Search results for: Deep cold rolling

Authors: Haoshui Yu, Donghoi Kim, Truls Gundersen

Abstract:

Low-temperature waste heat is abundant in the process industries, and large amounts of Liquefied Natural Gas (LNG) cold energy are discarded without being recovered properly in LNG terminals. Power generation is an effective way to utilize low-temperature waste heat and LNG cold energy simultaneously. Organic Rankine Cycles (ORCs) and CO₂ power cycles are promising technologies to convert low-temperature waste heat and LNG cold energy into electricity. If waste heat and LNG cold energy are utilized simultaneously in one system, the performance may outperform separate systems utilizing low-temperature waste heat and LNG cold energy, respectively. Low-temperature waste heat acts as the heat source and LNG regasification acts as the heat sink in the combined system. Due to the large temperature difference between the heat source and the heat sink, cascaded power cycle configurations are proposed in this paper. Cascaded power cycles can improve the energy efficiency of the system considerably. The cycle operating at a higher temperature to recover waste heat is called top cycle and the cycle operating at a lower temperature to utilize LNG cold energy is called bottom cycle in this study. The top cycle condensation heat is used as the heat source in the bottom cycle. The top cycle can be an ORC, transcritical CO₂ (tCO₂) cycle or supercritical CO₂ (sCO₂) cycle, while the bottom cycle only can be an ORC due to the low-temperature range of the bottom cycle. However, the thermodynamic path of the tCO₂ cycle and sCO₂ cycle are different from that of an ORC. The tCO₂ cycle and the sCO₂ cycle perform better than an ORC for sensible waste heat recovery due to a better temperature match with the waste heat source. Different combinations of the tCO₂ cycle, sCO₂ cycle and ORC are compared to screen the best configurations of the cascaded power cycles. The influence of the working fluid and the operating conditions are also investigated in this study. Each configuration is modeled and optimized in Aspen HYSYS. The results show that cascaded tCO₂/ORC performs better compared with cascaded ORC/ORC and cascaded sCO₂/ORC for the case study.

Keywords: LNG cold energy, low-temperature waste heat, organic Rankine cycle, supercritical CO2 cycle, transcritical CO2 cycle.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1014

Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

Abstract:

2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: Artificial Intelligence, machine learning, deep learning, convolutional neural networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1180

Authors: A. Rabin, G. Mazor, I. Ladizhenski, R. Z. Shneck

Abstract:

The hardness and hardenability of AISI D2 cold work tool steel with conventional quenching (CQ), deep cryogenic quenching (DCQ) and rapid deep cryogenic quenching heat treatments caused by temporary porous coating based on magnesium sulfate was investigated. Each of the cooling processes was examined from the perspective of the full process efficiency, heat flux in the austenite-martensite transformation range followed by characterization of the temporary porous layer made of magnesium sulfate using confocal laser scanning microscopy (CLSM), surface and core hardness and hardenability using Vickers hardness technique. The results show that the cooling rate (CR) at the austenite-martensite transformation range has a high influence on the hardness of the studied steel.

Keywords: AISI D2, controllable cooling, magnesium sulfate coating, rapid cryogenic heat treatment, temporary porous layer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 292

Authors: Maziar Ramezani, Thomas Neitzert

Abstract:

This paper gives an overview of a deep drawing process by pressurized liquid medium separated from the sheet by a rubber diaphragm. Hydroforming deep drawing processing of sheet metal parts provides a number of advantages over conventional techniques. It generally increases the depth to diameter ratio possible in cup drawing and minimizes the thickness variation of the drawn cup. To explore the deformation mechanism, analytical and numerical simulations are used for analyzing the drawing process of an AA6061-T4 blank. The effects of key process parameters such as coefficient of friction, initial thickness of the blank and radius between cup wall and flange are investigated analytically and numerically. The simulated results were in good agreement with the results of the analytical model. According to finite element simulations, the hydroforming deep drawing method provides a more uniform thickness distribution compared to conventional deep drawing and decreases the risk of tearing during the process.

Keywords: Deep drawing, Hydroforming, Rubber diaphragm

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2858

Authors: S. Jeon, J. Kim, H. Choi

Abstract:

KSLV-I(Korea Space Launch Vehicle-I) is designed as a launch vehicle to enter a 100 kg-class satellite to the LEO(Low Earth Orbit). Attitude angles of the upper-stage, including roll, pitch and yaw are controlled by the cold gas thruster system using nitrogen gas. The cold gas thruster is an actuator in the RCS(Reaction Control System). To design an attitude controller for the upper-stage, thrust measurement in vacuum condition is required. In this paper, the new thrust measurement system and calibration mechanism are developed and measurement errors and signal processing method are presented.

Keywords: cold gas thruster, launch vehicle, thrust measurement, calibration mechanism, signal processing

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2708

Authors: Vishal Naranje, S. Kumar

Abstract:

In this paper a low cost knowledge base system (KBS) framework is proposed for design of deep drawing die and procedure for developing system modules. The task of building the system is structured into different modules for major activities of design of deep drawing die. A manufacturability assessment module of the proposed framework is developed to check the manufacturability of deep drawn parts. The technological knowledge is represented by using IF- THEN rules and it is coded in AutoLISP language. The module is designed to be loaded into the prompt area of AutoCAD. The cost of implementation of proposed system makes it affordable for small and medium scale sheet metal industries.

Keywords: Knowledge base system, Deep drawing die, Manufacturability, Sheet metal.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2069

Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

Abstract:

Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: Cold-start, expectation propagation, multi-armed bandits, Thompson sampling, variational inference.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 486

Authors: Mannal Tariq

Abstract:

Construction industry is making progress at a high pace. The trend of the world is getting more biased towards the high rise buildings. Deep beams are one of the most common elements in modern construction having small span to depth ratio. Deep beams are mostly used as transfer girders. This experimental study consists of 16 reinforced concrete (RC) deep beams. These beams were divided into two groups; A and B. Groups A and B consist of eight beams each, having 381 mm (15 in) and 457 mm (18 in) depth respectively. Each group was further subdivided into four sub groups each consisting of two identical beams. Each subgroup was comprised of solid/control beam (without opening), opening above neutral axis (NA), at NA and below NA. Except for control beams, all beams with openings were strengthened with carbon fibre reinforced polymer (CFRP) vertical strips. These eight groups differ from each other based on depth and location of openings. For testing sake, all beams have been loaded with two symmetrical point loads. All beams have been designed based on strut and tie model concept. The outcome of experimental investigation elaborates the difference in the shear behaviour of deep beams based on depth and location of circular openings variation. 457 mm (18 in) deep beam with openings above NA show the highest strength and 381 mm (15 in) deep beam with openings below NA show the least strength. CFRP sheets played a vital role in increasing the shear capacity of beams.

Keywords: CFRP, deep beams, openings in deep beams, strut and tie model, shear behaviour.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1299

Authors: N.Pourmahmoud, S.Akhesmeh

Abstract:

This work has been carried out in order to provide an understanding of the physical behaviors of the flow variation of pressure and temperature in a vortex tube. A computational fluid dynamics model is used to predict the flow fields and the associated temperature separation within a Ranque–Hilsch vortex tube. The CFD model is a steady axisymmetric model (with swirl) that utilizes the standard k-ε turbulence model. The second–order numerical schemes, was used to carry out all the computations. Vortex tube with a circumferential inlet stream and an axial (cold) outlet stream and a circumferential (hot) outlet stream was considered. Performance curves (temperature separation versus cold outlet mass fraction) were obtained for a specific vortex tube with a given inlet mass flow rate. Simulations have been carried out for varying amounts of cold outlet mass flow rates. The model results have a good agreement with experimental data.

Keywords: Ranque–Hilsch vortex tube, Temperature separation, k–ε model, cold mass fraction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2359

Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: Natural language processing, sentiment analysis, document analysis, multimodal sentiment analysis, deep learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1882

Authors: N. Kh. Gomidze, I. N. Jabnidze, K. A. Makharadze

Abstract:

The influence of inhomogeneities of plasma and statistical characteristics on the propagation of signal is very actual in wireless communication systems. While propagating in the media, the deformation and evaluation of the signal in time and space take place and on the receiver we get a deformed signal. The present article is dedicated to studying the space-time evolution of rectangular, sinusoidal, exponential and bi-exponential impulses via numerical experiment in the collisional, cold plasma. The presented method is not based on the Fourier-presentation of the signal. Analytically, we have received the general image depicting the space-time evolution of the radio impulse amplitude that gives an opportunity to analyze the concrete results in the case of primary impulse.

Keywords: Collisional, cold plasma, rectangular pulse signal, impulse envelope.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 796

Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Currently the most prevalent deep learning methods require a large amount of data for training, whereas few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: Few-shot learning, triplet network, adaptive margin, deep learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 821

Authors: S.H. Suseno, T.A.Yang, W.N. Abdullah , N.A. Febrianto, W.N. Asti, B. Bahtiar, Hamidah, A. Suman, Desniar, A. Hartoyo

Abstract:

Sixteen selected deep-sea fish obtained from Southern Java Ocean and Western Sumatra Ocean was analyzed to determine its proximate, fatty acid and mineral composition. The moisture content was ranged from 64.38 to 86.04 %, ash from 0.17 to 0.69 %, the fat content was 1.54 – 13.30 % while the protein content varied from 15.84 to 23.60%. Among the fatty acids, oleic acid and palmitic acid was the dominant MUFA and SFA. Linoleic acid was the highest PUFA found at the selected deep-sea fish. Phospor was the highest macroelement concentration on selected deep-sea fish, followed by K, Ca, Mg and Iod, Fe and Zn among microelement. The trace concentration was found at Se microelement.

Keywords: deep-sea fish, fatty acid, microelement, macroelement, monounsaturated fatty acid, proximate, polyunsaturated fatty acids.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1797

Authors: S. Sendhil Kumar, M. Senthil Kumar

Abstract:

Maintenance and design engineers have great concern for the functioning of rotating machineries due to the vibration phenomenon. Improper functioning in rotating machinery originates from the damage to rolling element bearings. The status of rolling element bearings require advanced technologies to monitor their health status efficiently and effectively. Avoiding vibration during machine running conditions is a complicated process. Vibration simulation should be carried out using suitable sensors/ transducers to recognize the level of damage on bearing during machine operating conditions. Various issues arising in rotating systems are interlinked with bearing faults. This paper presents an approach for fault diagnosis of bearings using neural networks and time/frequencydomain vibration analysis.

Keywords: Bearing vibration, Condition monitoring, Fault diagnosis, Frequency domain.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2473

Authors: Amir Hossein Daei Sorkhabi, Farid Vakili Tahami

Abstract:

In this paper, creep constitutive equations of base (Parent) and weld materials of the weldment for cold-drawn 304L stainless steel have been obtained experimentally. For this purpose, test samples have been generated from cold drawn bars and weld material according to the ASTM standard. The creep behavior and properties have been examined for these materials by conducting uniaxial creep tests. Constant temperatures and constant load uni-axial creep tests have been carried out at two high temperatures, 680 and 720 oC, subjected to constant loads, which produce initial stresses ranging from 240 to 360 MPa. The experimental data have been used to obtain the creep constitutive parameters using numerical optimization techniques.

Keywords: Creep, Constitutive equation, Cold-drawn 304L stainless steel, Weld, Base material

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2714

Authors: Vijay Kumar Sharma, Manisha Pattanaik, Balwinder Raj

Abstract:

Minimizations of power dissipation, chip area with higher circuit performance are the necessary and key parameters in deep submicron regime. The leakage current increases sharply in deep submicron regime and directly affected the power dissipation of the logic circuits. In deep submicron region the power dissipation as well as high performance is the crucial concern since increasing importance of portable systems. Number of leakage reduction techniques employed to reduce the leakage current in deep submicron region but they have some trade-off to control the leakage current. ONOFIC approach gives an excellent agreement between power dissipation and propagation delay for designing the efficient CMOS logic circuits. In this article ONOFIC approach is compared with LECTOR technique and output results show that ONOFIC approach significantly reduces the power dissipation and enhance the speed of the logic circuits. The lower power delay product is the big outcome of this approach and makes it an influential leakage reduction technique.

Keywords: Deep submicron, Leakage Current, LECTOR, ONOFIC, Power Delay Product

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2455

Authors: Alnouss M. Ahmed, Al-Nuaimi A. Ibrahim

Abstract:

In this paper, the energy performance of a selected UHDE Ammonia plant is optimized by conducting heat integration through waste heat recovery and the synthesis of a heat exchange network (HEN). Minimum hot and cold utility requirements were estimated through IChemE spreadsheet. Supporting simulation was carried out using HYSYS software. The results showed that there is no need for heating utility while the required cold utility was found to be around 268,714 kW. Hence a threshold pinch case was faced. Then, the hot and cold streams were matched appropriately. Also, waste heat recovered resulted with savings in HP and LP steams of approximately 51.0% and 99.6%, respectively. An economic analysis on proposed HEN showed very attractive overall payback period not exceeding 3 years. In general, a net saving approaching 35% was achieved in implementing heat optimization of current studied UHDE Ammonia process.

Keywords: Ammonia, Energy Optimization, Heat Exchange Network and Techno-Economic Analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4497

Authors: J. D. Burges, M. J. Hall, E. G. Lightsey

Abstract:

A new dual-fluid concept was studied that could eventually find application for cold-gas propulsion for small space satellites or other constant flow applications. In basic form, the concept uses two different refrigerant working fluids, each having a different saturation vapor pressure. The higher vapor pressure refrigerant remains in the saturation phase and is used to pressurize the lower saturation vapor pressure fluid (the propellant) which remains in the compressed liquid phase. A demonstration thruster concept based on this principle was designed and built to study its operating characteristics. An automotive-type electronic fuel injector was used to meter and deliver the propellant. Ejected propellant mass and momentum were measured for several combinations of refrigerants and hydrocarbon fluids. The thruster has the advantage of delivering relatively large total impulse at low tank pressure within a small volume.

Keywords: cold-gas, nano-satellite, R134a, thruster

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4218

Authors: Delowar Hossain, Genci Capi

Abstract:

This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: Deep learning, genetic algorithm, object recognition, robot grasping.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2080

Authors: Mehdi Salehi Barough, Saviz Sehat Kashani, A.A. Bidokhti, A.Ranjbar

Abstract:

The presence of cold air with the convergent topography of the Lut valley over the valley-s sloping terrain can generate Low Level Jets (LLJ). Moreover, the valley-parallel pressure gradients and northerly LLJ are produced as a result of the large-scale processes. In the numerical study the regional MM5 model was run leading to achieve an appropriate dynamical analysis of flows in the region for summer and winter. The results of this study show the presence of summer synoptical systems cause the formation of north-south pressure gradients in the valley which could be led to the blowing of winds with the velocity more than 14 ms-1 and vulnerable dust and wind storms lasting more than 120 days. Whereas the presence of cold air masses in the region in winter, cause the average speed of LLJs decrease. In this time downslope flows are noticeable in creating the night LLJs.

Keywords: Cold advection, Low Level Jet, MM5 Model, Pressure gradient

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478

Authors: Yifan Fan, Xudong Luo, Pingping Lin

Abstract:

Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: Dialogue management, response generation, reinforcement learning, deep learning, evaluation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 717

Authors: C. H. S. Vidyasagar, D. B. Karunakar

Abstract:

In this present work, five different composite samples with AA2024 as matrix and varying amounts of yttrium (0.1-0.5 wt.%) as reinforcement are developed through cold compaction. The microstructures of the developed composite samples revealed that the yttrium reinforcement caused grain refinement up to 0.3 wt.% and beyond which the refinement is not effective. The microstructure revealed Al2Cu precipitation which strengthened the composite up to 0.3 wt.% yttrium reinforcement. Upon further increase in yttrium reinforcement, the intermetallics and the precipitation coarsen and their corresponding strengthening effect decreases. The mechanical characterization revealed that the composite sample reinforced with 0.3 wt.% yttrium showed highest mechanical properties like 82 HV of hardness, 276 MPa Ultimate Tensile Strength (UTS), 229 MPa Yield Strength (YS) and an elongation (EL) of 18.9% respectively. However, the relative density of the developed composites decreased with the increase in yttrium reinforcement.

Keywords: Mechanical properties, AA 2024 matrix, yttrium reinforcement, cold compaction, precipitation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 580

Authors: D. I. Ekine, C. C. Akpanibah

Abstract:

This paper analyses the productivity of median scale battery cage and deep litter chicken egg producers in Rivers State, Nigeria. 90 battery cage and 90 deep litter farmers giving a total of 180 farmers were sampled through a multistage sampling procedure. Mean productivity was higher for the battery cage than the deep litter farmers at 2.65 and 2.33 respectively. Productivity of battery cage farmers were positively influenced by age, extension contacts, experience and feed quantity while the productivity of deep litter farmers was positively influenced by age, extension contacts, household size, experience and labour. The major constraints identified by both categories are high cost of feed, high price of day-old chick, inadequate finance, lack of credit and high cost of drug/vaccination. Furthermore, the work recommends that government should assist chicken egg farmers through subsidies of input resources and put policies to make financial institutions give out loans at low interest rate to the farmers. The farmers should abide by the recommended number of birds per unit area while stocking.

Keywords: Productivity, battery cage, deep litter, median scale, egg production.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 172

Authors: Haiyan. Li, Jitendra. Paliwal, Digvir S. Jayas, Noel D. G. White

Abstract:

A study was undertaken to investigate the effect of liquid nitrogen aeration on mortalities of adult Cryptolestes furrugineus, rusty grain beetles, in a prototype cardboard grain bin equipped with an aeration system. The grain bin was filled with Hard Red Spring wheat and liquid nitrogen was introduced from the bottom of the bin. The survival of both cold acclimated and unacclimated C. furrugineus was tested. The study reveals that cold acclimated insects had higher survival than unacclimated insects under similar cooling conditions. In most cases, mortalities of as high as 100% were achieved at the bottom 100 cm of the grain bin for unacclimated insects for most of the trials. Insect survival increased as the distance from the bottom of the grain bin increased. There was no adverse effect of liquid nitrogen aeration on wheat germination.

Keywords: Cold acclimated, liquid nitrogen aeration, mortalities, rusty grain beetles.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1481

Authors: M. A. Sanda, B. Johansson, J. Johansson

Abstract:

The purpose of this paper is to conceptualize a futureoriented human work environment and organizational activity in deep mines that entails a vision of good and safe workplace. Futureoriented technological challenges and mental images required for modern work organization design were appraised. It is argued that an intelligent-deep-mine covering the entire value chain, including environmental issues and with work organization that supports good working and social conditions towards increased human productivity could be designed. With such intelligent system and work organization in place, the mining industry could be seen as a place where cooperation, skills development and gender equality are key components. By this perspective, both the youth and women might view mining activity as an attractive job and the work environment as a safe, and this could go a long way in breaking the unequal gender balance that exists in most mines today.

Keywords: Mining activity; deep mining; human operators; intelligent deep mine; work environment; organizational activity.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1607

Authors: H. Meddah, M. Berediaf-Bourahla, B. El-Djouzi, N. Bourahla

Abstract:

Shear walls made of cold formed steel are used as lateral force resisting components in residential and low-rise commercial and industrial constructions. The seismic design analysis of such structures is often complex due to the slenderness of members and their instability prevalence. In this context, a simplified modeling technique across the panel is proposed by using the finite element method. The approach is based on idealizing the whole panel by a nonlinear shear link element which reflects its shear behavior connected to rigid body elements which transmit the forces to the end elements (studs) that resist the tension and the compression. The numerical model of the shear wall panel was subjected to cyclic loads in order to evaluate the seismic performance of the structure in terms of lateral displacement and energy dissipation capacity. In order to validate this model, the numerical results were compared with those from literature tests. This modeling technique is particularly useful for the design of cold formed steel structures where the shear forces in each panel and the axial forces in the studs can be obtained using spectrum analysis.

Keywords: Cold-formed steel, cyclic loading, modeling technique, nonlinear analysis, shear wall panel.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1216

Authors: Barenten Suciu

Abstract:

In this work, effects of the friction and truncation on the dynamics of a double-cone gravitational motor, self-propelled on a straight V-shaped horizontal rail, are evaluated. Such mechanism has a variable radius of contact, and, on one hand, it is similar to a pulley mechanism that changes the potential energy into the kinetic energy of rotation, but on the other hand, it is similar to a pendulum mechanism that converts the potential energy of the suspended body into the kinetic energy of translation along a circular path. Movies of the self- propelled double-cones, made of S45C carbon steel and wood, along rails made of aluminum alloy, were shot for various opening angles of the rails. Kinematical features of the double-cones were estimated through the slow-motion processing of the recorded movies. Then, a kinematical model is derived under assumption that the distance traveled by the contact points on the rectilinear rails is identical with the distance traveled by the contact points on the truncated conical surface. Additionally, a dynamic model, for this particular contact problem, was proposed and validated against the experimental results. Based on such model, the traction force and the traction torque acting on the double-cone are identified. One proved that the rolling traction force is always smaller than the sliding friction force; i.e., the double-cone is rolling without slipping. Results obtained in this work can be used to achieve the proper design of such gravitational motor.

Keywords: Truncated double-cone, friction, rolling and sliding, dynamic model, gravitational motor.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1293

Authors: Rouaz Idriss, Bourahla Nour-Eddine, Kahlouche Farah, Rafa Sid Ali

Abstract:

The stability of structures made of light-gauge steel depends highly on the contribution of Shear Wall Panel (SWP) systems under horizontal forces due to wind or earthquake loads. Steel plate sheathing is often used with these panels made of cold formed steel (CFS) to improve its shear strength. In order to predict the shear strength resistance, two methods are presented in this paper. In the first method, the steel plate sheathing is modeled with plats strip taking into account only the tension and compression force due to the horizontal load, where both track and stud are modeled according to the geometrical and mechanical characteristics of the specimen used in the experiments. The theoretical background and empirical formulations of this method are presented in this paper. However, the second method is based on a micro modeling of the cold formed steel Shear Wall Panel “CFS-SWP” using Abaqus software. A nonlinear analysis was carried out with an in-plan monotonic load. Finally, the comparison between these two methods shows that the micro modeling with Abaqus gives better prediction of shear resistance of SWP than strips method. However, the latter is easier and less time consuming than the micro modeling method.

Keywords: Cold Formed Steel Shear Wall Panel, CFS-SWP, micro modeling, nonlinear analysis, strip method.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1471

Authors: Ashkan Shafee, Ahmad Fahimifar

Abstract:

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, pile group, inclined loading, lateral deformation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 934

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. However, 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 are 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.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 603