Search results for: stochastic averaging method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19275

Search results for: stochastic averaging method

18915 A Method for Measurement and Evaluation of Drape of Textiles

Authors: L. Fridrichova, R. Knížek, V. Bajzík

Abstract:

Drape is one of the important visual characteristics of the fabric. This paper is introducing an innovative method of measurement and evaluation of the drape shape of the fabric. The measuring principle is based on the possibility of multiple vertical strain of the fabric. This method more accurately simulates the real behavior of the fabric in the process of draping. The method is fully automated, so the sample can be measured by using any number of cycles in any time horizon. Using the present method of measurement, we are able to describe the viscoelastic behavior of the fabric.

Keywords: drape, drape shape, automated drapemeter, fabric

Procedia PDF Downloads 656
18914 Pyrolysis of Mixed Plastic Fractions with PP, PET and PA

Authors: Rudi P. Nielsen, Karina H. Hansen, Morten E. Simonsen

Abstract:

To improve the possibility of the chemical recycling of mixed plastic waste, such as municipal plastic waste, work has been conducted to gain an understanding of the effect of typical polymers from waste (PP, PET, and PA) on the quality of the pyrolysis oil produced. Plastic fractions were pyrolyzed in a lab-scale reactor system, with mixture compositions of up to 15 wt.% PET and five wt.% PA in a PP matrix and processing conditions from 400 to 450°C. The experiments were conducted as a full factorial design and in duplicates to provide reliable results and the possibility to determine any interactions between the parameters. The products were analyzed using FT-IR and GC-MS for compositional information as well as the determination of calorific value, ash content, acid number, density, viscosity, and elemental analysis to provide further data on the fuel quality of the pyrolysis oil. Oil yield was found to be between 61 and 84 wt.%, while char yield was below 2.6 wt.% in all cases. The calorific value of the produced oil was between 32 and 46 MJ/kg, averaging at approx. 41 MJ/kg, thus close to that of heavy fuel oil. The oil product was characterized to contain aliphatic and cyclic hydrocarbons, alcohols, and ethers with chain lengths between 10 and 25 carbon atoms. Overall, it was found that the addition of PET decreased oil yield, while the addition of both PA and PET decreased oil quality in general by increasing acid number (PET), decreasing calorific value (PA), and increasing nitrogen content (PA). Furthermore, it was identified that temperature increased ammonia production from PA during pyrolysis, while ammonia production was decreased by the addition of PET.

Keywords: PET, plastic waste, polyamide, polypropylene, pyrolysis

Procedia PDF Downloads 148
18913 Zero-Dissipative Explicit Runge-Kutta Method for Periodic Initial Value Problems

Authors: N. Senu, I. A. Kasim, F. Ismail, N. Bachok

Abstract:

In this paper zero-dissipative explicit Runge-Kutta method is derived for solving second-order ordinary differential equations with periodical solutions. The phase-lag and dissipation properties for Runge-Kutta (RK) method are also discussed. The new method has algebraic order three with dissipation of order infinity. The numerical results for the new method are compared with existing method when solving the second-order differential equations with periodic solutions using constant step size.

Keywords: dissipation, oscillatory solutions, phase-lag, Runge-Kutta methods

Procedia PDF Downloads 411
18912 Reflection on Using Bar Model Method in Learning and Teaching Primary Mathematics: A Hong Kong Case Study

Authors: Chui Ka Shing

Abstract:

This case study research attempts to examine the use of the Bar Model Method approach in learning and teaching mathematics in a primary school in Hong Kong. The objectives of the study are to find out to what extent (a) the Bar Model Method approach enhances the construction of students’ mathematics concepts, and (b) the school-based mathematics curriculum development with adopting the Bar Model Method approach. This case study illuminates the effectiveness of using the Bar Model Method to solve mathematics problems from Primary 1 to Primary 6. Some effective pedagogies and assessments were developed to strengthen the use of the Bar Model Method across year levels. Suggestions including school-based curriculum development for using Bar Model Method and further study were discussed.

Keywords: bar model method, curriculum development, mathematics education, problem solving

Procedia PDF Downloads 219
18911 An Analytical Method for Bending Rectangular Plates with All Edges Clamped Supported

Authors: Yang Zhong, Heng Liu

Abstract:

The decoupling method and the modified Naiver method are combined for accurate bending analysis of rectangular thick plates with all edges clamped supported. The basic governing equations for Mindlin plates are first decoupled into independent partial differential equations which can be solved separately. Using modified Navier method, the analytic solution of rectangular thick plate with all edges clamped supported is then derived. The solution method used in this paper leave out the complicated derivation for calculating coefficients and obtain the solution to problems directly. Numerical comparisons show the correctness and accuracy of the results at last.

Keywords: Mindlin plates, decoupling method, modified Navier method, bending rectangular plates

Procedia PDF Downloads 600
18910 Modern Methods of Technology and Organization of Production of Construction Works during the Implementation of Construction 3D Printers

Authors: Azizakhanim Maharramli

Abstract:

The gradual transition from entrenched traditional technology and organization of construction production to innovative additive construction technology inevitably meets technological, technical, organizational, labour, and, finally, social difficulties. Therefore, the chosen nodal method will lead to the elimination of the above difficulties, combining some of the usual methods of construction and the myth in world practice that the labour force is subjected to a strong stream of reduction. The nodal method of additive technology will create favourable conditions for the optimal degree of distribution of labour across facilities due to the consistent performance of homogeneous work and the introduction of additive technology and traditional technology into construction production.

Keywords: parallel method, sequential method, stream method, combined method, nodal method

Procedia PDF Downloads 94
18909 About Some Results of the Determination of Alcohol in Moroccan Gasoline-Alcohol Mixtures

Authors: Mahacine Amrani

Abstract:

A simple and rapid method for the determination of alcohol in gasoline-alcohol mixtures using density measurements is described. The method can determine a minimum of 1% of alcohol by volume. The precision of the method is ± 3%.The method is more useful for field test in the quality assessment of alcohol blended fuels.

Keywords: gasoline-alcohol, mixture, alcohol determination, density, measurement, Morocco

Procedia PDF Downloads 322
18908 A TgCNN-Based Surrogate Model for Subsurface Oil-Water Phase Flow under Multi-Well Conditions

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

Procedia PDF Downloads 86
18907 The Finite Element Method for Nonlinear Fredholm Integral Equation of the Second Kind

Authors: Melusi Khumalo, Anastacia Dlamini

Abstract:

In this paper, we consider a numerical solution for nonlinear Fredholm integral equations of the second kind. We work with uniform mesh and use the Lagrange polynomials together with the Galerkin finite element method, where the weight function is chosen in such a way that it takes the form of the approximate solution but with arbitrary coefficients. We implement the finite element method to the nonlinear Fredholm integral equations of the second kind. We consider the error analysis of the method. Furthermore, we look at a specific example to illustrate the implementation of the finite element method.

Keywords: finite element method, Galerkin approach, Fredholm integral equations, nonlinear integral equations

Procedia PDF Downloads 375
18906 An Online 3D Modeling Method Based on a Lossless Compression Algorithm

Authors: Jiankang Wang, Hongyang Yu

Abstract:

This paper proposes a portable online 3D modeling method. The method first utilizes a depth camera to collect data and compresses the depth data using a frame-by-frame lossless data compression method. The color image is encoded using the H.264 encoding format. After the cloud obtains the color image and depth image, a 3D modeling method based on bundlefusion is used to complete the 3D modeling. The results of this study indicate that this method has the characteristics of portability, online, and high efficiency and has a wide range of application prospects.

Keywords: 3D reconstruction, bundlefusion, lossless compression, depth image

Procedia PDF Downloads 82
18905 A Method for Modeling Flexible Manipulators: Transfer Matrix Method with Finite Segments

Authors: Haijie Li, Xuping Zhang

Abstract:

This paper presents a computationally efficient method for the modeling of robot manipulators with flexible links and joints. This approach combines the Discrete Time Transfer Matrix Method with the Finite Segment Method, in which the flexible links are discretized by a number of rigid segments connected by torsion springs; and the flexibility of joints are modeled by torsion springs. The proposed method avoids the global dynamics and has the advantage of modeling non-uniform manipulators. Experiments and simulations of a single-link flexible manipulator are conducted for verifying the proposed methodologies. The simulations of a three-link robot arm with links and joints flexibility are also performed.

Keywords: flexible manipulator, transfer matrix method, linearization, finite segment method

Procedia PDF Downloads 428
18904 Dynamic Response Analysis of Structure with Random Parameters

Authors: Ahmed Guerine, Ali El Hafidi, Bruno Martin, Philippe Leclaire

Abstract:

In this paper, we propose a method for the dynamic response of multi-storey structures with uncertain-but-bounded parameters. The effectiveness of the proposed method is demonstrated by a numerical example of three-storey structures. This equation is integrated numerically using Newmark’s method. The numerical results are obtained by the proposed method. The simulation accounting the interval analysis method results are compared with a probabilistic approach results. The interval analysis method provides a mean curve that is between an upper and lower bound obtained from the probabilistic approach.

Keywords: multi-storey structure, dynamic response, interval analysis method, random parameters

Procedia PDF Downloads 190
18903 Risk Assessment of Flood Defences by Utilising Condition Grade Based Probabilistic Approach

Authors: M. Bahari Mehrabani, Hua-Peng Chen

Abstract:

Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

Procedia PDF Downloads 233
18902 Portfolio Optimization with Reward-Risk Ratio Measure Based on the Mean Absolute Deviation

Authors: Wlodzimierz Ogryczak, Michal Przyluski, Tomasz Sliwinski

Abstract:

In problems of portfolio selection, the reward-risk ratio criterion is optimized to search for a risky portfolio with the maximum increase of the mean return in proportion to the risk measure increase when compared to the risk-free investments. In the classical model, following Markowitz, the risk is measured by the variance thus representing the Sharpe ratio optimization and leading to the quadratic optimization problems. Several Linear Programming (LP) computable risk measures have been introduced and applied in portfolio optimization. In particular, the Mean Absolute Deviation (MAD) measure has been widely recognized. The reward-risk ratio optimization with the MAD measure can be transformed into the LP formulation with the number of constraints proportional to the number of scenarios and the number of variables proportional to the total of the number of scenarios and the number of instruments. This may lead to the LP models with huge number of variables and constraints in the case of real-life financial decisions based on several thousands scenarios, thus decreasing their computational efficiency and making them hardly solvable by general LP tools. We show that the computational efficiency can be then dramatically improved by an alternative model based on the inverse risk-reward ratio minimization and by taking advantages of the LP duality. In the introduced LP model the number of structural constraints is proportional to the number of instruments thus not affecting seriously the simplex method efficiency by the number of scenarios and therefore guaranteeing easy solvability. Moreover, we show that under natural restriction on the target value the MAD risk-reward ratio optimization is consistent with the second order stochastic dominance rules.

Keywords: portfolio optimization, reward-risk ratio, mean absolute deviation, linear programming

Procedia PDF Downloads 406
18901 A New Approach to Image Stitching of Radiographic Images

Authors: Somaya Adwan, Rasha Majed, Lamya'a Majed, Hamzah Arof

Abstract:

In order to produce images with whole body parts, X-ray of different portions of the body parts is assembled using image stitching methods. A new method for image stitching that exploits mutually feature based method and direct based method to identify and merge pairs of X-ray medical images is presented in this paper. The performance of the proposed method based on this hybrid approach is investigated in this paper. The ability of the proposed method to stitch and merge the overlapping pairs of images is demonstrated. Our proposed method display comparable if not superior performance to other feature based methods that are mentioned in the literature on the standard databases. These results are promising and demonstrate the potential of the proposed method for further development to tackle more advanced stitching problems.

Keywords: image stitching, direct based method, panoramic image, X-ray

Procedia PDF Downloads 541
18900 Numerical Solutions of Generalized Burger-Fisher Equation by Modified Variational Iteration Method

Authors: M. O. Olayiwola

Abstract:

Numerical solutions of the generalized Burger-Fisher are obtained using a Modified Variational Iteration Method (MVIM) with minimal computational efforts. The computed results with this technique have been compared with other results. The present method is seen to be a very reliable alternative method to some existing techniques for such nonlinear problems.

Keywords: burger-fisher, modified variational iteration method, lagrange multiplier, Taylor’s series, partial differential equation

Procedia PDF Downloads 429
18899 Biological Organic or Inorganic Sulfur Sources Feeding Effects on Intake and Some Blood Metabolites of Close-Up Holstein Cows

Authors: Mehdi Kazemi-Bonchenari, Esmaeil Manidari, Vahid Keshavarz

Abstract:

This study was carried out to investigate the effects of increased level of sulfur by supplementing magnesium sulfate with or without biologically organic source in dairy cow close-up diets on dry matter intake (DMI) and some blood metabolites. The 24 multiparous close-up Holstein cows averaging body weight 687.94 kg and days until expected calving date 21.89 d were allocated in three different treatments (8 cows per each) in a completely randomized design. The first treatment (T1) has contained 0.21% sulfur (DM basis), the second treatment (T2) has contained 0.41% sulfur which entirely supplied through magnesium sulfate and the third treatment (T3) has contained 0.41% sulfur which supplied through combination of magnesium sulfate and an organic source of sulfur. All the cows were fed same diet after parturition until 21 d. The DMI for both pre-calving (P < 0.001) and post-calving was affected by treatments (P < 0.004) and T2 showed the lowest DMI among treatments. Among the blood metabolites, glucose, calcium, and copper were decreased in T2 (P < 0.05). However, blood concentrations of BHBA, NEFA, urea, CPK, and AST were increased in T2 (P < 0.05). The results of the present study indicate that although magnesium sulfate has negative effect on dairy cow health and performance, a combination of magnesium sulfate and biological organic source of sulfur in close-up diets could have positive effects on DMI and performance of Holstein dairy cows.

Keywords: organic sulfur, dairy cow, intake, blood metabolites

Procedia PDF Downloads 309
18898 Development of a Data-Driven Method for Diagnosing the State of Health of Battery Cells, Based on the Use of an Electrochemical Aging Model, with a View to Their Use in Second Life

Authors: Desplanches Maxime

Abstract:

Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

Procedia PDF Downloads 69
18897 Non-Isothermal Stationary Laminar Oil Flow Numerical Simulation

Authors: Daniyar Bossinov

Abstract:

This paper considers a non-isothermal stationary waxy crude oil flow in a two-dimensional axisymmetric pipe with the transition of a Newtonian fluid to a non-Newtonian fluid. The viscosity and yield stress of waxy crude oil are highly dependent on temperature changes. During the hot pumping of waxy crude oil through a buried pipeline, a non-isothermal flow occurs due to heat transfer to the surrounding soil. This leads to a decrease in flow temperature, an increase in viscosity, the appearance of yield stress, the crystallization of wax, and the deposition of solid particles on the pipeline's inner wall. The deposition of oil solid particles reduces a pipeline flow area and leads to the appearance of a stagnant zone with thermal insulation in the near-wall area. Waxy crude oil properties change. A Newtonian fluid at low temperatures transits to a non-Newtonian fluid. The one-dimensional modeling of a non-isothermal waxy crude oil flow in a two-dimensional axisymmetric pipeline by traditional averaging of temperature and velocity over the pipeline cross-section does not allow for explaining a physics phenomenon. Therefore, in this work, a two-dimensional flow model and the heat transfer of waxy oil are constructed. The calculated data show the transition of a Newtonian fluid to a non-Newtonian fluid due to the heat exchange of waxy oil with the environment.

Keywords: non-isothermal laminar flow, waxy crude oil, stagnant zone, yield stress

Procedia PDF Downloads 26
18896 Multi-Criteria Evolutionary Algorithm to Develop Efficient Schedules for Complex Maintenance Problems

Authors: Sven Tackenberg, Sönke Duckwitz, Andreas Petz, Christopher M. Schlick

Abstract:

This paper introduces an extension to the well-established Resource-Constrained Project Scheduling Problem (RCPSP) to apply it to complex maintenance problems. The problem is to assign technicians to a team which has to process several tasks with multi-level skill requirements during a work shift. Here, several alternative activities for a task allow both, the temporal shift of activities or the reallocation of technicians and tools. As a result, switches from one valid work process variant to another can be considered and may be selected by the developed evolutionary algorithm based on the present skill level of technicians or the available tools. An additional complication of the observed scheduling problem is that the locations of the construction sites are only temporarily accessible during a day. Due to intensive rail traffic, the available time slots for maintenance and repair works are extremely short and are often distributed throughout the day. To identify efficient working periods, a first concept of a Bayesian network is introduced and is integrated into the extended RCPSP with pre-emptive and non-pre-emptive tasks. Thereby, the Bayesian network is used to calculate the probability of a maintenance task to be processed during a specific period of the shift. Focusing on the domain of maintenance of the railway infrastructure in metropolitan areas as the most unproductive implementation process at construction site, the paper illustrates how the extended RCPSP can be applied for maintenance planning support. A multi-criteria evolutionary algorithm with a problem representation is introduced which is capable of revising technician-task allocations, whereas the duration of the task may be stochastic. The approach uses a novel activity list representation to ensure easily describable and modifiable elements which can be converted into detailed shift schedules. Thereby, the main objective is to develop a shift plan which maximizes the utilization of each technician due to a minimization of the waiting times caused by rail traffic. The results of the already implemented core algorithm illustrate a fast convergence towards an optimal team composition for a shift, an efficient sequence of tasks and a high probability of the subsequent implementation due to the stochastic durations of the tasks. In the paper, the algorithm for the extended RCPSP is analyzed in experimental evaluation using real-world example problems with various size, resource complexity, tightness and so forth.

Keywords: maintenance management, scheduling, resource constrained project scheduling problem, genetic algorithms

Procedia PDF Downloads 231
18895 Spectral Domain Fast Multipole Method for Solving Integral Equations of One and Two Dimensional Wave Scattering

Authors: Mohammad Ahmad, Dayalan Kasilingam

Abstract:

In this paper, a spectral domain implementation of the fast multipole method is presented. It is shown that the aggregation, translation, and disaggregation stages of the fast multipole method (FMM) can be performed using the spectral domain (SD) analysis. The spectral domain fast multipole method (SD-FMM) has the advantage of eliminating the near field/far field classification used in conventional FMM formulation. The study focuses on the application of SD-FMM to one-dimensional (1D) and two-dimensional (2D) electric field integral equation (EFIE). The case of perfectly conducting strip, circular and square cylinders are numerically analyzed and compared with the results from the standard method of moments (MoM).

Keywords: electric field integral equation, fast multipole method, method of moments, wave scattering, spectral domain

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18894 Analytical Method Development and Validation of Stability Indicating Rp - Hplc Method for Detrmination of Atorvastatin and Methylcobalamine

Authors: Alkaben Patel

Abstract:

The proposed RP-HPLC method is easy, rapid, economical, precise and accurate stability indicating RP-HPLC method for simultaneous estimation of Astorvastatin and Methylcobalamine in their combined dosage form has been developed.The separation was achieved by LC-20 AT C18(250mm*4.6mm*2.6mm)Colum and water (pH 3.5): methanol 70:30 as mobile phase, at a flow rate of 1ml/min. wavelength of this dosage form is 215nm.The drug is related to stress condition of hydrolysis, oxidation, photolysis and thermal degradation.

Keywords: RP- HPLC, atorvastatin, methylcobalamine, method, development, validation

Procedia PDF Downloads 335
18893 Tip-Apex Distance as a Long-Term Risk Factor for Hospital Readmission Following Intramedullary Fixation of Intertrochanteric Fractures

Authors: Brandon Knopp, Matthew Harris

Abstract:

Purpose: Tip-apex distance (TAD) has long been discussed as a metric for determining risk of failure in the fixation of peritrochanteric fractures. TAD measurements over 25 millimeters (mm) have been associated with higher rates of screw cut out and other complications in the first several months after surgery. However, there is limited evidence for the efficacy of this measurement in predicting the long-term risk of negative outcomes following hip fixation surgery. The purpose of our study was to investigate risk factors including TAD for hospital readmission, loss of pre-injury ambulation and development of complications within 1 year after hip fixation surgery. Methods: A retrospective review of proximal hip fractures treated with single screw intramedullary devices between 2016 and 2020 was performed at a 327-bed regional medical center. Patients included had a postoperative follow-up of at least 12 months or surgery-related complications developing within that time. Results: 44 of the 67 patients in this study met the inclusion criteria with adequate follow-up post-surgery. There was a total of 10 males (22.7%) and 34 females (77.3%) meeting inclusion criteria with a mean age of 82.1 (± 12.3) at the time of surgery. The average TAD in our study population was 19.57mm and the average 1-year readmission rate was 15.9%. 3 out of 6 patients (50%) with a TAD > 25mm were readmitted within one year due to surgery-related complications. In contrast, 3 out of 38 patients (7.9%) with a TAD < 25mm were readmitted within one year due to surgery-related complications (p=0.0254). Individual TAD measurements, averaging 22.05mm in patients readmitted within 1 year of surgery and 19.18mm in patients not readmitted within 1 year of surgery, were not significantly different between the two groups (p=0.2113). Conclusions: Our data indicate a significant improvement in hospital readmission rates up to one year after hip fixation surgery in patients with a TAD < 25mm with a decrease in readmissions of over 40% (50% vs 7.9%). This result builds upon past investigations by extending the follow-up time to 1 year after surgery and utilizing hospital readmissions as a metric for surgical success. With the well-documented physical and financial costs of hospital readmission after hip surgery, our study highlights a reduction of TAD < 25mm as an effective method of improving patient outcomes and reducing financial costs to patients and medical institutions. No relationship was found between TAD measurements and secondary outcomes, including loss of pre-injury ambulation and development of complications.

Keywords: hip fractures, hip reductions, readmission rates, open reduction internal fixation

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18892 Application of Harris Hawks Optimization Metaheuristic Algorithm and Random Forest Machine Learning Method for Long-Term Production Scheduling Problem under Uncertainty in Open-Pit Mines

Authors: Kamyar Tolouei, Ehsan Moosavi

Abstract:

In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

Procedia PDF Downloads 105
18891 Percolation Transition in an Agglomeration of Spherical Particles

Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

Abstract:

Agglomerations of polydisperse systems of spherical particles are created in computer simulations using a simplified stochastic-hydrodynamic model: Particles sink to the bottom of the cylinder, taking into account gravity reduced by the buoyant force, the Stokes friction force, the added mass effect, and random velocity changes. Two types of particles are considered, with one of them being able to create connections to neighboring particles of the same type, thus forming a network within the agglomeration at the bottom of a cylinder. Decreasing the fraction of these particles, a percolation transition occurs. The critical regime is determined by investigating the maximum cluster size and the percolation susceptibility.

Keywords: binary system, maximum cluster size, percolation, polydisperse

Procedia PDF Downloads 61
18890 A Comparison of Bias Among Relaxed Divisor Methods Using 3 Bias Measurements

Authors: Sumachaya Harnsukworapanich, Tetsuo Ichimori

Abstract:

The apportionment method is used by many countries, to calculate the distribution of seats in political bodies. For example, this method is used in the United States (U.S.) to distribute house seats proportionally based on the population of the electoral district. Famous apportionment methods include the divisor methods called the Adams Method, Dean Method, Hill Method, Jefferson Method and Webster Method. Sometimes the results from the implementation of these divisor methods are unfair and include errors. Therefore, it is important to examine the optimization of this method by using a bias measurement to figure out precise and fair results. In this research we investigate the bias of divisor methods in the U.S. Houses of Representatives toward large and small states by applying the Stolarsky Mean Method. We compare the bias of the apportionment method by using two famous bias measurements: The Balinski and Young measurement and the Ernst measurement. Both measurements have a formula for large and small states. The Third measurement however, which was created by the researchers, did not factor in the element of large and small states into the formula. All three measurements are compared and the results show that our measurement produces similar results to the other two famous measurements.

Keywords: apportionment, bias, divisor, fair, measurement

Procedia PDF Downloads 366
18889 Solution for Thick Plate Resting on Winkler Foundation by Symplectic Geometry Method

Authors: Mei-Jie Xu, Yang Zhong

Abstract:

Based on the symplectic geometry method, the theory of Hamilton system can be applied in the analysis of problem solved using the theory of elasticity and in the solution of elliptic partial differential equations. With this technique, this paper derives the theoretical solution for a thick rectangular plate with four free edges supported on a Winkler foundation by variable separation method. In this method, the governing equation of thick plate was first transformed into state equations in the Hamilton space. The theoretical solution of this problem was next obtained by applying the method of variable separation based on the Hamilton system. Compared with traditional theoretical solutions for rectangular plates, this method has the advantage of not having to assume the form of deflection functions in the solution process. Numerical examples are presented to verify the validity of the proposed solution method.

Keywords: symplectic geometry method, Winkler foundation, thick rectangular plate, variable separation method, Hamilton system

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18888 Thermo-Mechanical Treatments of Cu-Ti Alloys

Authors: M. M. Morgham, A. A. Hameda, N. A. Zriba, H. A. Jawan

Abstract:

This paper aims to study the effect of cold work condition on the microstructure of Cu-1.5wt%Ti, and Cu-3.5wt%Ti and hence mechanical properties. The samples under investigation were machined and solution heat treated. X-ray diffraction technique is used to identify the different phases present after cold deformation by compression and also different heat treatment and also measuring the relative quantities of phases present. Metallographic examination is used to study the microstructure of the samples. The hardness measurements were used to indicate the change in mechanical properties. The results are compared with the mechanical properties obtained by previous workers. Experiments on cold compression followed by aging of Cu-Ti alloys have indicated that the most effective hardening of the material results from continuous precipitation of very fine particles within the matrix. These particles were reported to be β`-type, Cu4Ti phase. The β`-β transformation and particles coarsening within the matrix as well as a long grain boundaries were responsible for the averaging of Cu-1.5wt%Ti and Cu-3.5wt%Ti alloys. It is well know that plate like particles are β – type, Cu3Ti phase. Discontinuous precipitation was found to start at the grain boundaries and expand into grain interior. At the higher aging temperature a classic widmanstätten morphology forms giving rise to a coarse microstructure comprised of α and the equilibrium phase β. Those results were confirmed by X-ray analysis, which found that a few percent of Cu3Ti, β precipitates are formed during aging at high temperature for long time for both Cu- Ti alloys (i.e. Cu-1.5wt%Ti and Cu-3.5wt%Ti).

Keywords: metallographic, hardness, precipitation, aging

Procedia PDF Downloads 405
18887 Step Method for Solving Nonlinear Two Delays Differential Equation in Parkinson’s Disease

Authors: H. N. Agiza, M. A. Sohaly, M. A. Elfouly

Abstract:

Parkinson's disease (PD) is a heterogeneous disorder with common age of onset, symptoms, and progression levels. In this paper we will solve analytically the PD model as a non-linear delay differential equation using the steps method. The step method transforms a system of delay differential equations (DDEs) into systems of ordinary differential equations (ODEs). On some numerical examples, the analytical solution will be difficult. So we will approximate the analytical solution using Picard method and Taylor method to ODEs.

Keywords: Parkinson's disease, step method, delay differential equation, two delays

Procedia PDF Downloads 205
18886 Modeling Flow and Deposition Characteristics of Solid CO2 during Choked Flow of CO2 Pipeline in CCS

Authors: Teng lin, Li Yuxing, Han Hui, Zhao Pengfei, Zhang Datong

Abstract:

With the development of carbon capture and storage (CCS), the flow assurance of CO2 transportation becomes more important, particularly for supercritical CO2 pipelines. The relieving system using the choke valve is applied to control the pressure in CO2 pipeline. However, the temperature of fluid would drop rapidly because of Joule-Thomson cooling (JTC), which may cause solid CO2 form and block the pipe. In this paper, a Computational Fluid Dynamic (CFD) model, using the modified Lagrangian method, Reynold's Stress Transport model (RSM) for turbulence and stochastic tracking model (STM) for particle trajectory, was developed to predict the deposition characteristic of solid carbon dioxide. The model predictions were in good agreement with the experiment data published in the literature. It can be observed that the particle distribution affected the deposition behavior. In the region of the sudden expansion, the smaller particles accumulated tightly on the wall were dominant for pipe blockage. On the contrary, the size of solid CO2 particles deposited near the outlet usually was bigger and the stacked structure was looser. According to the calculation results, the movement of the particles can be regarded as the main four types: turbulent motion close to the sudden expansion structure, balanced motion at sudden expansion-middle region, inertial motion near the outlet and the escape. Furthermore the particle deposits accumulated primarily in the sudden expansion region, reattachment region and outlet region because of the four type of motion. Also the Stokes number had an effect on the deposition ratio and it is recommended for Stokes number to avoid 3-8St.

Keywords: carbon capture and storage, carbon dioxide pipeline, gas-particle flow, deposition

Procedia PDF Downloads 368