Search results for: Deep mixed column

Authors: R. Ziaie Moayed, A. Mahigir

Abstract:

Stone column technique has been successfully employed to improve the load-settlement characteristics of foundations. A series of finite element numerical analyses of harmonic dynamic loading have been conducted on strengthened raft footing to study the effects of single and group stone columns on settlement of circular footings. The settlement of circular raft footing that improved by single and group of stone columns are studied under harmonic dynamic loading. This loading is caused by heavy machinery foundations. A detailed numerical investigation on behavior of single column and group of stone columns is carried out by varying parameters like weight of machinery, loading frequency and period. The result implies that presence of single and group of stone columns enhanced dynamic behavior of the footing so that the maximum and residual settlement of footing significantly decreased. 

Keywords: finite element analysis, harmonic loading, settlement, stone column

Procedia PDF Downloads 371

Authors: Azeddine El-Hassouny, Chandrashekhar Meshram, Geraldin Nanfack

Abstract:

In recent years, learning from data with noisy labels (Label Noise) has been a major concern in supervised learning. This problem has become even more worrying in Deep Learning, where the generalization capabilities have been questioned lately. Indeed, deep learning requires a large amount of data that is generally collected by search engines, which frequently return data with unreliable labels. In this paper, we investigate the Label Noise in Deep Learning using variational inference. Our contributions are : (1) exploiting Label Noise concept where the true labels are learnt using reparameterization variational inference, while observed labels are learnt discriminatively. (2) the noise transition matrix is learnt during the training without any particular process, neither heuristic nor preliminary phases. The theoretical results shows how true label distribution can be learned by variational inference in any discriminate neural network, and the effectiveness of our approach is proved in several target datasets, such as MNIST and CIFAR32.

Keywords: label noise, deep learning, discrete latent variable, variational inference, MNIST, CIFAR32

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

Abstract:

The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: A. M. Halahla, M. H. Baluch, M. K. Rahman, A. H. Al-Gadhib, M. N. Akhtar

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In the present study, 3D simulation of a typical exterior (RC) beam–column joint (BCJ) strengthened with carbon fiber-reinforced plastic (CFRP) sheet are carried out. Numerical investigations are performed using a nonlinear finite element ( FE) analysis by incorporating damage plasticity model (CDP), for material behaviour the concrete response in compression, tension softening were used, linear plastic with isotropic hardening for reinforcing steel, and linear elastic lamina material model for CFRP sheets using the commercial FE software ABAQUS. The numerical models developed in the present study are validated with the results obtained from the experiment under monotonic loading using the hydraulic Jack in displacement control mode. The experimental program includes casting of deficient BCJ loaded to failure load for both un-strengthened and strengthened BCJ. The failure mode, and deformation response of CFRP strengthened and un-strengthened joints and propagation of damage in the components of BCJ are discussed. Finite element simulations are compared with the experimental result and are noted to yield reasonable comparisons. The damage plasticity model was able to capture with good accuracy of the ultimate load and the mode of failure in the beam column joint.

Keywords: reinforced concrete, exterior beam-column joints, concrete damage plasticity model, computational simulation, 3-D finite element model

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Authors: Eleni Tsalaporta, Sebastien Vaesen, James M. D. MacElroy, Wolfgang Schmitt

Abstract:

Carbon dioxide capture has attracted the attention of many governments, industries and scientists over the last few decades, due to the rapid increase in atmospheric CO2 composition, with several studies being conducted in this area over the last few years. In many of these studies, CO2 capture in complex Pressure Swing Adsorption (PSA) cycles has been associated with high energy consumption despite the promising capture performance of such processes. The purpose of this study is the economic capture of atmospheric carbon dioxide for its transformation into a clean type of energy. A single column Temperature /Vacuum Swing Adsorption (TSA/VSA) process is proposed as an alternative option to multi column Pressure Swing Adsorption (PSA) processes. The proposed adsorbent is SIFSIX-3-Ni, a newly developed MOF (Metal Organic Framework), with extended CO2 selectivity and capacity. There are three stages involved in this paper: (i) SIFSIX-3-Ni is synthesized and pelletized and its physical and chemical properties are examined before and after the pelletization process, (ii) experiments are designed and undertaken for the estimation of the diffusion and adsorption parameters and limitations for CO2 undergoing capture from the air; and (iii) the CO2 adsorption capacity and dynamical characteristics of SIFSIX-3-Ni are investigated both experimentally and mathematically by employing a single column TSA/VSA, for the capture of atmospheric CO2. This work is further supported by a technical-economical study for the estimation of the investment cost and the energy consumption of the single column TSA/VSA process. The simulations are performed using gProms.

Keywords: carbon dioxide capture, temperature/vacuum swing adsorption, metal organic frameworks, SIFSIX-3-Ni

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Authors: Mustafa Kaya

Abstract:

In this study, the effect of pre-stressed strand diameters, providing the beam-to-column connections, was investigated from both experimental, and analytical aspects. In the experimental studies, the strength, stiffness, and energy dissipation capacities of the precast specimens comprising two pre-stressed strand samples of 12.70 mm, and 15.24 mm diameters, were compared with the reference specimen. The precast specimen with strands of 15.24 mm reached 96% of the maximum strength of the reference specimen; the amount of energy dissipated by this specimen until end of the test reached 48% of the amount of energy dissipated by the reference sample, and the stiffness of the same specimen at a 1.5% drift of reached 77% of the stiffness of the reference specimen at this drift. Parallel results were obtained during the analytical studies from the aspects of strength, and behavior, but the initial stiffness of the analytical models was lower than that of the test specimen.

Keywords: precast beam to column connection, moment resisting connection, post tensioned connections, finite element method

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Authors: Narava Manose

Abstract:

Distillation is a very old separation technology for separating liquid mixtures that can be traced back to the chemists in Alexandria in the first century A. D. Today distillation is the most important industrial separation technology. By the eleventh century, distillation was being used in Italy to produce alcoholic beverages. At that time, distillation was probably a batch process based on the use of just a single stage, the boiler. The word distillation is derived from the Latin word destillare, which means dripping or trickling down. By at least the sixteenth century, it was known that the extent of separation could be improved by providing multiple vapor-liquid contacts (stages) in a so called Rectifactorium. The term rectification is derived from the Latin words rectefacere, meaning to improve. Modern distillation derives its ability to produce almost pure products from the use of multi-stage contacting. Throughout the twentieth century, multistage distillation was by far the most widely used industrial method for separating liquid mixtures of chemical components.The basic principle behind this technique relies on the different boiling temperatures for the various components of the mixture, allowing the separation between the vapor from the most volatile component and the liquid of other(s) component(s). •Developed a simple non-linear model of a binary distillation column using Skogestad equations in Simulink. •We have computed the steady-state operating point around which to base our analysis and controller design. However, the model contains two integrators because the condenser and reboiler levels are not controlled. One particular way of stabilizing the column is the LV-configuration where we use D to control M_D, and B to control M_B; such a model is given in cola_lv.m where we have used two P-controllers with gains equal to 10.

Keywords: modelling, distillation column, control, binary distillation

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Authors: C. C. Chen, C. W. Hun, C. J. Wang, C. Y. Chen, J. S. Lin, K. J. Huang

Abstract:

Cesium iodide (CsI) melt was injected into anodic aluminum oxide (AAO) template and was solidified to CsI column. The controllable AAO channel size (10~500 nm) can makes CsI column size from 10 to500 nm in diameter. In order to have a shorter light irradiate from each singe CsI column top to bottom the AAO template was coated a TiO2 nano-film. The TiO2 film acts a refraction film and makes X-ray has a shorter irradiation path in the CsI crystal making a stronger the photo-electron signal. When the incidence light irradiate from air (R=1.0) to CsI’s first surface (R=1.84) the first refraction happen, the first refraction continue into TiO2 film (R=2.88) and produces the low angle of the second refraction. Then the second refraction continue into AAO wall (R=1.78) and produces the third refraction after refractions between CsI and AAO wall (R=1.78) produce the fourth refraction. The incidence light after through CsI and TiO2 film refractions arrive to the CsI second surface. Therefore, the TiO2 film can has shorter refraction path of incidence light and increase the photo-electron conversion efficiency.

Keywords: cesium iodide, anodic aluminum oxide (AAO), TiO2, refraction, X-ray

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Authors: X. Han, S. Duan, C. Liu, C. Zhou, W. Zhu, L. Kong

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The ionic imprinting technique refers to the three-dimensional rigid structure with the fixed pore sizes, which was formed by the binding interactions of ions and functional monomers and used ions as the template, it has a high level of recognition to the ionic template. The preparation of monolithic column by the in-situ polymerization need to put the compound of template, functional monomers, cross-linking agent and initiating agent into the solution, dissolve it and inject to the column tube, and then the compound will have a polymerization reaction at a certain temperature, after the synthetic reaction, we washed out the unread template and solution. The monolithic columns are easy to prepare, low consumption and cost-effective with fast mass transfer, besides, they have many chemical functions. But the monolithic columns have some problems in the practical application, such as low-efficiency, quantitative analysis cannot be performed accurately because of the peak shape is wide and has tailing phenomena; the choice of polymerization systems is limited and the lack of theoretical foundations. Thus the optimization of components and preparation methods is an important research direction. During the preparation of ionic imprinted monolithic columns, pore-forming agent can make the polymer generate the porous structure, which can influence the physical properties of polymer, what’ s more, it can directly decide the stability and selectivity of polymerization reaction. The compounds generated in the pre-polymerization reaction could directly decide the identification and screening capabilities of imprinted polymer; thus the choice of pore-forming agent is quite critical in the preparation of imprinted monolithic columns. This article mainly focuses on the research that when using different pore-forming agents, the impact of zinc ion imprinted monolithic column on the enrichment performance of zinc ion.

Keywords: high performance liquid chromatography (HPLC), ionic imprinting, monolithic column, pore-forming agent

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Authors: Anuar Ishak

Abstract:

The mixed convection stagnation point flow toward a vertical plate is investigated. The external flow impinges normal to the heated plate and the surface temperature is assumed to vary linearly with the distance from the stagnation point. The governing partial differential equations are transformed into a set of ordinary differential equations, which are then solved numerically using MATLAB routine boundary value problem solver bvp4c. Numerical results show that dual solutions are possible for a certain range of the mixed convection parameter. A stability analysis is performed to determine which solution is linearly stable and physically realizable.

Keywords: dual solutions, heat transfer, mixed convection, stability analysis

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Authors: Raghabendra Yadav, Baochun Chen, Huihui Yuan, Zhibin Lian

Abstract:

Concrete Filled Steel Tube (CFST) columns are widely used in Civil Engineering Structures due to their abundant properties. CFST-RC column is a built up column in which CFST members are connected with RC web. The CFST-RC column has excellent static and earthquake resistant properties, such as high strength, high ductility and large energy absorption capacity. CFST-RC columns have been adopted as piers in Ganhaizi Bridge in high seismic risk zone with a highest pier of 107m. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. The experimental investigation on scaled models of similar type of the CFST-RC pier are carried out. Under cyclic loading, the hysteretic performance of CFST-RC columns, such as failure modes, ductility, load displacement hysteretic curves, energy absorption capacity, strength and stiffness degradation are studied in this paper.

Keywords: CFST, cyclic load, Ganhaizi bridge, seismic performance

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Authors: Jong Il Rhee

Abstract:

The polypeptide representing the mature part of human BMP-7 was cloned and efficiently expressed in Escherichia coli and Bacillus subtilis, which had a clear band for hBMP-7, a homodimeric protein with an apparent molecular weight of 15.4 kDa. Recombinant E.coli produced 111 pg hBMP-7/mg of protein hBMP-7 through IPTG induction. Recombinant B. subtilis also produced 350 pg hBMP-7/ml of culture medium. The hBMP-7 was purified in 2 steps using an FPLC system with an ion exchange column and a gel filtration column. The hBMP-7 produced in this work also stimulated the alkaline phosphatase (ALP) activity in a dose-dependent manner, i.e. 2.5- and 8.9-fold at 100 and 300 ng hBMP-7/ml, respectively, and showed intact biological activity.

Keywords: B. subtilis, E. coli, fermentation, hBMP-7

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Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

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Authors: Ashkan Shafee, Ahmad Fahimifar

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There is a growing demand for construction of high-rise buildings and infrastructures in large cities, which sometimes require deep excavations in the vicinity of pile foundations. In this study, a two-dimensional finite element analysis is used to gain insight into the response of pile groups adjacent to deep excavations in sand. The numerical code was verified by available experimental works, and a parametric study was performed on different working load combinations, excavation depth and supporting system. The results show that the simple two-dimensional plane strain model can accurately simulate the excavation induced changes on adjacent pile groups. It was found that further excavation than pile toe level and also inclined loading on adjacent pile group can severely affect the serviceability of the foundation.

Keywords: deep excavation, inclined loading, lateral deformation, pile group

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

Abstract:

Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. Accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER, benefiting from deep learning, especially CNN and VGG16. First, the data is pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning

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Authors: Elia Efraim, Boris Blostotsky

Abstract:

Testing of columns in sway mode is performed in order to determine the maximal allowable load limited by plastic deformations or their end connections and a critical load limited by columns stability. Motivation to determine accurate value of critical force is caused by its using as follow: - critical load is maximal allowable load for given column configuration and can be used as criterion of perfection; - it is used in calculation prescribed by standards for design of structural elements under combined action of compression and bending; - it is used for verification of theoretical analysis of stability at various end conditions of columns. In the present work a new non-destructive method for determination of columns critical buckling load in sway mode is proposed. The method allows performing measurements during the tests under loads that exceeds the columns critical load without losing its stability. The possibility of such loading is achieved by structure of the loading system. The system is performed as frame with rigid girder, one of the columns is the tested column and the other is additional two-hinged strut. Loading of the frame is carried out by the flexible traction element attached to the girder. The load applied on the tested column can achieve values that exceed the critical load by choice of parameters of the traction element and the additional strut. The system lateral stiffness and the column critical load are obtained by the dynamic method. The experiment planning and the comparison between the experimental and theoretical values were performed based on the developed dependency of lateral stiffness of the system on vertical load, taking into account semi-rigid connections of the column's ends. The agreement between the obtained results was established. The method can be used for testing of real full-size columns in industrial conditions.

Keywords: buckling, columns, dynamic method, end-fixity factor, sway mode

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Authors: Asmaa El Harat, Toumi Hicham, Youssef Baddi

Abstract:

This survey delves into the complex realm of Internet of Things (IoT) security, highlighting the urgent need for effective cybersecurity measures as IoT devices become increasingly common. It explores a wide array of cyber threats targeting IoT devices and focuses on mitigating these attacks through the combined use of deep learning and machine learning algorithms, as well as edge and cloud computing paradigms. The survey starts with an overview of the IoT landscape and the various types of attacks that IoT devices face. It then reviews key machine learning and deep learning algorithms employed in IoT cybersecurity, providing a detailed comparison to assist in selecting the most suitable algorithms. Finally, the survey provides valuable insights for cybersecurity professionals and researchers aiming to enhance security in the intricate world of IoT.

Keywords: internet of things (IoT), cybersecurity, machine learning, deep learning

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Authors: Harmonis Rante, Rudy Djamaluddin, Herman Parung, Victor Sampebulu

Abstract:

Many research of FRP strengthening on beam-column joint have been done. They used FRP as a strengthening material but not as a connection method. This paper presents a result of experimental-study on connection method of precast beam-column using CFRP sheet to investigate the possibility of CFRP sheet to be a connecting material. Six specimens were prepared and tested to investigate the behavior of CFRP-s connection capacity. The performance of two-connection method is presented in this paper. Three specimens have been tested so far, they were specimen without belt, specimen using one belt and monolith specimen as a control specimen. Result indicated that FRP joint system without belt reached higher capacity than joint system using one belt, but both are lower than monolith joint. Capacity of joint system without belt is 90.6% and 62.5% for the joint system using one belt, respectively compared to the control specimen.

Keywords: belt, CFRP-s, connection method, strengthening

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Authors: Shuko Takeshita

Abstract:

This study investigates the identity formation of mixed-race children in Japan. From the latter half of the 1980s to the mid-2000s, Japan experienced an 'intermarriage boom,' which was soon followed by a fairly significant number of children born to these unions. These children are now coming of age. Among mixed-race children, some embraced both cultural traditions, while others chose a monocultural path despite exposure to two cultural traditions as they grew up. What factors are involved in shaping the identity of mixed-race children? How does identity formation actually occur in these children? This study addresses these questions through an interview survey of 139 cross-cultural families since 1999, including 23 Pakistani-Japanese families, 20 Turkish-Japanese families, 26 families comprising other international Muslim husbands and Japanese wives, 33 Filipino-Japanese families, and 37 Brazilian-Japanese families. The results of this two-decade-long study reveal that in cases where one cannot tell at first glance that children are mixed race, there is a tendency for them to hide their mixed background due to fear of bullying at school, as well as for their parents to encourage them to do this. To pass as a Japanese is one strategy for avoiding discrimination and prejudice, and it can provide a measure of ethnic security or a way of coping with social intolerance. Certainly, among my informants, there are some children who were bullied or teased at school, and as a result, they stopped attending or transferred to other schools. But the mixed-race experience is not always a negative thing in Japan. There is clearly a double standard involved in that mixed-race children of a Caucasian parent are more readily accepted by society than those of a non-Caucasian parent. The perceived social status of mixed-race individuals is usually understood in relation to the hierarchical positionings of monoracial groups. Mixed-race children could be guaranteed the right to enjoy the benefit of maintaining and developing an identity as a Japanese, in addition to one more identity. We need to encourage a new awareness of the children as agents for a transition from a monocultural system to a multicultural system in Japanese society.

Keywords: identity formation, intermarriage, mixed race, multicultural children

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Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar, David Phipps, Ortoneda Pedrola

Abstract:

Temperature is an essential parameter in the electrocoagulation process (EC) as it governs the solubility of electrodes and the precipitates and the collision rate of particles in water being treated. Although it has been about 100 years since the EC technology was invented and applied in water and wastewater treatment, the effects of temperature on the its performance were insufficiently investigated. Thus, the present project aims to fill this gap by an innovative use of perforated flow columns in the designing of a new EC reactor (ECR1). The new reactor (ECR1) consisted of a Perspex made cylinder container supplied with a flow column consisted of perorated discoid electrodes that made from aluminium. The flow column has been installed vertically, half submerged in the water being treated, inside a plastic cylinder. The unsubmerged part of the flow column works as a radiator for the water being treated. In order to investigate the performance of ECR1; water samples with different initial temperatures (15, 20, 25, 30, and 35 °C) to the ECR1 for 20 min. Temperature of effluent water samples were measured using Hanna meter (Model: HI 98130). The obtained results demonstrated that the ECR1 reduced water temperature from 35, 30, and 25 °C to 24.6, 23.8, and 21.8 °C respectively. While low water temperature, 15 °C, increased slowly to reach 19.1 °C after 15 minutes and kept the same level till the end of the treatment period. At the same time, water sample with initial temperature of 20 °C showed almost a steady level of temperature along the treatment process, where the temperature increased negligibly from 20 to 20.1 °C after 20 minutes of treatment. In conclusion, ECR1 is able to control the temperature of water being treated around the room temperature even when the initial temperature was high (35 °C) or low (15 °C).

Keywords: electrocoagulation, flow column, treatment, water temperature

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Authors: Pawan S. Nagda, Purnank S. Bhatt, Mit K. Shah

Abstract:

Earing defect in drawing process is highly undesirable not only because it adds on an additional trimming operation but also because the uneven material flow demands extra care. The objective of this work is to study the earing problem in the Deep Drawing of circular cup and to optimize the blank shape to reduce the earing. A finite element model is developed for 3-D numerical simulation of cup forming process in ABAQUS. Extra-deep-drawing (EDD) steel sheet has been used for simulation. Properties and tool design parameters were used as input for simulation. Earing was observed in the simulated cup and it was measured at various angles with respect to rolling direction. To reduce the earing defect initial blank shape was modified with the help of anisotropy coefficient. Modified blanks showed notable reduction in earing.

Keywords: anisotropy, deep drawing, earing, finite element simulation

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Authors: Shiyin He, Zheng Huang

Abstract:

In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

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Authors: Farshid Hajati, Federico Girosi, Shima Ghassempour

Abstract:

We present a Deep Belief Network (DBN) method for clustering health trajectories. Deep Belief Network (DBN) is a deep architecture that consists of a stack of Restricted Boltzmann Machines (RBM). In a deep architecture, each layer learns more complex features than the past layers. The proposed method depends on DBN in clustering without using back propagation learning algorithm. The proposed DBN has a better a performance compared to the deep neural network due the initialization of the connecting weights. We use Contrastive Divergence (CD) method for training the RBMs which increases the performance of the network. The performance of the proposed method is evaluated extensively on the Health and Retirement Study (HRS) database. The University of Michigan Health and Retirement Study (HRS) is a nationally representative longitudinal study that has surveyed more than 27,000 elderly and near-elderly Americans since its inception in 1992. Participants are interviewed every two years and they collect data on physical and mental health, insurance coverage, financial status, family support systems, labor market status, and retirement planning. The dataset is publicly available and we use the RAND HRS version L, which is easy to use and cleaned up version of the data. The size of sample data set is 268 and the length of the trajectories is equal to 10. The trajectories do not stop when the patient dies and represent 10 different interviews of live patients. Compared to the state-of-the-art benchmarks, the experimental results show the effectiveness and superiority of the proposed method in clustering health trajectories.

Keywords: health trajectory, clustering, deep learning, DBN

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Authors: Okoro Ikechukwu Ralph, Fuat Kara

Abstract:

The discoveries of hydrocarbon reserves has clearly drifted offshore, and in deeper waters - areas where the industry still has limited knowledge; and that were hitherto, regarded as being out of reach. This shift presents significant and increased challenges in technology requirements needed to guarantee safety of personnel, environment and equipment; ensure high reliability of installed equipment; and provide high level of confidence in security of investment and company reputation. Nowhere are these challenges more apparent than on subsea well integrity and production performance. The past two decades has witnessed enormous rise in deep and ultra-deep water offshore field developments for the recovery of hydrocarbons. Subsea installed equipment at the seabed has been the technology of choice for these developments. This paper discusses the role of Subsea Control module (SCM) as a vital factor for deep-water well integrity and production performance. A case study for Deep-water well integrity and production performance is analysed.

Keywords: offshore reliability, production performance, subsea control module, well integrity

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Authors: Boris Blostotsky, Elia Efraim

Abstract:

Testing of columns in sway mode is performed in order to determine the maximal allowable load limited by plastic deformations or their end connections and a critical load limited by columns stability. Motivation to determine accurate value of critical force is caused by its using as follow: - critical load is maximal allowable load for given column configuration and can be used as criterion of perfection; - it is used in calculation prescribed by standards for design of structural elements under combined action of compression and bending; - it is used for verification of theoretical analysis of stability at various end conditions of columns. In the present work a new non-destructive method for determination of columns critical buckling load in sway mode is proposed. The method allows performing measurements during the tests under loads that exceeds the columns critical load without losing its stability. The possibility of such loading is achieved by structure of the loading system. The system is performed as frame with rigid girder, one of the columns is the tested column and the other is additional two-hinged strut. Loading of the frame is carried out by the flexible traction element attached to the girder. The load applied on the tested column can achieve a values that exceed the critical load by choice of parameters of the traction element and the additional strut. The system lateral stiffness and the column critical load are obtained by the dynamic method. The experiment planning and the comparison between the experimental and theoretical values were performed based on the developed dependency of lateral stiffness of the system on vertical load, taking into account a semi-rigid connections of the column's ends. The agreement between the obtained results was established. The method can be used for testing of real full-size columns in industrial conditions.

Keywords: buckling, columns, dynamic method, semi-rigid connections, sway mode

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Authors: Zhiming Ye, Dejiang Wang, Huiling Zhao

Abstract:

Development of the technology demands a higher-level research on the mechanical behavior of materials. Structural members made of bi-modulus materials have different elastic modulus when they are under tension and compression. The stress and strain states of the point effect on the elastic modulus and Poisson ratio of every point in the bi-modulus material body. Accompanied by the uncertainty and nonlinearity of the elastic constitutive relation is the complicated nonlinear problem of the bi-modulus members. In this paper, the small displacement and large displacement finite element method for the bi-modulus members have been proposed. Displacement nonlinearity is considered in the elastic constitutive equation. Mechanical behavior of slender bi-modulus beam-column under different boundary conditions and loading patterns has been simulated by the proposed method. The influence factors on the ultimate bearing capacity of slender beam and columns have been studied. The results show that as the ratio of tensile modulus to compressive modulus increases, the error of the simulation employing the same elastic modulus theory exceeds the engineering permissible error.

Keywords: bi-modulus, ultimate capacity, beam-column, nonlinearity

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Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

The increasing use of deep learning applications in production is becoming a competitive advantage. Predictive quality enables the assurance of product quality by using data-driven forecasts via machine learning models as a basis for decisions on test results. The use of real Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the leakage of directional valves.

Keywords: artificial neural networks, classification, hydraulics, predictive quality, deep learning

Procedia PDF Downloads 243

Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

Abstract:

The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: foot recognition, deep learning, knee rehabilitation, convolutional neural network

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Authors: Mohamed H. Sorour, Hayam F. Shaalan, Heba A. Hani, Eman S. Sayed

Abstract:

Ion exchange adsorption has a long standing history of success for seawater softening and selective ion removal from saline sources. Strong, weak and mixed types ion exchange systems could be designed and optimized for target separation. In this paper, different types of adsorbents comprising zeolite 13X and kaolin, in addition to, poly acrylate/zeolite (AZ), poly acrylate/kaolin (AK) and stand-alone poly acrylate (A) hydrogel types were prepared via microwave (M) and ultrasonic (U) irradiation techniques. They were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The developed adsorbents were evaluated on bench scale level and based on assessment results, a composite bed has been formulated for performance evaluation in pilot scale column investigations. Owing to the hydrogel nature of the partially crosslinked poly acrylate, the developed adsorbents manifested a swelling capacity of about 50 g/g. The pilot trials have been carried out using magnesium enriched Red Seawater to simulate Red Seawater desalination brine. Batch studies indicated varying uptake efficiencies, where Mg adsorption decreases according to the following prepared hydrogel types AU>AM>AKM>AKU>AZM>AZU, being 108, 107, 78, 69, 66 and 63 mg/g, respectively. Composite bed adsorbent tested in the up-flow mode column studies indicated good performance for Mg uptake. For an operating cycle of 12 h, the maximum uptake during the loading cycle approached 92.5-100 mg/g, which is comparable to the performance of some commercial resins. Different regenerants have been explored to maximize regeneration and minimize the quantity of regenerants including 15% NaCl, 0.1 M HCl and sodium carbonate. Best results were obtained by acidified sodium chloride solution. In conclusion, developed cation exchange adsorbents comprising clay or zeolite support indicated adequate performance for Mg recovery under saline environment. Column design operated at the up-flow mode (approaching expanded bed) is appropriate for such type of separation. Preliminary cost indicators for Mg recovery via ion exchange have been developed and analyzed.

Keywords: batch and dynamic magnesium separation, seawater, polyacrylate hydrogel, cost evaluation

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Authors: Sarthak Karki, Haribansha Timalsina

Abstract:

Kanchan Arsenic Filter is an economical low cost and termed the most efficient arsenic removal filter system in South Asian countries such as Nepal. But when the effluent quality was evaluated, it was seen to possess a lower removal rate of arsenite species. In addition to that, greater pathogenic growth and loss in overall efficacy with time due to precipitation of iron sulphates were the further complications. This brings the health issue on the front line as millions of people rely on groundwater sources for general water necessities. With this paper, we analyzed the mechanisms and changes in the efficiency of the extant filter system when integrated with activated laterite and hair column beds, plus an additional charcoal layer for inhibiting pathogen colonies. Hair column have rich keratin protein that binds with arsenic species, and similarly, raw laterite has huge deposits of iron and aluminum, all of these factors helping to remove heavy metal contaminants from water sources. Further study on the commercialized mass production of the new proposed filter and versatility analysis is required.

Keywords: laterite, charcoal, arsenic removal, hair column

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