS-DA score plots showed clear segregation of injury groups to controls. Among various lipids in mild blast and CCI, five lipids (Glycerophospholipids {PC 30:2, PE O-33:3, PG 28:3;O3 and PS 36:1 } and fatty acyl { FA 21:3;O2}) were significantly altered in both injury groups at Day 1 and Day 7, and also had VIP score >1. Pathway analysis by Biopan has also shown hampered synthesis of Glycerolipids and Glycerophospholipiods, which coincides with earlier reports. It could be a direct result of alteration in the Acetylcholine signaling pathway in response to TBI. Understanding the role of a specific class of lipid metabolism, regulation and transport could be beneficial to TBI research since it could provide new targets and determine the best therapeutic intervention. This study demonstrates the potential lipid biomarkers which can be used for injury severity diagnosis and identification irrespective of injury type (diffusive or focal).

Keywords: LipidBlast, lipidomic biomarker, LIPID MAPS®, TBI

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Authors: Tiffany Baetens, Sophie Halliez, Luc Buée, Emiliano Pallecchi, Vincent Thomy, Steve Arscott

Abstract:

We demonstrate here a viable stretchable bio-microelectromechanical systems (BioMEMS) technology for use with biological studies concerned with the effect of high mechanical strains on living cells. An example of this is traumatic brain injury (TBI) where neurons are damaged with physical force to the brain during, e.g., accidents and sports. Robust, miniaturized integrated systems are needed by biologists to be able to study the effect of TBI on neuron cells in vitro. The major challenges in this area are (i) to develop micro, and nanofabrication processes which are based on stretchable substrates and to (ii) create systems which are robust and performant at very high mechanical strain values—sometimes as high as 100%. At the time of writing, such processes and systems were rapidly evolving subject of research and development. The BioMEMS which we present here is composed of an elastomer substrate (low Young’s modulus ~1 MPa) onto which is patterned robust electrodes and insulators. The patterning of the thin films is achieved using standard photolithography techniques directly on the elastomer substrate—thus making the process generic and applicable to many materials’ in based systems. The chosen elastomer used is commercial ‘Sylgard 184’ polydimethylsiloxane (PDMS). It is spin-coated onto a silicon wafer. Multistep ultra-violet based photolithography involving commercial photoresists are then used to pattern robust thin film metallic electrodes (chromium/gold) and insulating layers (parylene) on the top of the PDMS substrate. The thin film metals are deposited using thermal evaporation and shaped using lift-off techniques The BioMEMS has been characterized mechanically using an in-house strain-applicator tool. The system is composed of 12 electrodes with one reference electrode transversally-orientated to the uniaxial longitudinal straining of the system. The electrical resistance of the electrodes is observed to remain very stable with applied strain—with a resistivity approaching that of evaporated gold—up to an interline strain of ~50%. The mechanical characterization revealed some interesting original properties of such stretchable BioMEMS. For example, a Poisson effect induced electrical ‘self-healing’ of cracking was identified. Biocompatibility of the commercial photoresist has been studied and is conclusive. We will present the results of the BioMEMS, which has also characterized living cells with a commercial Multi Electrode Array (MEA) characterization tool (Multi Channel Systems, USA). The BioMEMS enables the cells to be strained up to 50% and then characterized electrically and optically.

Keywords: BioMEMS, elastomer, electrical impedance measurements of living cells, high mechanical strain, microfabrication, stretchable systems, thin films, traumatic brain injury

Procedia PDF Downloads 127

Authors: Hossein Havaeji, Tony Wong, Thien-My Dao

Abstract:

1. Research Problems and Research Objectives: Blockchain Technology-enabled Supply Chain System (BT-enabled SCS) is the system using BT to drive SCS transparency, security, durability, and process integrity as SCS data is not always visible, available, or trusted. The costs of operating BT in the SCS are a common problem in several organizations. The costs must be estimated as they can impact existing cost control strategies. To account for system and deployment costs, it is necessary to overcome the following hurdle. The problem is that the costs of developing and running a BT in SCS are not yet clear in most cases. Many industries aiming to use BT have special attention to the importance of BT installation cost which has a direct impact on the total costs of SCS. Predicting BT installation cost in SCS may help managers decide whether BT is to be an economic advantage. The purpose of the research is to identify some main BT installation cost components in SCS needed for deeper cost analysis. We then identify and categorize the main groups of cost components in more detail to utilize them in the prediction process. The second objective is to determine the suitable Supervised Learning technique in order to predict the costs of developing and running BT in SCS in a particular case study. The last aim is to investigate how the running BT cost can be involved in the total cost of SCS. 2. Work Performed: Applied successfully in various fields, Supervised Learning is a method to set the data frame, treat the data, and train/practice the method sort. It is a learning model directed to make predictions of an outcome measurement based on a set of unforeseen input data. The following steps must be conducted to search for the objectives of our subject. The first step is to make a literature review to identify the different cost components of BT installation in SCS. Based on the literature review, we should choose some Supervised Learning methods which are suitable for BT installation cost prediction in SCS. According to the literature review, some Supervised Learning algorithms which provide us with a powerful tool to classify BT installation components and predict BT installation cost are the Support Vector Regression (SVR) algorithm, Back Propagation (BP) neural network, and Artificial Neural Network (ANN). Choosing a case study to feed data into the models comes into the third step. Finally, we will propose the best predictive performance to find the minimum BT installation costs in SCS. 3. Expected Results and Conclusion: This study tends to propose a cost prediction of BT installation in SCS with the help of Supervised Learning algorithms. At first attempt, we will select a case study in the field of BT-enabled SCS, and then use some Supervised Learning algorithms to predict BT installation cost in SCS. We continue to find the best predictive performance for developing and running BT in SCS. Finally, the paper will be presented at the conference.

Keywords: blockchain technology, blockchain technology-enabled supply chain system, installation cost, supervised learning

Procedia PDF Downloads 101

Authors: Justine Kiiza, Xu Jiafang

Abstract:

The world’s demand for energy is increasing rapidly due to population growth and a reduction in shallow conventional oil and gas reservoirs, resorting to deeper and mostly unconventional reserves like shale oil and gas. Most shale formations contain a large amount of expansive sodium montmorillonite (Na-Mnt), due to high water adsorption, hydration, and when the drilling fluid filtrate enters the formation with high Mnt content, the wellbore wall can be unstable due to hydration and swelling, resulting to shrinkage, sticking, balling, time wasting etc., and well collapse in extreme cases causing complex downhole accidents and high well costs. Recently, polyamines like 1, 6 – hexane diamine (HEDA) have been used as typical drilling fluid shale inhibitors to minimize and/or cab clay mineral swelling and maintain the wellbore stability. However, their application is limited to shallow drilling due to their sensitivity to elevated temperature and pressure. Inorganic potassium salts i.e., KCl, have long been applied for restriction of shale formation hydration expansion in deep wells, but their use is limited due to toxicity. Understanding the adsorption behaviour of HEDA on Na-Mnt surfaces in present of organo-salts, organic K-salts e.g., HCO₂K - main component of organo-salt drilling fluid, is of great significance in explaining the inhibitory performance of polyamine inhibitors. Molecular dynamic simulations (MD) were applied to investigate the influence of HCO₂K and KCl on the adsorption mechanism of HEDA on the Na-Mnt surface. Simulation results showed that adsorption configurations of HEDA are mainly by terminal amine groups with a flat-lying alkyl hydrophobic chain. Its interaction with the clay surface decreased the H-bond number between H₂O-clay and neutralized the negative charge of the Mnt surface, thus weakening the surface hydration ability of Na-Mnt. The introduction of HCO₂K greatly improved inhibition ability, coordination of interlayer ions with H₂O as they were replaced by K+, and H₂O-HCOO- coordination reduced H₂O-Mnt interactions, mobility and transport capability of H₂O molecules were more decreased. While KCl showed little ability and also caused more hydration with time, HCO₂K can be used as an alternative for offshore drilling instead of toxic KCl, with a maximum concentration noted in this study as 1.65 wt%. This study provides a theoretical elucidation for the inhibition mechanism and adsorption characteristics of HEDA inhibitor on Na-Mnt surfaces in the presence of K+-salts and may provide more insight into the evaluation, selection, and molecular design of new clay-swelling high-performance WBDF systems used in oil and gas complex offshore drilling well sections.

Keywords: shale, hydration, inhibition, polyamines, organo-salts, simulation

Procedia PDF Downloads 22