Search results for: longitudinal reinforcement

Authors: P. Saleh, G. Challita, R. Hazimeh, K. Khalil

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In this paper 3D FEM analysis was carried out on double lap bonded joint with composite adherents subjected to dynamic shear. The adherents are made of Carbon/Epoxy while the adhesive is epoxy Araldite 2031. The maximum average shear stress and the stress homogeneity in the adhesive layer were examined. Three fibers textures were considered: UD; 2.5D and 3D with same volume fiber then a parametric study based on changing the thickness and the type of fibers texture in 2.5D was accomplished. Moreover, adherents’ dissimilarity was also investigated. It was found that the main parameter influencing the behavior is the longitudinal stiffness of the adherents. An increase in the adherents’ longitudinal stiffness induces an increase in the maximum average shear stress in the adhesive layer and an improvement in the shear stress homogeneity within the joint. No remarkable improvement was observed for dissimilar adherents.

Keywords: adhesive, composite adherents, impact shear, finite element

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Mai A. Aljaberi

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The anchorage of fibre-reinforced polymer (FRP) sheets is the most effective solution to prevent or delay debonding failure; this system has proven to get better levels of FRP utilization. Unfortunately, the related design information is still unclear. This shortcoming limits the widespread use of the anchorage system. In order to minimize the knowledge gap about the design of U-wrap anchors, this paper reports the results of tested beams which were strengthened with carbon fiber-reinforced polymer (CFRP) sheets at their tension sides and secured with U-wrap anchors at each end of the longitudinal CFRP. The beams were tested under four-point loading until failure. The parameters examined include the compressive strength of the concrete and the number of longitudinal CFRP. It is concluded that these parameters have a considerable effect on the debonding of the strain. The greatest improvement in the strain was 55.8% over the control beam.

Keywords: CFRP, concrete strengthening, debonding failure, debonding strain, U-wrap anchor

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Authors: Shengwei Zhu, Alireza Afshani, Hirokazu Akagi

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Ground surface settlement induced by shield tunneling is addressing increasing attention as shield tunneling becomes a popular construction technique for tunnels in urban areas. This paper discusses a 2D longitudinal FEM simulation of a tunneling case study in Japan (Tokyo Metro Yurakucho Line). Tunneling-induced field data was already collected and is used here for comparison and evaluating purposes. In this model, earth pressure, face pressure, backfilling grouting, elastic tunnel lining, and Mohr-Coulomb failure criterion for soil elements are considered. A method called ‘stress relaxation’ is also exploited to simulate the gradual tunneling excavation. Ground surface settlements obtained from numerical results using the introduced method are then compared with the measurement data.

Keywords: 2D longitudinal FEM model, tunneling case study, stress relaxation, shield tunneling excavation

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Authors: Thi Nguyet Hang Nguyen, Kang Hai Tan

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Precast/prestressed concrete hollow core (PCHC) slabs, especially ones with depth more than 300 mm, are susceptible to web-shear failure. The reasons lie on the fact that the production process of PCHC slabs, i.e., the extrusion method (the most common method to cast PCHC slabs nowadays), does not allow them to contain any shear reinforcement. Moreover, due to the presence of the longitudinal voids, cross sections of PCHC slabs are reduced. Therefore, the shear capacity of the slabs depends solely on the tensile strength of concrete which is relatively low. Given that shear is a major concern in using hollow-core slabs, this paper investigates the possibility of adopting steel fibers in PCHC slabs produced by the extrusion method to enhance the shear capacity of the slabs. Three full-scale PCHC slabs with and without hooked-steel fibers were cast and tested until failure. Three different volumetric fiber contents of 0, 0.51 and 0.89% were investigated. The test results showed that there were substantial increases in shear capacity and ductility with the use of hooked-steel fibers. Ultimate shear strength increased with fiber content. In addition, while the specimen without steel fibers and the one with the steel-fiber volume fraction of 0.51% failed in web-shear mode, the specimen with the higher fiber content (0.89%) collapsed in flexural-shear mode. However, as the hooked-steel fibers with the fiber content of 0.89% were used, difficulties in concrete consolidation were observed while concrete was being cast. This could lead to a lower ultimate shear capacity due to a poorer bond between the concrete and the steel fibers.

Keywords: hollow-core slabs, shear strength, steel fibers, web-shear failure

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Authors: Einav Srulovici, Michal Grinstein-Weiss, George Knafl, Linda Beeber, Shawn Kneipp, Barbara Mark

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Background: The asset-building theoretical framework (ABTF) is acknowledged as the most complete framework thus far for depicting the relationships between asset accumulation (the stock of a household’s saved resources available for future investment) and health outcomes. Although the ABTF takes into consideration the reciprocal relationship between asset accumulation and health, no ABTF based study has yet examined this relationship. Therefore, the purpose of this study was to test the ABTF and psychological distress, focusing on the reciprocal relationship between assets accumulation and psychological distress. Methods: The study employed longitudinal data from 6,295 families from the 2001 and 2007 Panel Study of Income Dynamics data sets. Structural equation modeling (SEM) was used to test the reciprocal relationship between asset accumulation and psychological distress. Results: In general, the data displayed a good fit to the model. The longitudinal SEM found that asset accumulation significantly increased with a decreased in psychological distress over time, while psychological distress significantly increased with an increase in asset accumulation over time, confirming the existence of the hypothesized reciprocal relationship. Conclusions: Individuals who are less psychological distressed might have more energy to engage in activities, such as furthering their education or obtaining better jobs that are in turn associated with greater asset accumulation, while those who have greater assets may invest those assets in riskier investments, resulting in increased psychological distress. The confirmation of this reciprocal relationship highlights the importance of conducting longitudinal studies and testing the reciprocal relationship between asset accumulation and other health outcomes.

Keywords: asset-building theoretical framework, psychological distress, structural equation modeling, reciprocal relationship

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Authors: A. Bouhaloufa, T. Kadri, S. Zouaoui, A. Belhacene

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To put more durable bridges, it is important to maintain existing structures, rather than investing in new structures. Instead of demolishing the old bridge and replace them with new, we must preserve and upgrade using better methods of diagnosis, auscultation and repair, the interest of this work is to increase the bearing capacity bridges damaged by additional prestressing, this type of reinforcement is growing continuously. In addition to excellent static strength, prestressing also has a very high resistance to fatigue, so it is suitable to solve the problem of failure of the bearing capacity of the bridges. This failure often comes to the development of overloads in quantity and quality, that is our daily traffic has increased and become very complicated, on the other hand its constituents are advanced in weight and speed and therefore almost all old bridges became unable to support the movement of the latter and remain disabled to all these problems. The main purpose of this work includes the following three aspects: - Determination of the main diseases and factors affecting the deterioration of bridges in Algeria, - Evaluation of the bearing capacity of bridges, - Proposal technical reinforcement to improve the bearing capacity of a degraded structure.

Keywords: bridges, repair, auscultation, diagnosis, pathology, additional prestressing

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Authors: Ki-Seok Kwon, Heung-Youl Kim

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This research evaluated fire resistances of high-strengthened reinforced concrete (RC) column, spiral wire rope which applied with 60, and 100MPa. The fire resistance test of RC column with loading condition was conducted following the ISO 834 (3 hours). This experiment set mixing of fiber (PP fiber, Steel fiber) and types of horizontal reinforcement as a variable of reinforcement method. The fire resistance test measured the main steel bar’s max and mean temperatures also the shrinkage and shrinking ratio of columns(500 X 500 X 3,000mm) with loadings. As a result, the specimen of 60MPa attained three hours fire resistance with only spiral wire rope. Also, the specimen of 100MPa must be reinforced with fibers and spiral wire rope to attain three hours fire resistance.

Keywords: reinforced concrete column, high strength concrete, wire rope, fire resistance test

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Authors: Metwally Abdel Aziz Ahmed, Ahmed Shaban Abdel Hay Gabr, Inas Mohamed Saleh

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The main objective of structural design is to ensure safety and functional performance requirements of a structural system for its target reliability levels. In this study, the reliability index for the reinforcement concrete slender columns with rectangular cross section is studied. The variable parameters studied include the loads, the concrete compressive strength, the steel yield strength, the dimensions of concrete cross-section, the reinforcement ratio, and the location of steel placement. Risk analysis program was used to perform the analytical study. The effect of load eccentricity on the reliability index of reinforced concrete slender column was studied and presented. The results of this study indicate that the good quality control improve the performance of slender reinforced columns through increasing the reliability index β.

Keywords: reliability, reinforced concrete, safety, slender column

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Authors: S. Subrmanian, A. Siva, R. Raghul

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In modern construction industry, usage of cold form composite slab has its scope widely due to its light weight, high structural properties and economic factor. To enhance the structural integrity, mechanical interlocking or frictional interlocking was introduced. The role of mechanical interlocking or frictional interlocking is to increase the longitudinal shear between the profiled sheet and concrete. This paper deals with the experimental evaluation of three types of mechanical interlocking devices namely normal stud shear connector, J-Type shear connector, U-Type shear connector. An attempt was made to evolve the shear connector which can be suitable for the composite slab as an interlocking device. Totally six number of composite slabs have been experimented with three types of shear connectors and comparison study is made. The outcome was compared with numerical model was created by ABAQUS software and analyzed for comparative purpose. The result was U-Type shear connector provided better performance and resistance.

Keywords: composite slabs, shear connector, end slip, longitudinal shear

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Authors: Li Xu, Yang Hong, T. Zhao Wen

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Experimental results of many RC beam-column subassemblage indicate that slippage of longitudinal beam rebar within the joint and the shear deformation of joint core have significant influence on seismic behavior of the subassemblage. However, rigid joint assumption has been generally used in the seismic response analysis of RC frames, in which two kinds of inelastic deformation of joint have been ignored. Based on OpenSees platform, ‘Super Joint Element Model’ with more detailed inelastic mechanism is used to simulate the inelastic response of joints. Two finite element models of typical RC plane frame, namely considering or ignoring the inelastic deformation of joint respectively, were established and analyzed under seven strong earthquake waves. The simulated global and local inelastic deformations of the RC plane frame is shown and discussed. The analyses also confirm the security of the earthquake-resistant frame designed according to Chinese codes.

Keywords: frame structure, beam-column joint, longitudinal bar slippage, shear deformation, nonlinear analysis

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Authors: Vivian A. Galindo, Maria C. Galvis, Jaime R. Obando, Alvaro Guarin

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In Colombia, most of the roads of the national tertiary road network are unpaved roads with granular rolling surface. These are very important ways of guaranteeing the mobility of people, products, and inputs from the agricultural sector from the most remote areas to urban centers; however, it has not paid much attention to the search for alternatives to avoid the occurrence of deteriorations that occur shortly after its commissioning. In recent years, geosynthetics have been used satisfactorily to reinforce unpaved roads on soft soils, with geotextiles and geogrids being the most widely used. The interaction of the geogrid and the aggregate minimizes the lateral movement of the aggregate particles and increases the load capacity of the material, which leads to a better distribution of the vertical stresses, consequently reducing the vertical deformations in the subgrade. Taking into account the above, the research aimed at the mechanical behavior of the granular material, used in unpaved roads with and without the presence of geogrids, from the development of laboratory tests through the loaded wheel tester (LWT). For comparison purposes, the reinforced conditions and traffic conditions to which this type of material can be accessed in practice were simulated. In total four types of geogrids, were tested with granular material; this means that five test sets, the reinforced material and the non-reinforced control sample were evaluated. The results of the numbers of load cycles and depth rutting supported by each test body showed the influence of the properties of the reinforcement on the mechanical behavior of the assembly and the significant increases in the number of load cycles of the reinforced specimens in relation to those without reinforcement.

Keywords: geosynthetics, load wheel tester LWT, tertiary roads, unpaved road, vertical deformation

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Authors: Masato Nishi, Tetsushi Kaburagi, Masashi Kurose, Tei Hirashima, Tetsusei Kurasiki

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The process of thermoforming a carbon fiber reinforced thermoplastic (CFRTP) has increased its presence in the automotive industry for its wide applicability to the mass production car. A non-isothermal forming for CFRTP can shorten its cycle time to less than 1 minute. In this paper, the textile reinforcement FE model which the authors proposed in a previous work is extended to the CFRTP model for non-isothermal forming simulation. The effect of thermoplastic is given by adding shell elements which consider thermal effect to the textile reinforcement model. By applying Reuss model to the stress calculation of thermoplastic, the proposed model can accurately predict in-plane shear behavior, which is the key deformation mode during forming, in the range of the process temperature. Using the proposed model, thermoforming simulation was conducted and the results are in good agreement with the experimental results.

Keywords: carbon fiber reinforced thermoplastic, finite element analysis, pre-impregnated textile composite, non-isothermal forming

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Authors: Nirmal Kant Singh, Anshuman Pratap Singh

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In this study the augmentation of heat transfer in a channel with delta winglet type vortex generators is evaluated. Three-dimensional numerical simulations are performed in a rectangular channel with longitudinal triangular vortex generators (LVGs). The span wise averaged Nusselt number and mean temperature are compared with and without vortex generators in the channel. The effect of variation of blade angle (15°, 30°, 45°, and 60°) is studied at a Reynolds number of 10000. The numerical results indicate that the application of LVGs effectively enhances heat transfer in the channel. The Nusselt number and mean outlet temperature were found to be greater using LVGs than in the channel without LVGs. It is observed that heat transfer increases with increase in blade angle at the same Reynolds number.

Keywords: heat transfer, rectangular channel, longitudinal vortex generators, effect of blade angle

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Keerti Kembhavi, M. R. Archana, V. Anjaneyappa

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Most asphalt pavement condition evaluation use rating frameworks in which asphalt pavement distress is estimated by type, extent, and severity. Rating is carried out by the pavement condition rating (PCR), which is tedious and expensive. This paper presents the development of a low-cost technique for image pavement distress analysis that permits the identification of pothole and cracks. The paper explores the application of image processing tools for the detection of potholes and cracks. Longitudinal cracking and pothole are detected using Fuzzy-C- Means (FCM) and proceeded with the Spectral Theory algorithm. The framework comprises three phases, including image acquisition, processing, and extraction of features. A digital camera (Gopro) with the holder is used to capture pavement distress images on a moving vehicle. FCM classifier and Spectral Theory algorithms are used to compute features and classify the longitudinal cracking and pothole. The Matlab2016Ra Image preparing tool kit utilizes performance analysis to identify the viability of pavement distress on selected urban stretches of Bengaluru city, India. The outcomes of image evaluation with the utilization semi-computerized image handling framework represented the features of longitudinal crack and pothole with an accuracy of about 80%. Further, the detected images are validated with the actual dimensions, and it is seen that dimension variability is about 0.46. The linear regression model y=1.171x-0.155 is obtained using the existing and experimental / image processing area. The R2 correlation square obtained from the best fit line is 0.807, which is considered in the linear regression model to be ‘large positive linear association’.

Keywords: crack detection, pothole detection, spectral clustering, fuzzy-c-means

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Mohammad Reza Koushki Ardestani, Saeed Daneshmand, Mohammad Heydari Vini

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In the present study, AA7075/SiO2 composites have been fabricated via liquid metallurgy process. Using the degassing process, the wet ability of the molten aluminum alloys increased which improved the bonding between aluminum matrix and reinforcement (SiO2) particles. AA7075 alloy and SiO2 particles were taken as the base matrix and reinforcements, respectively. Then, contents of 2.5 and 5 wt. % of SiO2 subdivisions were added into the AA7075 matrix. To improve wettability and distribution, reinforcement particles were pre-heated to a temperature of 550°C for each composite sample. A uniform distribution of SiO2 particles was observed through the matrix alloy in the microstructural study. A hardened EN32 steel disc as the counter face was used to evaluate the wear rate pin-on-disc, a wear testing machine containing. The results showed that the wear rate of the AA/SiO2 composites was lesser than that of the monolithic AA7075 samples. Finally, The SEM worn surfaces of samples were investigated.

Keywords: Al7075, SiO₂, wear, composites, stir casting

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Authors: Parisa Ahmadi Oliaei, Seyed Abolhassan Naeini

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The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the Pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the Pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of Pull- out a test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Keywords: plaxis, pull-out test, sand, soil- geogrid interaction

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Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

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Authors: Stephan Schiffer, Andreas Kain, Philipp Wilde, Maximilian Helbing, Bernard Bäker

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Automobile manufacturers progressively focus on a downsizing strategy to meet the EU's CO2 requirements concerning type-approval consumption cycles. The reduction in naturally aspirated engine power is compensated by increased levels of turbocharging. By downsizing conventional engines, CO2 emissions are reduced. However, it also implicates major challenges regarding longitudinal dynamic characteristics. An example of this circumstance is the delayed turbocharger-induced torque reaction which leads to a partially poor response behavior of the vehicle during acceleration operations. That is why it is important to focus conventional drive train design on real customer driving again. The currently considered dynamic maneuvers like the acceleration time 0-100 km/h discussed by journals and car manufacturers describe longitudinal dynamics experienced by a driver inadequately. For that reason we present the realization and evaluation of a comprehensive proband study. Subjects are provided with different vehicle concepts (electrified vehicles, vehicles with naturally aspired engines and vehicles with different concepts of turbochargers etc.) in order to find out which dynamic criteria are decisive for a subjectively strong acceleration and response behavior of a vehicle. Subsequently, realistic acceleration criteria are derived. By weighing the criteria an evaluation metric is developed to objectify customer-oriented transient dynamics. Fully-electrified vehicles are the benchmark in terms of customer-oriented longitudinal dynamics. The electric machine provides the desired torque almost without delay. This advantage compared to combustion engines is especially noticeable at low engine speeds. In conclusion, we will show the degree to which extent customer-relevant longitudinal dynamics of conventional vehicles can be approximated to electrified vehicle concepts. Therefore, various technical measures (turbocharger concepts, 48V electrical chargers etc.) and drive train designs (e.g. varying the final drive) are presented and evaluated in order to strengthen the vehicle’s customer-relevant transient dynamics. As a rating size the newly developed evaluation metric will be used.

Keywords: 48V, customer-oriented driving dynamics, electric charger, electrified vehicles, vehicle concepts

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Authors: P. Leo, E. Cerri, L. Fratini, G. Buffa

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The Friction Stir Welding process uses an inert rotating mandrel and a force on the mandrel normal to the plane of the sheets to generate the frictional heat. The heat and the stirring action of the mandrel create a bond between the two sheets without melting the base metal. As matter of fact, the use of a solid state welding process limits the insurgence of defects, due to the presence of gas in melting bath, and avoids the negative effects of materials metallurgical transformation strictly connected with the change of phase. The industrial importance of Ti-6Al-4V alloy is well known. It provides an exceptional good balance of strength, ductility, fatigue and fracture properties together with good corrosion resistance and good metallurgical stability. In this paper, the authors analyze the microstructure of friction stir welded joints of Ti-6Al-4V processed at the same travel speed (35 mm/min) but at different rotation speeds (300-500 rpm). The microstructure of base material (BM), as result from both optical microscope and scanning electron microscope analysis is not homogenous. It is characterized by distorted α/β lamellar microstructure together with smashed zone of fragmented β layer and β retained grain boundary phase. The BM has been welded in the-as received state, without any previous heat treatment. Even the microstructure of the transverse and longitudinal sections of joints is not homogeneous. Close to the top of weld cross sections a much finer microstructure than the initial condition has been observed, while in the center of the joints the microstructure is less refined. Along longitudinal sections, the microstructure is characterized by equiaxed grains and lamellae. Both the length and area fraction of lamellas increases with distance from longitudinal axis. The hardness of joints is higher than that of BM. As the process temperature increases the average microhardness slightly decreases.

Keywords: friction stir welding, microhardness, microstructure, Ti-6Al-4V

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Authors: Jinghua Zhang

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Shaft-tunnel junction is a typical case of the structural nonuniformity in underground structures. The shaft and the tunnel possess greatly different structural features. Even under uniform excitations, they tend to behave discrepantly. Studies on shaft-tunnel junctions are mainly performed numerically. Shaking table tests are also conducted. Although many numerical and experimental data are obtained, an analytical solution still has great merits of gaining more insights into the shaft-tunnel problem. This paper will try to remedy the situation. Since the seismic responses of shaft-tunnel junctions are very related to directions of the excitations, they are studied in two scenarios: the longitudinal-excitation scenario and the transverse-excitation scenario. The former scenario will be addressed in this paper. Given that responses of the tunnel are highly dependent on the shaft, the analytical solutions would be developed firstly for the vertical shaft. Then, the seismic responses of the tunnel would be discussed. Since vertical shafts bear a resemblance to rigid caissons, the solution proposed in this paper is derived by introducing terms of shaft-tunnel and soil-tunnel interactions into equations originally developed for rigid caissons. The validity of the solution is examined by a validation model computed by finite element method. The mutual influence between the shaft and the tunnel is introduced. The soil-structure interactions are discussed parametrically based on the proposed equations. The shaft-tunnel relative displacement and the soil-tunnel relative stiffness are found to be the most important parameters affecting the magnitudes and distributions of the internal forces of the tunnel. A hinge-joint at the shaft-tunnel junction could significantly reduce the degree of stress concentration compared with a rigid joint.

Keywords: analytical solution, longitudinal excitation, numerical validation , shaft-tunnel junction

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Vara Prasad Vemu

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The aim of the present work is to investigate the mechanical properties and water absorption capacity of carbon and basalt fibers mixed with matrix epoxy. At present, there is demand for nature friendly products. Basalt reinforced composites developed recently, and these mineral amorphous fibres are a valid alternative to carbon fibres for their lower cost and to glass fibres for their strength. The present paper describes briefly on basalt and carbon fibres (uni-directional) which are used as reinforcement materials for composites. The matrix epoxy (LY 556-HY 951) is taken into account to assess its influence on the evaluated parameters. In order to use reinforced composites for structural applications, it is necessary to perform a mechanical characterization. With this aim experiments like tensile strength, flexural strength, hardness and water absorption are performed. Later the mechanical properties obtained from experiments are compared with ANSYS software results.

Keywords: carbon fibre, basalt fibre, uni-directional, reinforcement, mechanical tests, water absorption test, ANSYS

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Authors: Rahul Paul, Kedar Nath Das

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The paradigm of Reinforcement Learning (RL) has become prominent in training intelligent agents to make decisions in environments that are both dynamic and uncertain. The primary objective of RL is to optimize the policy of an agent in order to maximize the cumulative reward it receives throughout a given period. Nevertheless, the process of optimization presents notable difficulties as a result of the inherent trade-off between exploration and exploitation, the presence of extensive state-action spaces, and the intricate nature of the dynamics involved. Evolutionary Optimization Methods (EOMs) have garnered considerable attention as a supplementary approach to tackle these challenges, providing distinct capabilities for optimizing RL policies and value functions. The ongoing advancement of research in both RL and EOMs presents an opportunity for significant advancements in autonomous decision-making systems. The convergence of these two fields has the potential to have a transformative impact on various domains of artificial intelligence (AI) applications. This article highlights the considerable influence of EOMs in enhancing the capabilities of RL. Taking advantage of evolutionary principles enables RL algorithms to effectively traverse extensive action spaces and discover optimal solutions within intricate environments. Moreover, this paper emphasizes the practical implementations of EOMs in the field of RL, specifically in areas such as robotic control, autonomous systems, inventory problems, and multi-agent scenarios. The article highlights the utilization of EOMs in facilitating RL agents to effectively adapt, evolve, and uncover proficient strategies for complex tasks that may pose challenges for conventional RL approaches.

Keywords: machine learning, reinforcement learning, loss function, optimization techniques, evolutionary optimization methods

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Authors: Ergun Guntekin

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Elastic constants of Fir wood (Abies cilicica) have been investigated by means of ultrasound and compression tests. Three modulus of elasticity in principal directions (EL, ER, ET), six Poisson’s ratios (ʋLR, ʋLT, ʋRT, ʋTR, ʋRL, ʋTL) and three shear modules (GLR, GRT, GLT) were determined. 20 x 20 x 60 mm samples were conditioned at 65 % relative humidity and 20ºC before testing. Three longitudinal and six shear wave velocities propagating along the principal axes of anisotropy, and additionally, three quasi-shear wave velocities at 45° angle with respect to the principal axes of anisotropy were measured. 2.27 MHz longitudinal and 1 MHz shear sensors were used for obtaining sound velocities. Stress-strain curves of the samples in compression tests were obtained using bi-axial extensometer in order to calculate elastic constants. Test results indicated that most of the elastic constants determined in the study are within the acceptable range. Although elastic constants determined from ultrasound are usually higher than those determined from compression tests, the values of EL and GLR determined from compression tests were higher in the study. The results of this study can be used in the numerical modeling of elements or systems under load using Fir wood.

Keywords: compression tests, elastic constants, fir wood, ultrasound

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Authors: M. Gangadharappa, M. Ravi Kumar, H. N. Reddappa

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The mechanical properties and morphological analysis of Al6061-Red mud particulate composites were investigated. The compositions of the composite include a matrix of Al6061 and the red mud particles of 53-75 micron size as reinforcement ranging from 0% to 12% at an interval of 2%. Stir casting technique was used to fabricate Al6061-Red mud composites. Density measurement, estimation of percentage porosity, tensile properties, fracture toughness, hardness value, impact energy, percentage elongation and percentage reduction in area. Further, the microstructures and SEM examinations were investigated to characterize the composites produced. The result shows that a uniform dispersion of the red mud particles along the grain boundaries of the Al6061 alloy. The tensile strength and hardness values increases with the addition of Red mud particles, but there is a slight decrease in the impact energy values, values of percentage elongation and percentage reduction in area as the reinforcement increases. From these results of investigation, we concluded that the red mud, an industrial waste can be used to enhance the properties of Al6061 alloy for engineering applications.

Keywords: Al6061, red mud, tensile strength, hardness and microstructures

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Authors: Jatziri Y. Moreno-Martínez, Arturo Galván, Israel Enrique Herrera Díaz, José Ramón Gasca Tirado

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In recent years, for the elevated viaducts in Mexico City, a construction system based on precast/pre-stressed concrete elements has been used, in which the bridge girders are divided in two parts by imposing a hinged support in sections where the bending moments that are originated by the gravity loads in a continuous beam are minimal. Precast concrete girders with dapped ends are a representative sample of a behavior that has complex configurations of stresses that make them more vulnerable to cracking due to flexure–shear interaction. The design procedures for ends of the dapped girders are well established and are based primarily on experimental tests performed for different configurations of reinforcement. The critical failure modes that can govern the design have been identified, and for each of them, the methods for computing the reinforcing steel that is needed to achieve adequate safety against failure have been proposed. Nevertheless, the design recommendations do not include procedures for controlling diagonal cracking at the entrant corner under service loading. These cracks could cause water penetration and degradation because of the corrosion of the steel reinforcement. The lack of visual access to the area makes it difficult to detect this damage and take timely corrective actions. Three-dimensional non-linear numerical models based on Finite Element Method to study the cracking at the entrant corner of dapped-end beams were performed using the software package ANSYS v. 11.0. The cracking was numerically simulated by using the smeared crack approach. The concrete structure was modeled using three-dimensional solid elements SOLID65 capable of cracking in tension and crushing in compression. Drucker-Prager yield surface was used to include the plastic deformations. The longitudinal post-tension was modeled using LINK8 elements with multilinear isotropic hardening behavior using von Misses plasticity. The reinforcement was introduced with smeared approach. The numerical models were calibrated using experimental tests carried out in “Instituto de Ingeniería, Universidad Nacional Autónoma de México”. In these numerical models the characteristics of the specimens were considered: typical solution based on vertical stirrups (hangers) and on vertical and horizontal hoops with a post-tensioned steel which contributed to a 74% of the flexural resistance. The post-tension is given by four steel wires with a 5/8’’ (16 mm) diameter. Each wire was tensioned to 147 kN and induced an average compressive stress of 4.90 MPa on the concrete section of the dapped end. The loading protocol consisted on applying symmetrical loading to reach the service load (180 kN). Due to the good correlation between experimental and numerical models some additional numerical models were proposed by considering different percentages of post-tension in order to find out how much it influences in the appearance of the cracking in the reentrant corner of the dapped-end beams. It was concluded that the increasing of percentage of post-tension decreases the displacements and the cracking in the reentrant corner takes longer to appear. The authors acknowledge at “Universidad de Guanajuato, Campus Celaya-Salvatierra” and the financial support of PRODEP-SEP (UGTO-PTC-460) of the Mexican government. The first author acknowledges at “Instituto de Ingeniería, Universidad Nacional Autónoma de México”.

Keywords: concrete dapped-end beams, cracking control, finite element analysis, postension

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Authors: Alexander A. Karabutov, Natalia B. Podymova, Elena B. Cherepetskaya, Vladimir A. Makarov, Yulia G. Sokolovskaya

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The laser-ultrasonic method is realized for quantifying the influence of porosity on the local Young’s modulus of isotropic composite materials. The method is based on a laser generation of ultrasound pulses combined with measurement of the phase velocity of longitudinal and shear acoustic waves in samples. The main advantage of this method compared with traditional ultrasonic research methods is the efficient generation of short and powerful probing acoustic pulses required for reliable testing of ultrasound absorbing and scattering heterogeneous materials. Using as an example samples of a metal matrix composite with reinforcing microparticles of silicon carbide in various concentrations, it is shown that to provide an effective increase in Young’s modulus with increasing concentration of microparticles, the porosity of the final sample should not exceed 2%.

Keywords: laser ultrasonic, longitudinal and shear ultrasonic waves, porosity, composite, local elastic moduli

Procedia PDF Downloads 316