Search results for: crash prediction

Authors: R. Velvarska, A. Vrablik, M. Fiedlerova, R. Cerny

Abstract:

Near-infrared spectrometry (NIR) was tested as a rapid and alternative tool for determination of biodiesel oxidation stability. A PetroOxy method is standardly used for the determination, but this method is hazardous due to the possibility of explosion and ignition of flammable fuels. The second disadvantage is time consuming. The near-infrared spectrometry served for the development of the calibration model which was composed of 133 real samples (calibration standards). The reference values of these standards were obtained by PetroOxy method. Many chemometric diagnostics were used for the development of the final NIR model with the aim to have accurate prediction of the oxidation stability. The final NIR model was validated by 30 validation standards. The repeatability was determined as well with the acceptable residual standard deviation (8.59 %). The NIR spectrometry has proved to be an accurate alternative method for the determination of biodiesel oxidation stability with advantages as the time and cost saving, non-destructive character of analyzing and the possibility of online monitoring in safe mode.

Keywords: biodiesel, fatty acid methyl ester, NIR, oxidation stability

Procedia PDF Downloads 157

Authors: Fatemeh Yazdanmehr, Iulian Nistor

Abstract:

The scope of the current study is the prediction of water separation in a two-stage industrial crude oil desalting plant. This research study was focused on developing a desalting operation in an existing production unit of one Iranian heavy oil field with 75 MBPD capacity. Because of some operational issues, such as oil dehydration at high temperatures, the optimization of the desalter operational parameters was essential. The mathematical desalting is modeled based on the population balance method. The existing operational data is used for tuning and validation of the accuracy of the modeling. The inlet oil temperature to desalter used was decreased from 110°C to 80°C, and the desalted electrical field was increased from 0.75 kv to 2.5 kv. The proposed condition for the desalter also meets the water oil specification. Based on these conditions of desalter, the oil recovery is increased by 574 BBL/D, and the gas flaring decrease by 2.8 MMSCF/D. Depending on the oil price, the additional production of oil can increase the annual income by about $15 MM and reduces greenhouse gas production caused by gas flaring.

Keywords: desalter, demulsification, modelling, water-oil separation, crude oil emulsion

Procedia PDF Downloads 51

Authors: S. Bouharati, F. Allag, M. Belmahdi, M. Bounechada

Abstract:

In terms of ecology forecast effects of desertification, the purpose of this study is to develop a predictive model of growth and adaptation of species in arid environment and bioclimatic conditions. The impact of climate change and the desertification phenomena is the result of combined effects in magnitude and frequency of these phenomena. Like the data involved in the phytopathogenic process and bacteria growth in arid soil occur in an uncertain environment because of their complexity, it becomes necessary to have a suitable methodology for the analysis of these variables. The basic principles of fuzzy logic those are perfectly suited to this process. As input variables, we consider the physical parameters, soil type, bacteria nature, and plant species concerned. The result output variable is the adaptability of the species expressed by the growth rate or extinction. As a conclusion, we prevent the possible strategies for adaptation, with or without shifting areas of plantation and nature adequate vegetation.

Keywords: climate changes, dry soil, phytopathogenicity, predictive model, fuzzy logic

Procedia PDF Downloads 303

Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu

Abstract:

Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.

Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model

Procedia PDF Downloads 378

Authors: Monika Chuchro

Abstract:

This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain a subgroups of time series data with normal distribution from inflow into waste water treatment plant data which Composed of several groups differing by mean value. Two simple algorithms: K-mean and EM were chosen as a clustering method. The rand index was used to measure the similarity. After simple meta-clustering, regression model was performed for each subgroups. The final model was a sum of subgroups models. The quality of obtained model was compared with the regression model made using the same explanatory variables but with no clustering of data. Results were compared by determination coefficient (R2), measure of prediction accuracy mean absolute percentage error (MAPE) and comparison on linear chart. Preliminary results allows to foresee the potential of the presented technique.

Keywords: clustering, data analysis, data mining, predictive models

Procedia PDF Downloads 450

Authors: Honggang Qu, Yong Xu, Rongmei Liu, Zhenji Gao, Bin Wang

Abstract:

Today's mining industry is advancing gradually toward digital and visual direction. The three-dimensional visualization geological modeling of mine is the digital characterization of mineral deposits and is one of the key technology of digital mining. Three-dimensional geological modeling is a technology that combines geological spatial information management, geological interpretation, geological spatial analysis and prediction, geostatistical analysis, entity content analysis and graphic visualization in a three-dimensional environment with computer technology and is used in geological analysis. In this paper, the three-dimensional geological modeling of an iron mine through the use of Surpac is constructed, and the weight difference of the estimation methods between the distance power inverse ratio method and ordinary kriging is studied, and the ore body volume and reserves are simulated and calculated by using these two methods. Compared with the actual mine reserves, its result is relatively accurate, so it provides scientific bases for mine resource assessment, reserve calculation, mining design and so on.

Keywords: three-dimensional geological modeling, geological database, geostatistics, block model

Procedia PDF Downloads 62

Authors: Williams S. Ebhota, Freddie L. Inambao

Abstract:

This study investigates the use of centrifugal casting method to fabricate functionally graded aluminium A356 Alloy and A356-10%SiCp composite for hydro turbine bucket application. The study includes the design and fabrication of a permanent mould. The mould was put into use and the buckets of A356 Alloy and A356-10%SiCp composite were cast, cut and machined into specimens. Some specimens were given T6 heat treatment and the specimens were prepared for different examinations accordingly. The SiCp particles were found to be more at inner periphery of the bucket. The maximum hardness of As-Cast A356 and A356-10%SiCp composite was recorded at the inner periphery to be 60 BRN and 95BRN, respectively. And these values were appreciated to 98BRN and 122BRN for A356 alloy and A356-10%SiCp composite, respectively. It was observed that the ultimate tensile stress and yield tensile stress prediction curves show the same trend.

Keywords: A356 alloy, A356-10%SiCp composite, centrifugal casting, Pelton bucket, turbine blade

Procedia PDF Downloads 263

Authors: Theophilus Adjirackor, Frederic Sam, Irene Opoku-Ntim, David Okoh Kpeglo, Prince K. Gyekye, Frank K. Quashie, Kofi Ofori

Abstract:

Indoor radon concentrations were collected monthly over a period of one year in 10 different levels in an underground goldmine, and the data was analyzed using a four-moving average time series to determine the relationship between the depths of the underground mine and the indoor radon concentration. The detectors were installed in batches within four quarters. The measurements were carried out using LR115 solid-state nuclear track detectors. Statistical models are applied in the prediction and analysis of the radon concentration at various depths. The time series model predicted a positive relationship between the depth of the underground mine and the indoor radon concentration. Thus, elevated radon concentrations are expected at deeper levels of the underground mine, but the relationship was insignificant at the 5% level of significance with a negative adjusted R2 (R2 = – 0.021) due to an appropriate engineering and adequate ventilation rate in the underground mine.

Keywords: LR115, radon concentration, rime series, underground goldmine

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Authors: Marcelo Müller Beuren, José Luis Duarte Ribeiro

Abstract:

Studies point that Brazilian large airports are not managing their assets efficiently. Therefore, organizations seek improvements to raise their asset’s productivity. Hence, identification of assets useful life in airports becomes an important subject, since its accuracy leads to better maintenance plans and technological substitution, contribution to airport services management. However, current useful life prediction models do not converge in terms of determinant elements used, as they are particular to the studied situation. For that reason, the main objective of this paper is to identify the determinant elements for a useful life of major assets in airports. With that purpose, a case study was held in the key airport of the south of Brazil trough historical data analysis and specialist interview. This paper concluded that most of the assets useful life are determined by technical elements, maintenance cost, and operational costs, while few presented influence of technological obsolescence. As a highlight, it was possible to identify the determinant elements to be considered by a model which objective is to identify the useful life of airport’s major assets.

Keywords: airports, asset management, asset useful life

Procedia PDF Downloads 503

Authors: Emre Kara, Ahmet Fatih Geylan, Kadir Koç, Şura Karakuzu, Metehan Demir, Halil Aykul

Abstract:

The structures obtained with the use of sandwich technologies combine low weight with high energy absorbing capacity and load carrying capacity. Hence, there is a growing and markedly interest in the use of sandwiches with aluminium foam core because of very good properties such as flexural rigidity and energy absorption capability. The static (bending and penetration) and dynamic (dynamic bending and low velocity impact) tests were already performed on the aluminum foam cored sandwiches with different types of outer skins by some of the authors. In the current investigation, the static three-point bending tests were carried out on the sandwiches with aluminum foam core and glass fiber reinforced polymer (GFRP) skins at different values of support span distances (L= 55, 70, 80, 125 mm) aiming the analyses of their flexural performance. The influence of the core thickness and the GFRP skin type was reported in terms of peak load, energy absorption capacity and energy efficiency. For this purpose, the skins with two different types of fabrics ([0°/90°] cross ply E-Glass Woven and [0°/90°] cross ply S-Glass Woven which have same thickness value of 1.5 mm) and the aluminum foam core with two different thicknesses (h=10 and 15 mm) were bonded with a commercial polyurethane based flexible adhesive in order to combine the composite sandwich panels. The GFRP skins fabricated via Vacuum Assisted Resin Transfer Molding (VARTM) technique used in the study can be easily bonded to the aluminum foam core and it is possible to configure the base materials (skin, adhesive and core), fiber angle orientation and number of layers for a specific application. The main results of the bending tests are: force-displacement curves, peak force values, absorbed energy, energy efficiency, collapse mechanisms and the effect of the support span length and core thickness. The results of the experimental study showed that the sandwich with the skins made of S-Glass Woven fabrics and with the thicker foam core presented higher mechanical values such as load carrying and energy absorption capacities. The increment of the support span distance generated the decrease of the mechanical values for each type of panels, as expected, because of the inverse proportion between the force and span length. The most common failure types of the sandwiches are debonding of the upper or lower skin and the core shear. The obtained results have particular importance for applications that require lightweight structures with a high capacity of energy dissipation, such as the transport industry (automotive, aerospace, shipbuilding and marine industry), where the problems of collision and crash have increased in the last years.

Keywords: aluminum foam, composite panel, flexure, transport application

Procedia PDF Downloads 314

Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

Abstract:

This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

Procedia PDF Downloads 186

Authors: Danladi Ali

Abstract:

This work proposed to adopt and optimize the conventional method of estimating power generated from campus solid waste (CSW) using an intelligent technique. The chemical content of the CSW was analyzed, the population responsible for the generation of the CSW, the amount of CSW generated, power to grid predicted and forecasted were obtained, and sources of supply of electricity for Adamawa State University (ADSU) were compared with the PGPs estimated from the CSW. The percentage content of the chemical elements was obtained as 56.90% carbon, 8.40% hydrogen, 27.70% oxygen, 6.00% nitrogen and 1.00% sulfur. The amount of the CSW generated and power to grid predicted and forecasted for 10 years was determined as 287.74 tons/day, 13.12MW and 12.90 MW, respectively. A model for estimating power potential from CSW for ADSU was developed, and also the work revealed that the PGPs estimated from the CSW are adequate to power the University for 24 hours on a daily basis.

Keywords: prediction, intelligent, forecasting, environment, power to grid, campus solid waste

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Authors: Yulia V. Krasavtseva, Tatiana V. Kornilova

Abstract:

Risk-taking behaviors are not only dictated by cognitive components but also involve emotional aspects. Anticipatory emotions, involving both cognitive and affective mechanisms, are involved in decision-making in general, and risk-taking in particular. Affective reactions are prompted when an expectation or prediction is either validated or invalidated in the achieved result. This study aimed to combine predictions, anticipatory emotions, affective reactions, and personality traits in the context of risk-taking behaviors. An experimental online method Emotion and Prediction In a Casino (EPIC) was used, based on a casino-like roulette game. In a series of choices, the participant is presented with progressively riskier roulette combinations, where the potential sums of wins and losses increase with each choice and the participant is given a choice: to 'walk away' with the current sum of money or to 'play' the displayed roulette, thus accepting the implicit risk. Before and after the result is displayed, participants also rate their emotions, using the Self-Assessment Mannequin [Bradley, Lang, 1994], picking a picture, representing the intensity of pleasure, arousal, and dominance. The following personality measures were used: 1) Personal Decision-Making Factors [Kornilova, 2003] assessing risk and rationality; 2) I7 – Impulsivity Questionnaire [Kornilova, 1995] assessing impulsiveness, risk readiness, and empathy and 3) Subjective Risk Intelligence Scale [Craparo et al., 2018] assessing negative attitude toward uncertainty, emotional stress vulnerability, imaginative capability, and problem-solving self-efficacy. Two groups of participants took part in the study: 1) 98 university students (Mage=19.71, SD=3.25; 72% female) and 2) 94 online participants (Mage=28.25, SD=8.25; 89% female). Online participants were recruited via social media. Students with high rationality rated their pleasure and dominance before and after choices as lower (ρ from -2.6 to -2.7, p < 0.05). Those with high levels of impulsivity rated their arousal lower before finding out their result (ρ from 2.5 - 3.7, p < 0.05), while also rating their dominance as low (ρ from -3 to -3.7, p < 0.05). Students prone to risk-rated their pleasure and arousal before and after higher (ρ from 2.5 - 3.6, p < 0.05). High empathy was positively correlated with arousal after learning the result. High emotional stress vulnerability positively correlates with arousal and pleasure after the choice (ρ from 3.9 - 5.7, p < 0.05). Negative attitude to uncertainty is correlated with high anticipatory and reactive arousal (ρ from 2.7 - 5.7, p < 0.05). High imaginative capability correlates negatively with anticipatory and reactive dominance (ρ from - 3.4 to - 4.3, p < 0.05). Pleasure (.492), arousal (.590), and dominance (.551) before and after the result were positively correlated. Higher predictions positively correlated with reactive pleasure and arousal. In a riskier scenario (6/8 chances to win), anticipatory arousal was negatively correlated with the pleasure emotion (-.326) and vice versa (-.265). Correlations occur regardless of the roulette outcome. In conclusion, risk-taking behaviors are linked not only to personality traits but also to anticipatory emotions and affect in a modeled casino setting. Acknowledgment: The study was supported by the Russian Foundation for Basic Research, project 19-29-07069.

Keywords: anticipatory emotions, casino game, risk taking, impulsiveness

Procedia PDF Downloads 116

Authors: Bharatendra Rai

Abstract:

Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

Procedia PDF Downloads 303

Authors: Eun Kyung Kim, Kyehan Rhee

Abstract:

Viscoelastic wall properties of the arterial plaques change as the disease progresses, and estimation of wall viscoelasticity can provide a valuable assessment tool for plaque rupture prediction. Cross section of the stenotic coronary artery was modeled based on the IVUS image, and the finite element analysis was performed to get wall deformation under pulsatile pressure. The effects of viscoelastic parameters of the plaque on luminal diameter variations were explored. The result showed that decrease of viscous effect reduced the phase angle between the pressure and displacement waveforms, and phase angle was dependent on the viscoelastic properties of the wall. Because viscous effect of tissue components could be identified using the phase angle difference, wall deformation waveform analysis may be applied to predict plaque wall composition change and vascular wall disease progression.

Keywords: atherosclerotic plaque, diameter variation, finite element method, viscoelasticity

Procedia PDF Downloads 205

Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

Abstract:

This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

Procedia PDF Downloads 351

Authors: Li Zhang, Yuehong Su

Abstract:

Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.

Keywords: neural network, bended lightpipe, transmittance, Photopia

Procedia PDF Downloads 136

Authors: Benjamin Leiby, Darryl Ahner

Abstract:

This study demonstrates an alternative stochastic imputation approach for large datasets when preferred commercial packages struggle to iterate due to numerical problems. A large country conflict dataset motivates the search to impute missing values well over a common threshold of 20% missingness. The methodology capitalizes on correlation while using model residuals to provide the uncertainty in estimating unknown values. Examination of the methodology provides insight toward choosing linear or nonlinear modeling terms. Static tolerances common in most packages are replaced with tailorable tolerances that exploit residuals to fit each data element. The methodology evaluation includes observing computation time, model fit, and the comparison of known values to replaced values created through imputation. Overall, the country conflict dataset illustrates promise with modeling first-order interactions while presenting a need for further refinement that mimics predictive mean matching.

Keywords: correlation, country conflict, imputation, stochastic regression

Procedia PDF Downloads 104

Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

Abstract:

As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

Procedia PDF Downloads 495

Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

Abstract:

This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling

Procedia PDF Downloads 375

Authors: Belkacem Laimouche

Abstract:

With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

Procedia PDF Downloads 90

Authors: Debesh R. Roy

Abstract:

The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP as proposed by A. D. Becke along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: atomic clusters, density functional theory, jellium model, magic clusters, smart nanomaterials

Procedia PDF Downloads 511

Authors: M. Khalfa, H. Khachai, F. Chiker, K. Bougherara, R. Khenata, G. Murtaza, M. Harmel

Abstract:

A theoretical study of structural, elastic, electronic and thermodynamic properties of Fe2VX, (with X = Al and Ga), were studied by means of the full-relativistic version of the full-potential augmented plane wave plus local orbitals method. For exchange and correlation potential we used both generalized-gradient approximation (GGA) and local-density approximation (LDA). Our calculated ground state properties like as lattice constants, bulk modulus and elastic constants appear more accurate when we employed the GGA rather than the LDA approximation, and these results agree very well with the available experimental and theoretical data. Further, prediction of the thermal effects on some macroscopic properties of Fe2VAl and Fe2VGa are given in this paper using the quasi-harmonic Debye model in which the lattice vibrations are taken into account. We have obtained successfully the variations of the primitive cell volume, volume expansion coefficient, heat capacities and Debye temperature with pressure and temperature in the ranges of 0–40 GPa and 0–1500 K.

Keywords: full Heusler, FP-LAPW, electronic properties, thermal properties

Procedia PDF Downloads 475

Authors: Ramalan Musa Yerima

Abstract:

The paper titled “loading by number” explained a strategy developed recently by Zonal Commanding Officer of the Federal Road Safety Corps of Nigeria, covering Sokoto, Kebbi and Zamfara States of Northern Nigeria. The strategy is aimed at reducing competition, which will invariably leads to the reduction in speed, reduction in dangerous driving, reduction in crash rate, reduction in injuries, reduction in property damages and reduction in death through road traffic crashes (RTC). This research paper presents a study focused on enhancing the safety of commercial vehicles. The background of this study highlights the alarming statistics related to commercial vehicle crashes in Nigeria with focus on Sokoto, Kebbi and Zamfara States, which often result in significant damage to property, loss of lives, and economic costs. The significance and aims is to investigate and propose effective strategy to enhance the safety of commercial vehicles. The study recognizes the pressing need for heightened safety measures in commercial transportation, as it impacts not only the well-being of drivers and passengers but also the overall public safety. To achieve the objectives, an examination of accident data, including causes and contributing factors, was performed to identify critical areas for improvement. The major finding of the study reveals that when competition comes into play within the realm of commercial driving, it has detrimental effects on road safety and resource management. Commercial drivers are pushed to complete their routes quickly, deliver goods on time or they pushed themselves to arrive quickly for more passengers and new contracts. This competitive environment, fuelled by internal and external pressures such as tight deadlines, poverty and greed, often leads to sad endings. The study recommend that if a strategy called loading by number is integrated with other multiple safety measures such as driver training programs, regulatory enforcement, and infrastructure improvements, commercial vehicle safety can be significantly enhanced. "Loading by Number” approach is design to ensure that the sequence of departure of drivers from motor park ‘A’ would be communicated to motor park officials of park ‘B’, which would be considered sequentially when giving them returning passengers, regardless of the first to arrive. In conclusion, this paper underscores the significance of improving the safety measures of commercial vehicles, as they are often larger and heavier than other vehicles on the road. Whenever they are involved in accidents, the consequences can be more severe. Commercial vehicles are also frequently involved in long-haul or interstate transportation, which means they cover longer distances and spend more time on the road. This increased exposure to driving conditions increases the probability of accidents occurring. By implementing the suggested measures, policymakers, transportation authorities, and industry stakeholders can work collectively towards ensuring a safer commercial transportation system.

Keywords: commercial, safety, strategy, transportation

Procedia PDF Downloads 43

Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

Abstract:

Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

Procedia PDF Downloads 533

Authors: Nikolaos Simantiris, Markos Avlonitis

Abstract:

This work builds a simulation platform, modeling the spatial diffusion of the invasive species Callinectes sapidus (blue crab) as a random walk, incorporating also generation, fatality, and fishing rates modeling the time evolution of its population. Antinioti lagoon in West Greece was used as a testbed for applying the simulation model. Field measurements from June 2020 to June 2021 on the lagoon’s setting, bathymetry, and blue crab juveniles provided the initial population simulation of blue crabs, as well as biological parameters from the current literature were used to calibrate simulation parameters. The scope of this study is to render the authors able to predict the evolution of the blue crab population in confined environments of the Ionian Islands region in West Greece. The first result of the simulation experiments shows the possibility for a robust prediction for blue crab population evolution in the Antinioti lagoon.

Keywords: antinioti lagoon, blue crab, stochastic simulation, random walk

Procedia PDF Downloads 206

Authors: Ramalan Musa Yerima

Abstract:

The paper titled “Loading by number” explained a strategy developed recently by the Zonal Commanding Officer of the Federal Road Safety Corps of Nigeria, covering Sokoto, Kebbi and Zamfara States of Northern Nigeria. The strategy is aimed at reducing competition, which will invariably lead to a reduction in speed, reduction in dangerous driving, reduction in crash rate, reduction in injuries, reduction in property damages and reduction in death through road traffic crashes (RTC). This research paper presents a study focused on enhancing the safety of commercial vehicles. The background of this study highlights the alarming statistics related to commercial vehicle crashes in Nigeria with a focus on Sokoto, Kebbi and Zamfara States, which often result in significant damage to property, loss of lives, and economic costs. The significance and aims is to investigate and propose an effective strategy to enhance the safety of commercial vehicles. The study recognizes the pressing need for heightened safety measures in commercial transportation, as it impacts not only the well-being of drivers and passengers but also the overall public safety. To achieve the objectives, an examination of accident data, including causes and contributing factors, was performed to identify critical areas for improvement. The major finding of the study reveals that when competition comes into play within the realm of commercial driving, it has detrimental effects on road safety and resource management. Commercial drivers are pushed to complete their routes quickly and deliver goods on time, or they push themselves to arrive quickly for more passengers and new contracts. This competitive environment, fuelled by internal and external pressures such as tight deadlines, poverty and greed, often leads to sad endings. The study recommends that if a strategy called loading by number is integrated with other multiple safety measures, such as driver training programs, regulatory enforcement, and infrastructure improvements, commercial vehicle safety can be significantly enhanced. "Loading by Number” approach is designed to ensure that the sequence of departure of drivers from the motor park ‘A’ would be communicated to motor park officials of park ‘B’, which would be considered sequentially when giving them returning passengers, regardless of the first to arrive. In conclusion, this paper underscores the significance of improving the safety measures of commercial vehicles, as they are often larger and heavier than other vehicles on the road. Whenever they are involved in accidents, the consequences can be more severe. Commercial vehicles are also frequently involved in long-haul or interstate transportation, which means they cover longer distances and spend more time on the road. This increased exposure to driving conditions increases the probability of accidents occurring. By implementing the suggested measures, policymakers, transportation authorities, and industry stakeholders can work collectively toward ensuring a safer commercial transportation system.

Keywords: commercial, safety, strategy, transport

Procedia PDF Downloads 46

Authors: Umit Duru

Abstract:

The Soil and Water Assessment Tool (SWAT) was tested for prediction of water balance and sediment yield in the Ankara gauged basin, Turkey. The overall objective of this study was to evaluate the performance and applicability of the SWAT in this region of Turkey. Thirteen years of monthly stream flow, and suspended sediment, data were used for calibration and validation. This research assessed model performance based on differences between observed and predicted suspended sediment yield during calibration (1987-1996) and validation (1982-1984) periods. Statistical comparisons of suspended sediment produced values for NSE (Nash Sutcliffe efficiency), RE (relative error), and R² (coefficient of determination), of 0.81, -1.55, and 0.93, respectively, during the calibration period, and NSE, RE (%), and R² of 0.77, -2.61, and 0.87, respectively, during the validation period. Based on the analyses, SWAT satisfactorily simulated observed hydrology and sediment yields and can be used as a tool in decision making for water resources planning and management in the basin.

Keywords: calibration, GIS, sediment yield, SWAT, validation

Procedia PDF Downloads 261

Authors: Omar Hussein El Ayadi, EmadY. El-Mansouri, Mohamed B. Dozan

Abstract:

Production oil process require specific details i.e. oil composition. Generally, types of oil or differentiation between reservoir fluids depend specifically on composition. The main purpose of this study is to correlate and predict the Libyan oil (reservoir fluid and residual) composition utilizing tri-angle-coordinate plots discovered and tasked with Excel. The reservoir fluid data (61 old + 47 new), the residual oil data (33 new) collected from most of Libyan reservoirs were correlated with each others. Moreover, find a relation between stock tank molecular weight and stock tank oil gravity (oAPI), the molecular weight oh (C7+) versus residual oil gravity (oAPI). The average value of every oil composition was estimated including non-hydrocarbon (H2S, CO2, and N2). Nevertheless, the isomers (i-…) and normal (n-…) structure of (C4) and (C5) were also obtained. The summary of the conclusion is; utilizing excel Microsoft office to draw triangle coordinates to find two unknown component if only one is known. However, it is recommended to use the obtained oil composition plots and equations for any oil composition dependents i.e. optimum separator pressure.

Keywords: PVT, phase behavior, petroleum, chemical engineering

Procedia PDF Downloads 494

Authors: Sasitharan Ambicapathy, J. Vignesh, P. Sivaraj, Godfrey Derek Sams, K. Sabarinath, V. R. Sanal Kumar

Abstract:

The external flow simulation of a flying car at take off phase is a daunting task owing to the fact that the prediction of the transient unsteady flow features during its deployment phase is very complex. In this paper 3D numerical simulations of external flow of Ferrari F430 proposed flying car with different NACA 9618 rectangular wings have been carried. Additionally, the aerodynamics characteristics have been generated for optimizing its geometry for achieving the minimum take off velocity with better overall performance in both road and air. The three-dimensional standard k-omega turbulence model has been used for capturing the intrinsic flow physics during the take off phase. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations is employed. Through the detailed parametric analytical studies we have conjectured that Ferrari F430 flying car facilitated with high wings having three different deployment histories during the take off phase is the best choice for accomplishing its better performance for the commercial applications.

Keywords: aerodynamics of flying car, air taxi, negative lift, roadable airplane

Procedia PDF Downloads 405