Search results for: sand production prediction

Authors: Guoliang Fan, Aiping Li, Nan Xie, Liyun Xu, Xuemei Liu

Abstract:

Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.

Keywords: production line, layout planning, complexity measurement, optimization, mass customization

Procedia PDF Downloads 387

Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

Abstract:

Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

Procedia PDF Downloads 188

Authors: Said Boukais, Ali Kezmane, Kahil Amar, Mohand Hamizi, Hannachi Neceur Eddine

Abstract:

This paper presents an analytical study on the behavior of rectangular reinforced concrete walls with an aspect ratio between one and tow. Several experiments on such walls have been selected to be studied. Database from various experiments were collected and nominal wall strengths have been calculated using formulas, such as those of the ACI (American), NZS (New Zealand), Mexican (NTCC), and Wood equation for shear and strain compatibility analysis for flexure. Subsequently, nominal ultimate wall strengths from the formulas were compared with the ultimate wall strengths from the database. These formulas vary substantially in functional form and do not account for all variables that affect the response of walls. There is substantial scatter in the predicted values of ultimate strength. New semi empirical equation are developed using data from tests of 46 walls with the objective of improving the prediction of ultimate strength of walls with the most possible accuracy and for all failure modes.

Keywords: prediction, ultimate strength, reinforced concrete walls, walls, rectangular walls

Procedia PDF Downloads 329

Authors: Maciej Zaręba, Sławomir Lasota

Abstract:

Knowing the degree of dependencies between the sets of input signals and selected sets of indicators that measure a production system's effectiveness is of great importance in the industry. This paper introduces the SELM method that enables the selection of sets of input signals, which affects the most the selected subset of indicators that measures the effectiveness of a production system. For defined set of output indicators, the method quantifies the impact of input signals that are gathered in the continuous monitoring production system.

Keywords: manufacturing operation management, signal relationship, continuous monitoring, production systems

Procedia PDF Downloads 108

Authors: Seyed Abolhasan Naeini, Javad Shamsi Soosahab

Abstract:

The use of geosynthetic reinforcement within the footing soils is a very effective and useful method to avoid the construction of costly deep foundations. This study investigated the use of geosynthetics for soil improvement based on numerical modeling using FELA software. Pressure settlement behavior and bearing capacity ratio of foundation on geogrid reinforced sand is investigated and the effect of different parameters like as number of geogrid layers and vertical distance between elements in three different relative density soil is studied. The effects of geometrical parameters of reinforcement layers were studied for determining the optimal values to reach to maximum bearing capacity. The results indicated that the optimum range of the distance ratio between the reinforcement layers was achieved at 0.5 to 0.6 and after number of geogrid layers of 4, no significant effect on increasing the bearing capacity of footing on reinforced sandy with geogrid

Keywords: geogrid, reinforced sand, FELA software, distance ratio, number of geogrid layers

Procedia PDF Downloads 139

Authors: A. Benatiallah, D. Benatiallah, A. Harrouz, F. Abaidi, S. Mansouri

Abstract:

Photovoltaic system is established as a reliable and economical source of electricity in rural and Sahara areas, especially in developing countries where the population is dispersed, has low consumption of energy and the grid power is not extended to these areas due to viability and financial problems. The production of energy by the photovoltaic system fluctuates and depend on meteorological conditions. Wind is a very important and often neglected parameter in the behavior of the solar module. The electric performances of a solar module to the silicon are very appreciable to the blows; in the present work, we have studied the behavior of multi-crystal solar module according to the density of dust, and the principals electric feature of the solar module. An evaluation permits to affirm that a solar module under the effect of sand will collect a lower flux to the normal conditions.

Keywords: solar modulen pv, dust effect, experimental, performances

Procedia PDF Downloads 487

Authors: Mona Hejazi, Ali Motie Nasrabadi

Abstract:

Epilepsy is a persistent neurological disorder that affects more than 50 million people worldwide. Hence, there is a necessity to introduce an efficient prediction model for making a correct diagnosis of the epileptic seizure and accurate prediction of its type. In this study we consider how the Effective Connectivity (EC) patterns obtained from intracranial Electroencephalographic (EEG) recordings reveal information about the dynamics of the epileptic brain and can be used to predict imminent seizures, as this will enable the patients (and caregivers) to take appropriate precautions. We use this definition because we believe that effective connectivity near seizures begin to change, so we can predict seizures according to this feature. Results are reported on the standard Freiburg EEG dataset which contains data from 21 patients suffering from medically intractable focal epilepsy. Six channels of EEG from each patients are considered and effective connectivity using Directed Transfer Function (DTF) and Granger Causality (GC) methods is estimated. We concentrate on effective connectivity standard deviation over time and feature changes in five brain frequency sub-bands (Alpha, Beta, Theta, Delta, and Gamma) are compared. The performance obtained for the proposed scheme in predicting seizures is: average prediction time is 50 minutes before seizure onset, the maximum sensitivity is approximate ~80% and the false positive rate is 0.33 FP/h. DTF method is more acceptable to predict epileptic seizures and generally we can observe that the greater results are in gamma and beta sub-bands. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

Keywords: effective connectivity, Granger causality, directed transfer function, epilepsy seizure prediction, EEG

Procedia PDF Downloads 460

Authors: Aminah Muchdar, Nuraeni, Eddy

Abstract:

The aims of the research are: (1) to verify the cropsyst plant model of experimental data in the field of soybean plants and (2) to predict planting time and potential yield soybean plant with the use of cropsyst model. This research is divided into several stages: (1) first calibration stage which conducted in the field from June until September 2015.(2) application models stage, where the data obtained from calibration in the field will be included in cropsyst models. The required data models are climate data, ground data/soil data,also crop genetic data. The relationship between the obtained result in field with simulation cropsyst model indicated by Efficiency Index (EF) which the value is 0,939.That is showing that cropsyst model is well used. From the calculation result RRMSE which the value is 1,922%.That is showing that comparative fault prediction results from simulation with result obtained in the field is 1,92%. The conclusion has obtained that the prediction of soybean planting time cropsyst based models that have been made valid for use. and the appropriate planting time for planting soybeans mainly on rain-fed land is at the end of the rainy season, in which the above study first planting time (June 2, 2015) which gives the highest production, because at that time there was still some rain. Tanggamus varieties more resistant to slow planting time cause the percentage decrease in the yield of each decade is lower than the average of all varieties.

Keywords: soybean, Cropsyst, calibration, efficiency Index, RRMSE

Procedia PDF Downloads 174

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 137

Authors: Rehab Abdulmajed, Amr Hamada, Ahmed Elsaid, Hisashi Hayakawa, Ayman Mahrous

Abstract:

Solar emissions have a high impact on the Earth’s magnetic field, and the prediction of solar events is of high interest. Various techniques have been used in the prediction of solar wind using mathematical models, MHD models, and neural network (NN) models. This study investigates the coronal hole (CH) derived high-speed streams (HSSs) and their correlation to the CH area and create a neural network model to predict the HSSs. Two different algorithms were used to compare different models to find a model that best simulates the HSSs. A dataset of CH synoptic maps through Carrington rotations 1601 to 2185 along with Omni-data set solar wind speed averaged over the Carrington rotations is used, which covers Solar cycles (sc) 21, 22, 23, and most of 24.

Keywords: artificial neural network, coronal hole area, feed-forward neural network models, solar high speed streams

Procedia PDF Downloads 82

Authors: D. P. Rahardja, M. Rahman Hakim, V. Sri Lestari

Abstract:

An experiment was conducted to elucidate the effects of turmeric powder supplementation on egg production performance of old laying hens (104 weeks of age). There were 40 hens of Hysex Brown strain used in the study. They were caged individually, and randomly divided into 4 treatment groups of diet containing 0 (control), 1, 2 and 4 % oven dried turmeric powder for 3 periods of 4 weeks; Egg production (% hen day) and feed intake of the 4 treatment groups at the commencement of the experiment were not significantly different. In addition to egg production performance (%HD and egg weight), feed and water intakes were measured daily. The results indicated that feed intakes of the hen were significantly lowered when 4% turmeric powder supplemented, while there were no significant changes in water intakes. Egg production (%HD) were significantly increased and maintained at a higher level by turmeric powder supplementation up to 4% compared with the control, while the weight of eggs were not significantly affected. The research markedly demonstrated that supplementation of turmeric powder up to 4% could improve and maintain egg production performance of the old laying hen.

Keywords: curcumin, feed and water intake, old laying hen, egg production

Procedia PDF Downloads 477

Authors: Nursyafiqah Abdul Kahar, Niraku Rosmawati Ahmad, Hisham Mohamad, Siti Nuruljannah Mohd Marzuki

Abstract:

Assessment of geotechnical properties of the subsoil is necessary for generating relevant input for the design and construction of a foundation. It is significant for the future development in the area. The focus of this research is to investigate the preliminary geotechnical properties of the uncemented sandstone from Kati formation at Puncak Iskandar, Seri Iskandar. A series of basic soil tests, oedometer and direct shear box tests were carried out to obtain the soil parameters. The uncemented sandstone of Kati Formation was found to have well-graded and poorly graded sand distribution, depending on the location where the samples were obtained. The sand grains distribution was in a range of 82%-100% while, the specific gravity of the uncemented sandstone is in the range 2.65-2.86. The preconsolidation pressure for USB3 was 990 kPa indicating that the sandstone at USB3 sample had undergone 990 kPa of overburden pressure. The angle of friction for uncemented sandstone was ranging between 23.34°-32.92°.

Keywords: geotechnical properties, Kati formation, uncemented sandstone, oedometer test; shear box test

Procedia PDF Downloads 151

Authors: Brahim-Fares Zaidi, Malika Boudraa, Sid-Ahmed Selouani

Abstract:

Our work aims to improve our Automatic Recognition System for Dysarthria Speech (ARSDS) based on the Hidden Models of Markov (HMM) and the Hidden Markov Model Toolkit (HTK) to help people who are sick. With pronunciation problems, we applied two techniques of speech parameterization based on Mel Frequency Cepstral Coefficients (MFCC's) and Perceptual Linear Prediction (PLP's) and concatenated them with JITTER and SHIMMER coefficients in order to increase the recognition rate of a dysarthria speech. For our tests, we used the NEMOURS database that represents speakers with dysarthria and normal speakers.

Keywords: hidden Markov model toolkit (HTK), hidden models of Markov (HMM), Mel-frequency cepstral coefficients (MFCC), perceptual linear prediction (PLP’s)

Procedia PDF Downloads 153

Authors: Maciej Zaręba, Sławomir Lasota

Abstract:

Understanding the dependencies between the input signal, that controls the production system and signals, that capture its output, is of a great importance in intelligent systems. The method for identification of the relationship between signals in continuous monitoring of production systems is described in the paper. The method discovers the correlation between changes in the states derived from input signals and resulting changes in the states of output signals of the production system. The method is able to handle system inertia, which determines the time shift of the relationship between the input and output.

Keywords: manufacturing operation management, signal relationship, continuous monitoring, production systems

Procedia PDF Downloads 89

Authors: Khaled R. Khater

Abstract:

this paper is an extension to previously published two papers; all share the first part of their titles. The papers theme is soil-structure interaction in the ground of soil retaining structures. The secant pile wall is the concern, while the focus is its capping beam. The earlier papers suggested a technique to structurally analyze capping beam. It has been proved that; pile rigidity shares the capping beam rigidity to resist the wall deformations. The current paper explains how the beam-pile integration re-distributes the pile’s bending moment for the benefits of wall deformations. It is concluded that re-distribution of pile bending moment is completely different than the calculated by plain strain analysis, values, and distributions. The pile diameter, beam rigidity, pile spacing, and the 3D-analysis-effect individually or all together affect the pile bending moment. The Plaxis-2D and STAAD-Pro 3D are the used software’s. Throughout this study, three sand densities, various pile and beam rigidities, and three excavation depths, i.e., 3.0-m, 4.0-m and 5.0-m have been considered.

Keywords: bending moment, capping beam, numerical analysis, secant pile, sandy soil

Procedia PDF Downloads 174

Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

Abstract:

In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

Procedia PDF Downloads 57

Authors: Mehdi Modabberifar, Behrouz Raad, Bahman Mirzakhani

Abstract:

Flanges are widely used for connecting valves, pipes and other industrial devices such as gearboxes. Method of producing a flange has a considerable impact on the manner of their involvement with the industrial engines and gearboxes. By Using die casting instead of sand casting and machining for manufacturing flanges, production speed and dimensional accuracy of the parts increases. Also, in die casting, obtained dimensions are close to final dimensions and hence the need for machining flanges after die casting process decreases which makes a significant savings in raw materials and improves the mechanical properties of flanges. In this paper, a typical die of an industrial helical gearbox flange (size ISO 50) was designed and die casting process for producing this type of flange was simulated using ProCAST software. The results of simulation were used for optimizing die design. Finally, using the results of the analysis, optimized die was built.

Keywords: die casting, finite element, flange, helical gearbox

Procedia PDF Downloads 360

Authors: Vladimira Vytlacilova

Abstract:

Recycling of construction and demolition waste (C&DW) and their new reuse in structures is one of the solutions of environmental problems. Construction and demolition waste creates a major portion of total solid waste production in the world and most of it is used in landfills all the time. The paper deals with the situation of the recycling of the building and demolition waste in the Czech Republic during the recent years. The paper is dealing with questions of C&D waste recycling, it also characterizes construction and demolition waste in general, furthermore it analyses production of construction waste and subsequent production of recycled materials.

Keywords: Recycling, Construction and demolition waste, Recycled rubble, Waste management

Procedia PDF Downloads 295

Authors: Amir AlAmeeri, Mohamed Ibrahim

Abstract:

Various data points are constantly being measured in the production system, and due to the nature of the wells, these data points, such as pressure, temperature, water cut, etc.., fluctuations are constant, which requires high frequency monitoring and collection. It is a very difficult task to analyze these parameters manually using spreadsheets and email. An automated system greatly enhances efficiency, reduce errors, the need for constant emails which take up disk space, and frees up time for the operator to perform other critical tasks. Various production data is being recorded in an oil field, and this huge volume of data can be seen as irrelevant to some, especially when viewed on its own with no context. In order to fully utilize all this information, it needs to be properly collected, verified and stored in one common place and analyzed for surveillance and monitoring purposes. This paper describes how data is recorded by different parties and departments in the field, and verified numerous times as it is being loaded into a repository. Once it is loaded, a final check is done before being entered into a production monitoring system. Once all this is collected, various calculations are performed to report allocated production. Calculated production data is used to report field production automatically. It is also used to monitor well and surface facility performance. Engineers can use this for their studies and analyses to ensure field is performing as it should be, predict and forecast production, and monitor any changes in wells that could affect field performance.

Keywords: automation, oil production, Cheleken, exploration and production (E&P), Caspian Sea, allocation, forecast

Procedia PDF Downloads 151

Authors: Francielo Vendruscolo

Abstract:

This review summarizes the potential of starch agroindustrial residues as substrate for biohydrogen production. Types of potential starch agroindustrial residues, recent developments and bio-processing conditions for biohydrogen production will be discussed. Biohydrogen is a clean energy source with great potential to be an alternative fuel, because it releases energy explosively in heat engines or generates electricity in fuel cells producing water as only by-product. Anaerobic hydrogen fermentation or dark fermentation seems to be more favorable, since hydrogen is yielded at high rates and various organic waste enriched with carbohydrates as substrate result in low cost for hydrogen production. Abundant biomass from various industries could be source for biohydrogen production where combination of waste treatment and energy production would be an advantage. Carbohydrate-rich nitrogen-deficient solid wastes such as starch residues can be used for hydrogen production by using suitable bioprocess technologies. Alternatively, converting biomass into gaseous fuels, such as biohydrogen is possibly the most efficient way to use these agroindustrial residues.

Keywords: biofuel, dark fermentation, starch residues, food waste

Procedia PDF Downloads 390

Authors: Khaled R. Khater

Abstract:

This paper fits in soil-structure interaction division. Its theme is soil retaining structures. Hence, the cantilever secant-pile wall imposed itself, focusing on the capping beam. Four research questions are prompted and beg an answer. How to calculate the forces that control capping beam design? What is the statical system of ‘capping beam-secant pile’ as one unit? Is it possible to design it to satisfy pre-specific lateral deformation? Is it possible to suggest permissible lateral deformation limits? Briefly, pile head displacements induced by Plaxis-2D are converted to forces needed for STAAD-Pro 3D models. Those models are constructed based on the proposed structural system. This is the paper’s idea and methodology. Parametric study performed considered three sand densities, one pile rigidity, and two excavation depths, i.e., 3.0 m and 5.0 m. The research questions are satisfactorily answered. This paper could be a first step towards standardizing analysis, design, and lateral deformations checks.

Keywords: capping beam, secant pile, numerical, design aids, sandy soil

Procedia PDF Downloads 101

Authors: Mohamed Boualem Salah

Abstract:

The size and shape of soil particles reflect the formation history of the grains. In turn, the macro scale behavior of the soil mass results from particle level interactions which are affected by particle shape. Sphericity, roundness and smoothness characterize different scales associated to particle shape. New experimental data and data from previously published studies are gathered into two databases to explore the effects of particle shape on packing as well as small and large-strain properties of sandy soils. Data analysis shows that increased particle irregularity (angularity and/or eccentricity) leads to: an increase in emax and emin, a decrease in stiffness yet with increased sensitivity to the state of stress, an increase in compressibility under zero-lateral strain loading, and an increase in critical state friction angle φcs and intercept Γ with a weak effect on slope λ. Therefore, particle shape emerges as a significant soil index property that needs to be properly characterized and documented, particularly in clean sands and gravels. The systematic assessment of particle shape will lead to a better understanding of sand behavior.

Keywords: angularity, eccentricity, shape particle, behavior of soil

Procedia PDF Downloads 406

Authors: F. A. Saracoglu Varol, H. Agaccıoglu

Abstract:

Experimental studies to investigate the depth of the scour conducted at a side-weir intersection located at the 1800 curved flume which located Hydraulic Laboratory of Yıldız Technical University, Istanbul, Turkey. Side weirs were located at the middle of the straight part of the main channel. Three different lengths (25, 40 and 50 cm) and three different weir crest height (7, 10 and 12 cm) of the side weir placed on the side weir station. There is no scour when the material is only kaolin. Therefore, the cohesive bed was prepared by properly mixing clay material (kaolin) with 31% sand in all experiments. Following 24h consolidation time, in order to observe the effect of flow intensity on the scour depth, experiments were carried out for five different upstream Froude numbers in the range of 0.33-0.81. As a result of this study the relation between scour depth and upstream flow intensity as a function of time have been established. The longitudinal velocities decreased along the side weir; towards the downstream due to overflow over the side-weirs. At the beginning, the scour depth increases rapidly with time and then asymptotically approached constant values in all experiments for all side weir dimensions as in non-cohesive sediment. Thus, the scour depth reached equilibrium conditions. Time to equilibrium depends on the approach flow intensity and the dimensions of side weirs. For different heights of the weir crest, dimensionless scour depths increased with increasing upstream Froude number. Equilibrium scour depths which formed 7 cm side-weir crest height were obtained higher than that of the 12 cm side-weir crest height. This means when side-weir crest height increased equilibrium scour depths decreased. Although the upstream side of the scour hole is almost vertical, the downstream side of the hole is inclined.

Keywords: clay-sand mixed sediments, scour, side weir, hydraulic structures

Procedia PDF Downloads 301

Authors: R. Bakr, M. Elmeligy, A. Ibrahim

Abstract:

When the building loads are relatively small, challenges are often facing the foundation design especially when inappropriate soil conditions exist. These may be represented in the existence of soft soil in the upper layers of soil while sandy soil or firm cohesive soil exist in the deeper layers. In such cases, the design becomes infeasible if the piles are extended to the deeper layers, especially when there are sandy layers existing at shallower depths underlain by stiff clayey soil. In this research, models of piles terminated in sand underlain by clay soils are numerically simulated by different modelling theories. Finite element software, Plaxis 3-D Foundation was used to evaluate the pile behavior under different loading scenarios. The standard static load test according to ASTM D-1143 was simulated and compared with the real-life loading scenario. The results showed that the pile behavior obtained from the current static load test do not realistically represent that obtained from real-life loading. Attempts were carried out to capture the proper numerical loading scenario that simulates the pile behavior in real-life loading including the long-term effect. A modified method based on this research findings is proposed for the static pile loading tests. Field loading tests were carried out to validate the new method. Results obtained from both numerical and field tests by using the modified method prove that this method is more accurate in predicting the pile behavior in sand soil underlain by clay more than the current standard static load.

Keywords: numerical simulation, static load test, pile behavior, sand underlain with clay, creep

Procedia PDF Downloads 321

Authors: Xiangtuo Chen, Paul-Henry Cournéde

Abstract:

Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

Procedia PDF Downloads 226

Authors: Yang Zhou, Heli Sun, Jianbin Huang, Jizhong Zhao, Shaojie Qiao

Abstract:

Traffic prediction is a fundamental problem in urban environment, facilitating the smart management of various businesses, such as taxi dispatching, bike relocation, and stampede alert. Most earlier methods rely on identifying the intrinsic spatial-temporal correlation to forecast. However, the complex nature of this problem entails a more sophisticated solution that can simultaneously capture the mutual influence of both adjacent and far-flung areas, with the information of time-dimension also incorporated seamlessly. To tackle this difficulty, we propose a new multi-phase architecture, DSTDS (Dual Spatial-Temporal Data Scheme for traffic prediction), that aims to reveal the underlying relationship that determines future traffic trend. First, a graph-based neural network with an attention mechanism is devised to obtain the static features of the road network. Then, a multi-granularity recurrent neural network is built in conjunction with the knowledge from a grid-based model. Subsequently, the preceding output is fed into a spatial-temporal super-resolution module. With this 3-phase structure, we carry out extensive experiments on several real-world datasets to demonstrate the effectiveness of our approach, which surpasses several state-of-the-art methods.

Keywords: traffic prediction, spatial-temporal, recurrent neural network, dual data scheme

Procedia PDF Downloads 110

Authors: Volkmar Nolting

Abstract:

Fatigue crack growth prediction has become an important topic in both engineering and non-destructive evaluation. Crack propagation is influenced by the mechanical properties of the material and is conveniently modelled by the Paris-Erdogan equation. The critical crack size and the total number of load cycles are calculated. From a Larson-Miller plot the maximum operational temperature can for a given stress level be determined so that failure does not occur within a given time interval t. The study is used to determine a reasonable inspection cycle and thus enhances operational safety and reduces costs.

Keywords: fracturemechanics, crack growth prediction, lifetime of a component, structural health monitoring

Procedia PDF Downloads 38

Authors: Joselito Medina-Marin, Alexandr Karelin, Ana Tarasenko, Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Eva Selene Hernandez-Gress

Abstract:

A production line designer faces with several challenges in manufacturing system design. One of them is the assignment of buffer slots in between every machine of the production line in order to maximize the throughput of the whole line, which is known as the Buffer Allocation Problem (BAP). The BAP is a combinatorial problem that depends on the number of machines and the total number of slots to be distributed on the production line. In this paper, we are proposing a Petri Net (PN) Model to obtain the throughput in unreliable production lines, based on PN mathematical tools and the decomposition method. The results obtained by this methodology are similar to those presented in previous works, and the number of machines is not a hard restriction.

Keywords: buffer allocation problem, Petri Nets, throughput, production lines

Procedia PDF Downloads 298

Authors: Angela Luft, Sebastian Bremen, Nicolae Balc

Abstract:

Additive manufacturing processes have entered large parts of the industry and their range of application have progressed and grown significantly in the course of time. A major advantage of additive manufacturing is the innate flexibility of the machines. This corelates with the ongoing demand of creating highly flexible production environments. However, the potential of additive manufacturing technologies to enhance the flexibility of production systems has not yet been truly considered and quantified in a systematic way. In order to determine the potential of additive manufacturing technologies with regards to the strategic flexibility design in production systems, an integrated evaluation model has been developed, that allows for the simultaneous consideration of both conventional as well as additive production resources. With the described model, an operational scope of action can be identified and quantified in terms of mix and volume flexibility, process complexity, and machine capacity that goes beyond the current cost-oriented approaches and offers a much broader and more holistic view on the potential of additive manufacturing. A respective evaluation model is presented this paper.

Keywords: additive manufacturing, capacity planning, production systems, strategic production planning, flexibility enhancement

Procedia PDF Downloads 151

Authors: Flavio Araujo, Julio Lima, Paulo Scalize, Antonio Albuquerque

Abstract:

Water treatment residues (WTR) are produced during water treatment and have recently been seen as a reusable material. The aim of this research was to perform characterizations of the residue generated in the Meia-Ponte Water Treatment Plant, in Goiania, Brazil, seeking to obtain normative parameters and consider sustainable alternatives for reincorporation of the residues in the productive chain for manufacturing various materials construction. In order to reduce the environmental liabilities generated by sanitation companies and discontinue unsustainable forms of disposal. The analyzes performed: Granulometry, Scanning Electron Microscopy, and X-Ray Diffraction demonstrated the potential application of residues to replace the soil and sand, because it has characteristics compatible with small aggregate and can be used as feed stock for the manufacture of materials as ceramic and soil-cement bricks, mortars, interlocking floors and concrete artifacts.

Keywords: residue, sustainable, water treatment plants, WTR

Procedia PDF Downloads 539