Search results for: corrosion prediction ductile fracture

Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: Ajoy Kumar Das, Prasenjit Dey

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Heat transfer due to forced convection of copper water based nanofluid has been predicted by Artificial Neural network (ANN). The present nanofluid is formed by mixing copper nano particles in water and the volume fractions are considered here are 0% to 15% and the Reynolds number are kept constant at 100. The back propagation algorithm is used to train the network. The present ANN is trained by the input and output data which has been obtained from the numerical simulation, performed in finite volume based Computational Fluid Dynamics (CFD) commercial software Ansys Fluent. The numerical simulation based results are compared with the back propagation based ANN results. It is found that the forced convection heat transfer of water based nanofluid can be predicted correctly by ANN. It is also observed that the back propagation ANN can predict the heat transfer characteristics of nanofluid very quickly compared to standard CFD method.

Keywords: forced convection, square cylinder, nanofluid, neural network

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Authors: Maryam Kiani, Abdul Basit Kiani

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At larger scales, the performance of cementitious materials is impacted by processes occurring at the nanometer scale. These materials boast intricate hierarchical structures with random features that span from the nanometer to millimeter scale. It is fascinating to observe how the nanoscale processes influence the overall behavior and characteristics of these materials. By delving into and manipulating these processes, scientists and engineers can unlock the potential to create more durable and sustainable infrastructure and construction materials. It's like unraveling a hidden tapestry of secrets that hold the key to building stronger and more resilient structures. The present work employs simulations as the computational modeling methodology to predict mechanical properties for carbon/silica based cementitious materials at the molecular/nano scale level. Studies focused on understanding the effect of higher mechanical properties of cementitious materials with carbon silica nanoparticles via Material Studio materials modeling.

Keywords: nanomaterials, SiO₂, carbon black, mechanical properties

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Komol Phaisarn, Anuphan Suttimarn, Vitchanan Keawtong, Kittisak Thongyoun, Chaiyos Jamsawang

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This article is intended to analyze insurance information which contains information on the customer decision when purchasing life insurance pay package. The data were analyzed in order to present new customers with Life Insurance Perfect Pay package to meet new customers’ needs as much as possible. The basic data of insurance pay package were collect to get data mining; thus, reducing the scattering of information. The data were then classified in order to get decision model or decision tree using Algorithm C4.5 (J-48). In the classification, WEKA tools are used to form the model and testing datasets are used to test the decision tree for the accurate decision. The validation of this model in classifying showed that the accurate prediction was 68.43% while 31.25% were errors. The same set of data were then tested with other models, i.e. Naive Bayes and Zero R. The results showed that J-48 method could predict more accurately. So, the researcher applied the decision tree in writing the program used to introduce the product to new customers to persuade customers’ decision making in purchasing the insurance package that meets the new customers’ needs as much as possible.

Keywords: decision tree, data mining, customers, life insurance pay package

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Authors: Moustafa Osman

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The paper describes and analyses different good practice examples of protective levels, and initiatives actions (“framework conditions”) and encourages the uptake of environmental management systems (EMSs) to small and medium-sized enterprises (SMEs). Most of industries tend to take EMS as tools leading towards sustainability planning. The application of these tools has numerous environmental obligations that neither suggests decision nor recommends what a company should achieve ultimately. These set up clearly defined criteria to evaluate environmental protective action (EEPA) into sustainability indicators. The physical integration will evaluate how to incorporate traditional knowledge into baseline information, preparing impact prediction, and planning mitigation measures in monitoring conditions. Thereby efforts between the government, industry and community led protective action to concern with present needs for future generations, meeting the goal of sustainable development. The paper discusses how to set out distinct aspects of sustainable indicators and reflects inputs, outputs, and modes of impact on the environment.

Keywords: environmental management, sustainability, indicators, protective action

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Aleksandra Tepic-Horecki, Zdravko Sumic

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In this paper, the influence of six different phytochemical content (phenols, carotenoids, chlorophyll a, chlorophyll b, chlorophyll a + b and vitamin C) on antioxidant potential of Murai and Levistro lettuce varieties was evaluated. Variable selection was made by generalized pair correlation method (GPCM) as a novel ranking method. This method is used for the discrimination between two variables that almost equal correlate to a dependent variable. Fisher’s conditional exact and McNemar’s test were carried out. Established multiple linear (MLR) models were statistically evaluated. As the best phytochemicals for the antioxidant potential prediction, chlorophyll a, chlorophyll a + b and total carotenoids content stand out. This was confirmed through both GPCM and MLR, predictive ability of obtained MLR can be used for antioxidant potential estimation for similar lettuce samples. This article is based upon work from the project of the Provincial Secretariat for Science and Technological Development of Vojvodina (No. 114-451-347/2015-02).

Keywords: antioxidant activity, generalized pair correlation method, lettuce, regression analysis

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Authors: Chi-Yueh Hsu, Hsuan-Liang Hsu, Hsiu-Hui Chiang

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This study is to explore the relationship between the conspicuous consumption, leisure involvement and physical and mental health, and to understand the prediction of conspicuous consumption and leisure involvement to physical and mental health. The data was collected and analysed by purposive sampling, and the research objects were the dog walkers in Taiwan area. A total of 300 questionnaires were issued and after shaving the invalid questionnaire, a total of 246 valid samples were collected, and the effective rate was 82%.. The data were analyzed by correlation analysis and multiple stepwise regression analysis. The results showed that there was a significant correlation between conspicuous consumption and leisure involvement, and the conspicuous consumption and leisure involvement of dog walkers have a significant impact on physical and mental health, especially in self-expression, attractiveness and centrality of leisure involvement have a significant impact on physical and mental health.

Keywords: walking dog, attractiveness, self-expression, multiple stepwise regression analysis

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Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

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The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: desert soil, climatic changes, bacteria, vegetation, artificial neural networks

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Authors: Sanele E. Nene L., Lia M. Hewitt

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Background: Artificial intelligence (AI) has a high value in healthcare, various applications have been developed for the efficiency of clinical operations, such as appointment/surgery scheduling, diagnostic image analysis, prognosis, prediction and management of specific ailments. Purpose: The purpose of this study was to explore, describe, contrast, evaluate, and develop the various leadership strategies as a conceptual framework, applied by public health Operational Managers (OMs) to embrace AI benefits, with the aim to improve the healthcare system in a public hospital. Design and Method: A qualitative, exploratory, descriptive and contextual research design was followed and a descriptive phenomenological approach. Five phases were followed to conduct this study. Phenomenological individual interviews and focus groups were used to collect data and a phenomenological thematic data analysis method was used. Findings and conclusion: Three themes surfaced as the experiences of AI by the OMs; Positive experiences related to AI, Management and leadership processes in AI facilitation, and Challenges related to AI.

Keywords: ambivalence, embracing, Artificial intelligence, public hospital

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Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

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Authors: Bahatti̇n Ki̇mençe, Uğur Ki̇mençe

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In this study, the purpose of obtaining the influence functions of the displacement discontinuity in an anisotropic elastic medium is to produce the boundary element equations. A Displacement Discontinuous Method formulation (DDM) is presented with the aim of modeling two-dimensional elastic fracture problems. This formulation is found by analytical integration of the fundamental solution along a straight-line crack. With this purpose, Kelvin's fundamental solutions for anisotropic media on an infinite plane are used to form dipoles from singular loads, and the various combinations of the said dipoles are used to obtain the influence functions of displacement discontinuity. This study introduces a technique for coupling Fictitious Stress Method (FSM) and DDM; the reason for applying this technique to some examples is to demonstrate the effectiveness of the proposed coupling method. In this study, displacement discontinuity equations are obtained by using dipole solutions calculated with known singular force solutions in an anisotropic medium. The displacement discontinuities method obtained from the solutions of these equations and the fictitious stress methods is combined and compared with various examples. In this study, one or more crack problems with various geometries in rectangular plates in finite and infinite regions, under the effect of tensile stress with coupled FSM and DDM in the anisotropic environment, were examined, and the effectiveness of the coupled method was demonstrated. Since crack problems can be modeled more easily with DDM, it has been observed that the use of DDM has increased recently. In obtaining the displacement discontinuity equations, Papkovitch functions were used in Crouch, and harmonic functions were chosen to satisfy various boundary conditions. A comparison is made between two indirect boundary element formulations, DDM, and an extension of FSM, for solving problems involving cracks. Several numerical examples are presented, and the outcomes are contrasted to existing analytical or reference outs.

Keywords: displacement discontinuity method, fictitious stress method, crack problems, anisotropic material

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Authors: Saud Hassan

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This paper shows simulation for the prediction of the flow around the backlight angle of the passenger vehicle. The CFD simulations are carried out on different car models. The Ahmed model “bluff body” used as the stander model to study aerodynamics of the backlight angle. This paper described the airflow over the different car models with different backlight angles and also on the Ahmed model to determine the trailing vortices with the varying backlight angle of a passenger vehicle body. The CFD simulation is carried out with the Ahmed body which has simplified car model mainly used in automotive industry to investigate the flow over the car body surface. The main goal of the simulation is to study the behavior of trailing vortices of these models. In this paper the air flow over the slant angle of 0,5o, 12.5o, 20o, 30o, 40o are considered. As investigating on the rear backlight angle two dimensional flows occurred at the rear slant, on the other hand when the slant angle is 30o the flow become three dimensional. Above this angle sudden drop occurred in drag.

Keywords: aerodynamics, Ahemd vehicle , backlight angle, finite element method

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Authors: Buddhi Arachchige, Hessam Ghasemnejad

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In this study, the post impact behavior of curved composite plates subjected to low velocity impact was studied analytically and numerically. Approaches to damage modelling are proposed through the degradation of stiffness in the damaged region by reduction of thickness in the damage region. Spring-mass models were used to model the impact response of the plate and impactor. The study involved designing two damage models to compare and contrast the model best fitted with the numerical results. The theoretical force-time responses were compared with the numerical results obtained through a detailed study carried out in LS-DYNA. The modified damage model established a good prediction with the analytical force-time response for different layups and geometry. This study provides a gateway in selecting the most effective layups for variable stiffness curved composite panels able to withstand a higher impact damage.

Keywords: analytical modelling, composite damage, impact, variable stiffness

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Authors: El Korchi Ayoub, Cherif Raef

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Interior noise in vehicles is an essential factor affecting occupant comfort. Over recent decades, much work has been done to develop simulation tools for vehicle NVH. At the medium high-frequency range, the statistical energy analysis method (SEA) shows significant effectiveness in predicting noise and vibration responses of mechanical systems. In this paper, the evaluation of the sound pressure level (SPL) inside an automobile cabin has been performed numerically using the statistical energy analysis (SEA) method. A test car cabin was performed using a monopole source as a sound source. The decay rate method was employed to obtain the damping loss factor (DLF) of each subsystem of the developed SEA model. These parameters were then used to predict the sound pressure level in the interior cabin. The results show satisfactory agreement with the directly measured SPL. The developed SEA vehicle model can be used in early design phases and allows the engineer to identify sources contributing to the total noise and transmission paths.

Keywords: SEA, SPL, DLF, NVH

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Authors: Hakan Akgul

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Purpose: The use of firecrackers (i.e., Ramadan Cannon) during the month of Ramadan is a traditional way of indicating that the fasting period is over in Muslim countries. Here, we report the rehabilitation of a case of hand injury with pluridigital fractures due to premature explosion of a Ramadan cannon. Materials and Methods: A 48-year old man admitted to the Emergency Department due to left hand injury as a result of a premature explosion of a Ramadan cannon. The patient was immediately taken to operation room because of the multiple fractures, tendon loss, and soft tissue loss in the left hand. Range of motion (ROM) of joints was measured with goniometer, pain and oedema were measured and splinting was performed. Results: Rehabilitation team took over the patient at postoperative 9th week. During the 3 month rehabilitation, range of motion increased, oedema was taken under control, pain was reduced, the colour of the skin turned to the normal tone. According to the visual analog scale (VAS), pain decreased from 9 to 4. Oedema, around the metacarpofalangeal (MCP) joints, decreased from 27,5 cm to 23,5 cm. Total active range of motion of the wrist increased from 5 degrees to 50 degrees.Total active range of motion of supination and pronation increased from 55 degrees to 70 degrees. Discussion: The rehabilitation of multiple hand injury is quite difficult. Different aspects of trauma should be taken into consideration when rehabilitation is planned. Factors such as waiting for the bone union, wound healing, and use of external fixators may delay rehabilitation process. Joint mobilization, massage for reducing oedema and preventing scar tissue, exercise within the range of motion are efficient measures. Poor patient compliance to treatment may lead to poor outcome. First of all, oedema and scar formation must be taken under control. Removing fixators should not be delayed depending on the bone union, and exercise within the range of motion should be started.

Keywords: explosion, fracture, hand, injury

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Authors: Raja Kannusamy

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The research focuses on reducing food waste in the restaurant industry. A study has been conducted on the chain of retail restaurant outlets. It has been observed that the food wastages are due to the inefficient inventory management systems practiced in the restaurant outlets. The major food items which are wasted more in quantity are being selected across the retail chain outlets. A moving average forecasting method has been applied for the selected food items so that their future demand could be predicted accurately and food wastage could be avoided. It has been found that the moving average prediction method helps in predicting forecasts accurately. The demand values obtained from the moving average method have been compared to the actual demand values and are found to be similar with minimum variations. The inventory optimization technique helps in reducing food wastage in restaurant supply chain outlets.

Keywords: food wastage, restaurant supply chain, inventory optimisation, demand forecasting

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Authors: Jane E. Mullen, Kevin Kelloway, Ann Rhéaume-Brüning

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The purpose of this study is to examine the effects of perceived leader word-action alignment on subordinate extra-role safety behavior. Using survey data gathered from a sample of nurses employed in health care facilities located in Eastern Canada (n = 192), the effects of perceived word-action alignment (measured as the cross product of leaders speaking positively about safety and acting safely) on nurse safety participation was examined. Moderated regression analysis resulted in the significant (p < .01) prediction of nurse safety participation by the interaction term. Analysis of the simple slopes comprising the interaction term suggests that positively speaking about safety only predicted safety participation when leaders were also perceived by subordinates as acting safely. The results provide empirical support for the importance of the perceived alignment between leaders’ words, or espoused safety values and priorities, and their actions. Practical implications for safety leadership training are discussed.

Keywords: leadership, safety participation, safety performance, safety training

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Authors: Roopchand Tandon, Zaheer Khan Yusufzai, R. Manna, R. K. Mandal

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Present work describes microstructures, mechanical properties, and texture characteristics of the friction stir processed AA7075T7352 aluminum alloy. Phases were analyzed with the help of x-ray diffractometre (XRD), transmission electron microscope (TEM) along with the differential scanning calorimeter (DSC). Depth-wise microstructures and dislocation characteristics from the nugget-zone of the friction stir processed specimens were studied using the bright field (BF) and weak beam dark-field (WBDF) TEM micrographs, and variation in the microstructures as well as dislocation characteristics were the noteworthy features found. XRD analysis display changes in the chemistry as well as size of the phases in the nugget and heat affected zones (Nugget and HAZ). Whereas the base metal (BM) microstructures remain un-affected. High density dislocations were noticed in the nugget regions of the processed specimen, along with the formation of dislocation contours and tangles. .The ɳ’ and ɳ phases, along with the GP-Zones were completely dissolved and trapped by the dislocations. Such an observations got corroborated to the improved mechanical as well as stress corrosion cracking (SCC) performances. Bulk texture and residual stress measurements were done by the Panalytical Empyrean MRD system with Co- kα radiation. Nugget zone (NZ) display compressive residual stress as compared to thermo-mechanically(TM) and heat affected zones (HAZ). Typical f.c.c. deformation texture components (e.g. Copper, Brass, and Goss) were seen. Such a phenomenon is attributed to the enhanced hardening as well as other mechanical performance of the alloy. Mechanical characterizations were done using the tensile test and Anton Paar Instrumented Micro Hardness tester. Enhancement in the yield strength value is reported from the 89MPa to the 170MPa; on the other hand, highest hardness value was reported in the nugget-zone of the processed specimens.

Keywords: aluminum alloy, mechanical characterization, texture characterstics, friction stir processing

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Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

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Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: artificial neural network, bending angle, fuzzy logic, laser forming

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Authors: Jarek Krajewski, David Daxberger

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We propose a stress detection method based on an RGB camera using heart rate detection, also known as Photoplethysmography Imaging (PPGI). This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. A stationary lab setting with simulated video conferences is chosen using constant light conditions and a sampling rate of 30 fps. The ground truth measurement of heart rate is conducted with a common PPG system. The proposed approach for pulse peak detection is based on a machine learning-based approach, applying brute force feature extraction for the prediction of heart rate pulses. The statistical analysis showed good agreement (correlation r = .79, p<0.05) between the reference heart rate system and the proposed method. Based on these findings, the proposed method could provide a reliable, low-cost, and contactless way of measuring HR parameters in daily-life environments.

Keywords: heart rate, PPGI, machine learning, brute force feature extraction

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Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

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Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

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Authors: Hadi Farhadian, Homayoon Katibeh

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Groundwater inflow to the tunnels is one of the most important problems in tunneling operation. The objective of this study is the investigation of model dimension effects on tunnel inflow assessment in discontinuous rock masses using numerical modeling. In the numerical simulation, the model dimension has an important role in prediction of water inflow rate. When the model dimension is very small, due to low distance to the tunnel border, the model boundary conditions affect the estimated amount of groundwater flow into the tunnel and results show a very high inflow to tunnel. Hence, in this study, the two-dimensional universal distinct element code (UDEC) used and the impact of different model parameters, such as tunnel radius, joint spacing, horizontal and vertical model domain extent has been evaluated. Results show that the model domain extent is a function of the most significant parameters, which are tunnel radius and joint spacing.

Keywords: water inflow, tunnel, discontinues rock, numerical simulation

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Duncan Oteki, Andebut Yeneneh, Daba Gedafa, Nabil Suleiman

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Most agencies lack the equipment required to measure the dynamic modulus (|E*|) of asphalt mixtures, necessitating the need to use predictive models. This study compared measured |E*| values for nine North Dakota asphalt mixes using the original Witczak, modified Witczak, and Hirsch models. The influence of temperature on the |E*| models was investigated, and Pavement ME simulations were conducted using measured |E*| and predictions from the most accurate |E*| model. The results revealed that the original Witczak model yielded the lowest Se/Sy and highest R² values, indicating the lowest bias and highest accuracy, while the poorest overall performance was exhibited by the Hirsch model. Using predicted |E*| as inputs in the Pavement ME generated conservative distress predictions compared to using measured |E*|. The original Witczak model was recommended for predicting |E*| for low-reliability pavements in North Dakota.

Keywords: asphalt mixture, binder, dynamic modulus, MEPDG, pavement ME, performance, prediction

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Authors: Sudhir Kumar Tiwari

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The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

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Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

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Authors: Xiaocong He

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Self-pierce riveting (SPR) is a new high-speed mechanical fastening technique which is suitable for point joining dissimilar sheet materials, as well as coated and pre-painted sheet materials. Mechanical structures assembled by SPR are expected to possess a high damping capacity. In this study, experimental measurement techniques were proposed for the prediction of vibration behavior of single-lap cantilevered SPR beams. The dynamic test software and the data acquisition hardware were used in the experimental measurement of the dynamic response of the single-lap cantilevered SPR beams. Free and forced vibration behavior of the single-lap cantilevered SPR beams was measured using the LMS CADA-X experimental modal analysis software and the LMS-DIFA Scadas II data acquisition hardware. The frequency response functions of the SPR beams of different rivet number were compared. The main goal of the paper is to provide a basic measuring method for further research on vibration based non-destructive damage detection in single-lap cantilevered SPR beams.

Keywords: self-piercing riveting, dynamic response, experimental measurement, frequency response functions

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Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

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Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

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Authors: Magdi M. E. Zumrawi, Mohamed Awad

Abstract:

Determination of Resilient Modulus (M_R) is quite important for characterizing materials in pavement design and evaluation. The main focus of this study is to develop a correlation that predict the resilient modulus of subgrade soils from simple and easy measured soil index properties. To achieve this objective, three subgrade soils representing typical Khartoum soils were selected and tested in the laboratory for measuring resilient modulus. Other basic laboratory tests were conducted on the soils to determine their physical properties. Several soil samples were prepared and compacted at different moisture contents and dry densities and then tested using resilient modulus testing machine. Based on experimental results, linear relationship of M_R with the consistency factor ‘F_c’ which is a combination of dry density, void ratio and consistency index had been developed. The results revealed that very good linear relationship found between the M_R and the consistency factor with a coefficient of linearity (R²) more than 0.9. The consistency factor could be used for the prediction of the M_R of compacted subgrade soils with precise and reliable results.

Keywords: Consistency factor, resilient modulus, subgrade soil, properties

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