Search results for: corrosion prediction ductile fracture

Authors: Jia-Shiun Chen, Quoc-Viet Huynh

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This work develops a flexible-body dynamic model of an all-terrain vehicle (ATV), capable of recovering dynamic stresses while the ATV travels on random bumpy roads. The fatigue life of components is forecasted as well. While considering the interaction between dynamic forces and structure deformation, the proposed model achieves a highly accurate structure stress prediction and fatigue life prediction. During the simulation, stress time history of the ATV structure is retrieved for life prediction. Finally, the hot sports of the ATV frame are located, and the frame life for combined road conditions is forecasted, i.e. 25833.6 hr. If the usage of vehicle is eight hours daily, the total vehicle frame life is 8.847 years. Moreover, the reaction force and deformation due to the dynamic motion can be described more accurately by using flexible body dynamics than by using rigid-body dynamics. Based on recommendations made in the product design stage before mass production, the proposed model can significantly lower development and testing costs.

Keywords: flexible-body dynamics, veicle, dynamics, fatigue, durability

Procedia PDF Downloads 394

Authors: R. C. Sharma, Rishabh Bansal, Prajwal Menon, Manoj K. Sharma

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Silicon-air battery is highly promising for electric vehicles due to its high theoretical energy density (8470 Whkg⁻¹) and its discharge products are non-toxic. For the first time, pure silicon and germanium powders are used as anode material. Nickel wire meshes embedded with charcoal and manganese dioxide powder as cathode and concentrated potassium hydroxide is used as electrolyte. Voltage-time curves have been presented in this study for pure silicon and germanium powder and 5% and 10% germanium with silicon powder. Silicon powder cell assembly gives a stable voltage of 0.88 V for ~20 minutes while Si-Ge provides cell voltage of 0.80-0.76 V for ~10-12 minutes, and pure germanium cell provides cell voltage 0.80-0.76 V for ~30 minutes. The cell voltage is higher for concentrated (10%) sodium hydroxide solution (1.08 V) and it is stable for ~40 minutes. A sharp decrease in cell voltage beyond 40 min may be due to rapid corrosion.

Keywords: Silicon-air battery, Germanium-air battery, voltage-time curve, open circuit voltage, Anodic corrosion

Procedia PDF Downloads 237

Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

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Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: palm oil, fatty acid, NIRS, regression

Procedia PDF Downloads 506

Authors: B. Ramakrishna, S. Sivamurthy Reddy

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The various types of aggregates such as granite, dolerite, Quartzite, dolomitic limestone, limestone and river gravel were used to produce the concrete with 28-day target compressive strength of 35, 60, and 80 Mpa. The compressive strength of concrete, as well as aggregates, was measured to study the effect of rupture probability of aggregate on the fracture surface of the concrete. Also, the petrographic studies were carried out to study the texture, type of minerals present and their relative proportions in various types of aggregates. The concrete of various grades produced with the same aggregate has shown a rise in RPCA with strength. However, the above relationship has ceased to exist in the concretes of the same grade, made of different types of aggregates. The carbonate aggregates namely Limestone and Dolomitic limestone have produced concrete with higher RPCA irrespective of the strength of concrete. The mode of origin, texture and mineralogical composition of aggregates have a significant impact on their pulse velocity and thereby the pulse velocity of concrete.

Keywords: RPCA, DL, G, LS, RG

Procedia PDF Downloads 294

Authors: Neeraj Malhotra, Ramya Shenoy

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Objective: To assess the effect of clinical parameters (bonding agent, preparation design & storage media) on the strength of reattached anterior tooth fragment. Methodology: This is a systematic review and meta-analysis for articles referred from MEDLINE, PUBMED, and GOOGLE SCHOLAR. The articles on tooth reattachment and clinical factors affecting fracture strength/bond strength/fracture resistance of the reattached tooth fragment in anterior teeth and published in English from 1999 to 2016 were included for final review. Results: Out of 120 shortlisted articles, 28 articles were included for the systematic review and meta-analysis based on 3 clinical parameters i.e. bonding agent, tooth preparation design & storage media. Forest plot & funnel plots were generated based on individual clinical parameter and their effect on strength of reattached anterior tooth fragment. Results based on analysis suggest combination of both conclusive evidence favoring the experimental group as well as in-conclusive evidence for individual parameter. Conclusion: There is limited evidence as there are fewer articles supporting each parameter in human teeth. Bonding agent had showed better outcome in selected studies.

Keywords: bonding agent, bond strength, fracture strength, preparation design, reattachment, storage media

Procedia PDF Downloads 178

Authors: D. I. George Amalarethinam, A. Emima

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Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM.

Keywords: classification technique, data mining, EDM methods, prediction methods

Procedia PDF Downloads 117

Authors: Osung Im, Neha Yadav, Eui Hoon Lee, Joong Hoon Kim

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Artificial Neural Network (ANN) approach is commonly used in lots of fields for forecasting. In water resources engineering, forecast of water level or inflow of reservoir is useful for various kind of purposes. Due to advantages of ANN, many papers were written for inflow prediction in river networks, but in this study, ANN is used in urban sewer networks. The growth of severe rain storm in Korea has increased flood damage severely, and the precipitation distribution is getting more erratic. Therefore, effective pump operation in pump station is an essential task for the reduction in urban area. If real time inflow of pump station reservoir can be predicted, it is possible to operate pump effectively for reducing the flood damage. This study used ANN model for pump station reservoir inflow prediction using upstream sewer depth data. For this study, rainfall events, sewer depth, and inflow into Banpo pump station reservoir between years of 2013-2014 were considered. Feed – Forward Back Propagation (FFBF), Cascade – Forward Back Propagation (CFBP), Elman Back Propagation (EBP) and Nonlinear Autoregressive Exogenous (NARX) were used as ANN model for prediction. A comparison of results with ANN model suggests that ANN is a powerful tool for inflow prediction using the sewer depth data.

Keywords: artificial neural network, forecasting, reservoir inflow, sewer depth

Procedia PDF Downloads 317

Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

Procedia PDF Downloads 163

Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Triphonia Ngailo

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Rainfall is a major climatic parameter affecting many sectors such as health, agriculture and water resources. Its quantitative prediction remains a challenge to weather forecasters although numerical weather prediction models are increasingly being used for rainfall prediction. The performance of six convective parameterization schemes, namely the Kain-Fritsch scheme, the Betts-Miller-Janjic scheme, the Grell-Deveny scheme, the Grell-3D scheme, the Grell-Fretas scheme, the New Tiedke scheme of the weather research and forecast (WRF) model regarding quantitative rainfall prediction over Uganda is investigated using the root mean square error for the March-May (MAM) 2013 season. The MAM 2013 seasonal rainfall amount ranged from 200 mm to 900 mm over Uganda with northern region receiving comparatively lower rainfall amount (200–500 mm); western Uganda (270–550 mm); eastern Uganda (400–900 mm) and the lake Victoria basin (400–650 mm). A spatial variation in simulated rainfall amount by different convective parameterization schemes was noted with the Kain-Fritsch scheme over estimating the rainfall amount over northern Uganda (300–750 mm) but also presented comparable rainfall amounts over the eastern Uganda (400–900 mm). The Betts-Miller-Janjic, the Grell-Deveny, and the Grell-3D underestimated the rainfall amount over most parts of the country especially the eastern region (300–600 mm). The Grell-Fretas captured rainfall amount over the northern region (250–450 mm) but also underestimated rainfall over the lake Victoria Basin (150–300 mm) while the New Tiedke generally underestimated rainfall amount over many areas of Uganda. For deterministic rainfall prediction, the Grell-Fretas is recommended for rainfall prediction over northern Uganda while the Kain-Fritsch scheme is recommended over eastern region.

Keywords: convective parameterization schemes, March-May 2013 rainfall season, spatial variation of parameterization schemes over Uganda, WRF model

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

Procedia PDF Downloads 392

Authors: Ali Haghiri

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This research has been to investigate the cause of the stress corrosion cracking on dryer equipment (2DR-1745 and DR-1402) in Shahid Tondguyan Petrochemical Company (STPC). These dryers are as a drying powder Terphetalic acid in CTA2 and CTA1 unit. After passing through RVF equipment, wet cake moisture content of about 14% and temperature of 90C changed into a dry cake with a moisture content of less than 0.1% and the final temperature of about 140C and sent out Final Silo (FS-1820). After the declaration of the operation department concerning the observation of acid leakage under the primary insulation was decided that at the first opportunity, this issue must be investigated. So, after the shutdown of a unit at the date 2012/10/20 (2DR-1745) and 2021/11/24 (DR-1402) and after washing the dryer wall, insulation around the wall opened and it was found to crack and leakage from some points.

Keywords: stress corrosion cracking, residual stress, austenitic stainless steel, Br- ion

Procedia PDF Downloads 161

Authors: Abayomi T. Ogunjimi, Gbenga Alebiowu

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Mechanical properties of paracetamol tablets containing Neem (Azadirachta indica) gum were compared with standard Acacia gum BP as binder. Two dimensionless binding quantities BEN and BEC were used in assessing the influence of binder type on two mechanical properties, Tensile Strength (TS) and Brittle Fracture Index (BFI). The two quantities were also used to assess the influence of relative density and binder concentration on TS and BFI as well as compare Binding Efficiencies (BE). The result shows that TS is dependent on relative density, binder type and binder concentration while BFI is dependent on the binder type and binder concentration; and that although, the inclusion of NMG in a paracetamol tablet formulation may not enhance the TS of the tablets produced, however it will decrease the tendency of the tablets to cap or laminate. This work concludes that BEN may be useful in quantitative assessment while BEC may be appropriate for qualitative assessment.

Keywords: binding efficiency, brittle fracture index, dimensionless binding, tensile strength

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Authors: Viranshu Kumar, Hitesh Arora, Pradeep Joshi

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SS 304 is Austenitic stainless steel with Chromium and Nickel as basic constituents. It has excellent corrosion resistance properties and very good weldability. Austenitic stainless steels have superior mechanical properties at high temperatures and are used extensively in a range of applications. SS 304L has wide applications in various industries viz. Nuclear, Pharmaceutical, marine, chemical etc. due to its excellent applications and ease of joining this material has become very popular for fabrication as well as weld surfacing. Austenitic stainless steels have a tendency to form chromium depleted zones at the grain boundaries during welding and heat treatment, where chromium combines with available carbon in the vicinity of the grain boundaries, to produce an area depleted in chromium, and thus becomes susceptible to intergranular corrosion. This phenomenon is known as sensitization.

Keywords: sensitization, SS 304, GTAW, mechanical properties, carbideprecipitationHAZ, microstructure, micro hardness, tensile strength

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Authors: Vatsal Patel, Niraj Shah

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The aim of the research reported in this paper is to assess the Strength and durability performance of High Performance Concrete containing different percentages of waste marble powder produced from marble industry. Concrete mixes possessing a target mean compressive strength of 70MPa were prepared with 0%,5%,10%,15% and 20% cement replacement by waste marble powder with W/B =0.33. More specifically, the compressive strength, flexural strength, chloride penetration, sorptivity and accelerated corrosion were determined. Concrete containing 10% waste marble powder proved to have best Mechanical and durability properties than other mixtures made with binary blends. However, poorer performance was noticeable when replacement percentage was higher. The replacement of Waste Marble Powder will have major environmental benefits.

Keywords: durability, high performance concrete, marble waste powder, sorptivity, accelerated corrosion

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Authors: Jinyoung Choi, Hyun-A Kim, Sunmook Lee

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The effects of environmental stress factors such as storage conditions on the deterioration phenomenon and the characteristic of the display glass were studied. In order to investigate the effect of chemical stress on the glass during the period of storage, the respective components of commercial glass were first identified by XRF (X-ray fluorescence). The glass was exposed in the acid, alkali, neutral environment for about one month. Thin film formed on the glass surface was analyzed by XRD (X-ray diffraction) and FT-IR (Fourier transform infrared). The degree of corrosion and the rate of deterioration of each sample were confirmed by measuring the concentrations of silicon, calcium and chromium with ICP-OES (Inductively coupled plasma-optical emission spectrometry). The optical properties of the glass surface were confirmed by SEM (Scanning electron microscope) before and after the treatment. Acknowledgement—The authors gratefully acknowledge the financial support from the Ministry of Trade, Industry and Energy (Grant Number: 10076817)

Keywords: corrosion, degradation test, display glass, environmental stress factor

Procedia PDF Downloads 459

Authors: C. Venkataraman B. E., J. Nagarajan B. E., V. Srinivasan M. Tech

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For a better understanding on sulfide stress corrosion cracking, a theoretical approach based on crystal structure, molecule behavior, flow of electrons and electrochemical reaction is developed. Its impact on different materials such as carbon steel, low alloy, alloy for sour (H2S) environments is studied. This paper describes the theories on various disaster and failures occurred in the industry by Stress Corrosion Cracking (SCC). Parameters such as pH of process fluid, partial pressure of CO2, O2, Chlorine, effect of internal pressure (crystal structure deformation by stress), and external environment condition are considered. An analytical line graph is then created for process fluid parameter verses time, temperature, induced/residual stress due to local pressure build-up. By comparison with the load test result of NACE and ASTM, it is possible to predict and simplify the control of SCC by use of materials like ferritic, Austenitic material in the oil and gas & petroleum industries.

Keywords: crystal structure deformation, failure assessment, alloy-environment combination, H2S

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Authors: Sumit Sen, Sohan Khedekar, Umang Shinde, Shivam Bhargava

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This study has been undertaken to investigate whether the deep learning models are able to predict the future stock prices by training the model with the historical stock price data. Since this work required time series analysis, various models are present today to perform time series analysis such as Recurrent Neural Network LSTM, ARIMA and Facebook Prophet. Applying these models the movement of stock price of stocks are predicted and also tried to provide the future prediction of the stock price of a stock. Final product will be a stock price prediction web application that is developed for providing the user the ease of analysis of the stocks and will also provide the predicted stock price for the next seven days.

Keywords: Autoregressive Integrated Moving Average, Deep Learning, Long Short Term Memory, Time-series

Procedia PDF Downloads 141

Authors: Jinge Liu, Shuyuan Min, Bingchuan Liu, Bangzhao Yin, Bo Peng, Peng Wen, Yun Tian

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WE43 magnesium alloy can be additively manufactured via laser powder bed fusion (LPBF) for biodegradable applications, but the as-built WE43 exhibits an excessively rapid corrosion rate. High-temperature oxidation (HTO) was performed on the as-built WE43 to improve its biodegradation behavior. A sandwich structure including an oxide layer at the surface, a transition layer in the middle, and the matrix was generated influenced by the oxidation reaction and diffusion of RE atoms when heated at 525 ℃for 8 hours. The oxide layer consisted of Y₂O₃ and Nd₂O₃ oxides with a thickness of 2-3 μm. The transition layer is composed of α-Mg and Y₂O₃ with a thickness of 60-70 μm, while Mg24RE5 could be observed except α-Mg and Y₂O₃. The oxide layer and transition layer appeared to have an effective passivation effect. The as-built WE43 lost 40% weight after the in vitro immersion test for three days and finally broke into debris after seven days of immersion. The high-temperature oxidation samples kept the structural integrity and lost only 6.88 % weight after 28-day immersion. The corrosion rate of HTO samples was significantly controlled, which improved the biocompatibility of the as-built WE43 at the same time. The samples after HTO had better osteogenic capability according to ALP activity. Moreover, as built WE43 performed unqualified in cell adhesion and hemolytic test due to its excessively rapid corrosion rate. While as for HTO samples, cells adhered well, and the hemolysis ratio was only 1.59%.

Keywords: laser powder bed fusion, biodegradable metal, high temperature oxidation, biodegradation behavior, WE43

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Authors: Salman Mohamadi, Seyed Mohammad Ali Tayaranian Hosseini, Hamidreza Amindavar

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In this paper, we provide a procedure to analyze and model EEG (electroencephalogram) signal as a time series using ARIMA-GARCH to predict an epileptic attack. The heteroskedasticity of EEG signal is examined through the ARCH or GARCH, (Autore- gressive conditional heteroskedasticity, Generalized autoregressive conditional heteroskedasticity) test. The best ARIMA-GARCH model in AIC sense is utilized to measure the volatility of the EEG from epileptic canine subjects, to forecast the future values of EEG. ARIMA-only model can perform prediction, but the ARCH or GARCH model acting on the residuals of ARIMA attains a con- siderable improved forecast horizon. First, we estimate the best ARIMA model, then different orders of ARCH and GARCH modelings are surveyed to determine the best heteroskedastic model of the residuals of the mentioned ARIMA. Using the simulated conditional variance of selected ARCH or GARCH model, we suggest the procedure to predict the oncoming seizures. The results indicate that GARCH modeling determines the dynamic changes of variance well before the onset of seizure. It can be inferred that the prediction capability comes from the ability of the combined ARIMA-GARCH modeling to cover the heteroskedastic nature of EEG signal changes.

Keywords: epileptic seizure prediction , ARIMA, ARCH and GARCH modeling, heteroskedasticity, EEG

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Authors: Ahmet Yonetken, Ayhan Erol

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The microstructure, mechanical properties and corrosion characteristics of Ni plated %10Al2O3-%40Co-%20Cr and %10Ti powders were investigated using specimens produced by tube furnace sintering at 800-1200°C temperature. A uniform nickel layer on Al2O3-Co-Cr and Ti powders was deposited prior to sintering using electroless plating technique. A composite consisting of quintet additions, a metallic phase, Ti,Cr and Co including a ceramic phase, alumina, within a matrix of Ni has been prepared under Ar shroud and then tube furnace sintered. XRD, SEM (Scanning Electron Microscope), corrosion behavior in acidic media were investigated to characterize the properties of the specimens. Experimental results carried out for composition (%10Al2O3-%40Co-%20Cr- %10Ti)20Ni at 1200°C suggest that the best properties as 312.18HV were obtained at 1200°C.

Keywords: sintering, intermetallic, Electroless nickel plating, composite

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Authors: Jeries J. Abou-Hanna

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Several techniques exist for determining stress-intensity factors in linear elastic fracture mechanics analysis. These techniques are based on analytical, numerical, and empirical approaches that have been well documented in literature and engineering handbooks. However, not all techniques share the same merit. In addition to overly-conservative results, the numerical methods that require extensive computational effort, and those requiring copious user parameters hinder practicing engineers from efficiently evaluating stress-intensity factors. This paper investigates the prospects of reducing the complexity and required variables to determine stress-intensity factors through the utilization of the stress gradient and a weighting function. The heart of this work resides in the understanding that fracture emanating from stress concentration locations cannot be explained by a single maximum stress value approach, but requires use of a critical volume in which the crack exists. In order to understand the effectiveness of this technique, this study investigated components of different notch geometry and varying levels of stress gradients. Two forms of weighting functions were employed to determine stress-intensity factors and results were compared to analytical exact methods. The results indicated that the “exponential” weighting function was superior to the “absolute” weighting function. An error band +/- 10% was met for cases ranging from a steep stress gradient in a sharp v-notch to the less severe stress transitions of a large circular notch. The incorporation of the proposed method has shown to be a worthwhile consideration.

Keywords: fracture mechanics, finite element method, stress intensity factor, stress gradient

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Authors: Sarra Khelifi, Youcef Guerabli, Ahcene Boumaiza

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Advances in techniques for measuring individual crystallographic orientations have made it possible to investigate the role of local crystallography during the plastic deformation of materials. In this study, the change in crystallographic orientation distribution during deformation by deep drawing in carbon steel has been investigated in order to understand their role in propagation and arrest of crack. The results show that the change of grain orientation from initial recrystallization texture components of {111}<112> to deformation orientation {111}<110> incites the initiation and propagation of cracks in the region of {111}<112> small grains. Moreover, the misorientation profile and local orientation are analyzed in detail to discuss the change from {111}<112> to {111}<110>. The deformation of the grain with {111}<110> orientation is discussed in terms of stops of the crack in carbon steel during drawing. The SEM-EBSD technique was used to reveal the change of orientation; XRD was performed for the characterization of the global evolution of texture for deformed samples.

Keywords: fracture, heterogeneity, misorientation profile, stored energy

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Authors: Kisan Sarda, Bhavika Shingote

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This paper aims to evaluate regression modelling for prediction of Energy storage of solar photovoltaic (PV) system using Semi parametric regression techniques because there are some parameters which are known while there are some unknown parameters like humidity, dust etc. Here irradiation of solar energy is different for different places on the basis of Latitudes, so by finding out areas which give more storage we can implement PV systems at those places and our need of energy will be fulfilled. This regression modelling is done for daily, monthly and seasonal prediction of solar energy storage. In this, we have used R modules for designing the algorithm. This algorithm will give the best comparative results than other regression models for the solar PV cell energy storage.

Keywords: semi parametric regression, photovoltaic (PV) system, regression modelling, irradiation

Procedia PDF Downloads 381

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

Procedia PDF Downloads 146

Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

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Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

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Authors: E. A. Krasikov

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As the service life of an operating nuclear power plant (NPP) increases, the potential misunderstanding of the degradation of aging components must receive more attention. Integrity assurance analysis contributes to the effective maintenance of adequate plant safety margins. In essence, the reactor pressure vessel (RPV) is the key structural component determining the NPP lifetime. Environmentally induced cracking in the stainless steel corrosion-preventing cladding of RPV’s has been recognized to be one of the technical problems in the maintenance and development of light-water reactors. Extensive cracking leading to failure of the cladding was found after 13000 net hours of operation in JPDR (Japan Power Demonstration Reactor). Some of the cracks have reached the base metal and further penetrated into the RPV in the form of localized corrosion. Failures of reactor internal components in both boiling water reactors and pressurized water reactors have increased after the accumulation of relatively high neutron fluences (5´1020 cm–2, E>0,5MeV). Therefore, in the case of cladding failure, the problem arises of hydrogen (as a corrosion product) embrittlement of irradiated RPV steel because of exposure to the coolant. At present when notable progress in plasma physics has been obtained practical energy utilization from fusion reactors (FR) is determined by the state of material science problems. The last includes not only the routine problems of nuclear engineering but also a number of entirely new problems connected with extreme conditions of materials operation – irradiation environment, hydrogenation, thermocycling, etc. Limiting data suggest that the combined effect of these factors is more severe than any one of them alone. To clarify the possible influence of the in-service synergistic phenomena on the FR structural materials properties we have studied hydrogen-irradiated steel interaction including alternating hydrogenation and heat treatment (annealing). Available information indicates that the life of the first wall could be expanded by means of periodic in-place annealing. The effects of neutron fluence and irradiation temperature on steel/hydrogen interactions (adsorption, desorption, diffusion, mechanical properties at different loading velocities, post-irradiation annealing) were studied. Experiments clearly reveal that the higher the neutron fluence and the lower the irradiation temperature, the more hydrogen-radiation defects occur, with corresponding effects on the steel mechanical properties. Hydrogen accumulation analyses and thermal desorption investigations were performed to prove the evidence of hydrogen trapping at irradiation defects. Extremely high susceptibility to hydrogen embrittlement was observed with specimens which had been irradiated at relatively low temperature. However, the susceptibility decreases with increasing irradiation temperature. To evaluate methods for the RPV’s residual lifetime evaluation and prediction, more work should be done on the irradiated metal–hydrogen interaction in order to monitor more reliably the status of irradiated materials.

Keywords: hydrogen, radiation, stability, structural steel

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Authors: Ziba Talaeizadeh, Taghi Ebadi

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Hospitals and medical centers generate a wide array of infectious waste on a daily basis, leading to pressing environmental concerns associated with proper disposal. Disposable plastic items and spun-bond clothing, commonly made from polypropylene, pose a significant risk of disease transmission, necessitating specialized waste management strategies. Incorporating these materials into bituminous asphalt production offers a potential solution, as it can modify asphalt mixtures and reduce susceptibility to cracking. This study aims to assess the crack resistance of asphalt mixtures modified with hospital spun-bond waste. Asphalt mixtures were prepared using the Marshall method, with spun-bond waste added in varying proportions (5% to 20%). The Semi-Circular Bending (SCB) test was conducted to evaluate asphalt fracture behavior under Mode I loading at controlled speeds of 5, 20, and 50 millimeters per minute and an average temperature of 25°C. Parameters such as fracture energy (FE) and Crack Resistance Index (CRI) were quantified. The results indicate that the addition of 10% to 15% spun-bond polypropylene polymer enhances the performance of the modified mixture, resulting in an 18% increase in fracture energy and an 11% reduction in cracking stiffness compared to the control sample. Further investigations involving factors like compaction level, bitumen type, and aggregate grading are recommended to address medical waste management and mitigate asphalt pavement cracking issues.

Keywords: asphalt cracking, hospital waste, semi-circular bending test, spun-bond

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Authors: Tarek Sabri Duzan

Abstract:

Knowledge of the magnitude of Geo-pressures (Pore, Fracture & Over-burden pressures) is vital especially during drilling, completions, stimulations, Enhance Oil Recovery. Many times problems, like lost circulation could have been avoided if techniques for calculating Geo-pressures had been employed in the well planning, mud weight plan, and casing design. In this paper, we focused on the relationships between Geo-pressures and wave velocities (P-Wave (Vp) and S-wave (Vs)) in shallow Libyan carbonate reservoir in the western part of the Sirte Basin (Dahra F-Area). The data used in this report was collected from four new wells recently drilled. Those wells were scattered throughout the interested reservoir as shown in figure-1. The data used in this work are bulk density, Formation Mult -Tester (FMT) results and Acoustic wave velocities. Furthermore, Eaton Method is the most common equation used in the world, therefore this equation has been used to calculate Fracture pressure for all wells using dynamic Poisson ratio calculated by using acoustic wave velocities, FMT results for pore pressure, Overburden pressure estimated by using bulk density. Upon data analysis, it has been found that there is a linear relationship between Geo-pressures (Pore, Fracture & Over-Burden pressures) and wave velocities ratio (Vp/Vs). However, the relationship was not clear in the high-pressure area, as shown in figure-10. Therefore, it is recommended to use the output relationship utilizing the new seismic data for shallow carbonate reservoir to predict the Geo-pressures for future oil operations. More data can be collected from the high-pressure zone to investigate more about this area.

Keywords: bulk density, formation mult-tester (FMT) results, acoustic wave, carbonate shalow reservoir, d/jfield velocities

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Authors: Adhitya Mangala, Yobel

Abstract:

Bittuang geothermal prospect area located at Tana Toraja district, South Sulawesi. The geothermal system of the area related to Karua Volcano eruption product. This area has surface manifestation such as fumarole, hot springs, sinter silica and mineral alteration. Those prove that there are hydrothermal activities in the subsurface. However, the project and development of the area have not implemented yet. One of the important elements in geothermal exploration is to determine upflow and outflow zone. This information very useful to identify the target for geothermal wells and development which it is a risky task. The methods used in this research were Mercury (Hg) anomalies in soil, soil and manifestation temperature distribution and fault fracture density from 93 km² research area. Hg anomalies performed to determine the distribution of hydrothermal alteration. Soil and manifestation temperature distribution were conducted to estimate heat distribution. Fault fracture density (FFD) useful to determine fracture intensity and trend from surface observation. Those deliver Hg anomaly map, soil and manifestation temperature map that combined overlayed to fault fracture density map and geological map. Then, the conceptual model made from north – south, and east – west cross section to delineate upflow and outflow zone in this area. The result shows that upflow zone located in northern – northeastern of the research area with the increase of elevation and decrease of Hg anomalies and soil temperature. The outflow zone located in southern - southeastern of the research area which characterized by chloride, chloride - bicarbonate geothermal fluid type, higher soil temperature, and Hg anomalies. The range of soil temperature distribution from 16 – 19 °C in upflow and 19 – 26.5 °C in the outflow. The range of Hg from 0 – 200 ppb in upflow and 200 – 520 ppb in the outflow. Structural control of the area show northwest – southeast trend. The boundary between upflow and outflow zone in 1550 – 1650 m elevation. This research delivers the conceptual model with innovative methods that useful to identify a target for geothermal wells, project, and development in Bittuang geothermal prospect area.

Keywords: Bittuang geothermal prospect area, Hg anomalies, soil temperature, upflow and outflow zone

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Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

Abstract:

Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

Procedia PDF Downloads 554