Alaa Chateauneuf

Statistical and reliability analysis for mixed-mode fracture tests applied to wood material

The integrity of timber structures is mainly related to its capacity to resist crack propagation under various load conditions. However, this phenomenon is random by nature, and the need to incorporate statistical information is mandatory for practical use in structures. This paper aims at defining a probabilistic model in order to characterize the scatter of the toughness test results of timber. The instantaneous failure tests are performed using the mixed-mode crack growth specimen. The crack tip growth is recorded by a video camera for mixed-mode ratios of 15°, 30° and 60°, where the relative displacement of loading points is recorded by LVDT sensor. The experimental energy release rate is evaluated by the compliance method. As large scatter of the energy release rate is observed, the statistical analysis is performed by using the bootstrap simulation, in order to characterize the probabilistic models in the opening and shear crack modes. The reliability analysis is then performed in order to underline the impact of the statistical uncertainties on the rupture of wood material.

Optimal number of tests to achieve and validate product reliability

The reliability validation of engineering products and systems is mandatory for choosing the best cost-effective design among a series of alternatives. Decisions at early design stages have a large effect on the overall life cycle performance and cost of products. In this paper, an optimization-based formulation is proposed by coupling the costs of product design and validation testing, in order to ensure the product reliability with the minimum number of tests. This formulation addresses the question about the number of tests to be specified through reliability demonstration necessary to validate the product under appropriate confidence level. The proposed formulation takes into account the product cost, the failure cost and the testing cost. The optimization problem can be considered as a decision making system according to the hierarchy of structural reliability measures. The numerical examples show the interest of coupling design and testing parameters.

Imperfect Preventive Maintenance Policy for Complex Systems Based on Bayesian Networks

The main challenge in maintenance planning lies in the realistic modeling of the maintenance policy. This paper is focused on the maintenance optimization of complex repairable systems using Bayesian networks. A new policy is developed for periodic imperfect preventive maintenance policy with minimal repair at failure; this policy allows us to take into consideration several types of preventive maintenance with different efficiency levels. The Bayesian networks are used for complex system modeling, allowing the evaluation of the model parameters. The Weibull parameters and the maintenance efficiency are evaluated thanks to the proposed methodology using Bayesian inference. The approach developed in this paper is applied on a real system, to determine the optimal maintenance plan for a turbo-pump in oil industry. Copyright

Utility-Based Maintenance Optimization for Complex Water-Distribution Systems Using Bayesian Networks

Water supply systems (WSS), as well as other real-world systems, are characterized by complex configurations. For these systems, it is essential to ensure appropriate utility through optimal maintenance planning. The difficulties in decision-making are much increased by lack of information regarding the operation and failure conditions. When maintenance optimization is considered for systems configured as networks, comprising a large number of components, the main challenge is to model the reliability characteristics, such as availability, taking account of the interactions and dependencies between different components. The aim of this paper is to provide an optimal Preventive Maintenance (PM) plan with a view to maximizing the utility of a complex repairable system using Bayesian Networks (BNs). For each node of the BN, the optimal PM periodicity is obtained, in accordance with the policy of periodic imperfect PM with minimal repair at failure. The system availability is then computed, by Bayesian inference, for various combinations of nodes, or subsystems, periodicities and partial renewals before the complete renewal of the whole system. A utility function is then introduced to provide the maintenance plan for the system, leading to the implementation of the best policy. The methodology is illustrated by numerical application on WSS.

Reliability of prestressed concrete structures considering creep models

The reliability of prestressed concrete structures subject to viscoelastic behaviour is investigated regarding the creep model defined by the Eurocodes. A probabilistic phenomenological model is proposed for long-term creep strains on the basis of large database of creep tests. The uncertainties in the geometrical and mechanical parameters are modelled by random variables. The proposed model considers also the statistical fitting error in creep strain predictions. The reliability analysis is performed on a prestressed concrete deck, in order to show the large impact of time-dependent phenomena on the reliability of prestressed structures, and consequently the importance of considering appropriate viscoelastic models in the design of this kind of structures. Moreover, the errors related to creep models are shown to play a very important role in the structural safety assessment.

Maintenance optimization of series systems subject to reliability constraints

Abstract The extension of maintenance optimization methodologies used for single component to multiple component systems must take into account the interdependencies that may exist between the components. Such dependencies could arise when the maintenance optimization of the system over the time is subject to constraints. In this paper, a methodology using Lagrangian relaxation techniques embedded in dynamic programming is proposed for minimizing the maintenance costs of reliability constrained series systems. The methodology could be applied to deterministic and probabilistic dynamic programming problems, as well as to partially observable Markov Decision process. The computational complexity of the proposed approach is polynomial in the number Q of the system components. Theoretical and practical issues related to the existence, and the computation of the Lagrange multipliers are considered. The proposed methodology is illustrated by a numerical application considering maintenance planning of a pipeline.

Morphology characterization of irregular particles using image analysis. Application to solid inorganic fertilizers

Abstract This research deals with how to characterize the morphology of mineral fertilizers using dynamic image analysis. A machine-vision system was first developed to capture digital images of irregular particles. The vision system was designed as a mechanical assembly to generate a flow of separated grains passing in front of a camera, combined with a flash. The vision system’s parameters were then calibrated and optimized – particularly in terms of image resolution, light sources and exposure time. An optimal value of 34u202fpixels/mm was obtained for the image resolution. Then, the system was tested and validated by imaging perfect plastic spheres of known size. Secondly, an image-processing algorithm was developed to extract geometrical and morphological information for various particles. Various shape parameters, describing the differences of a particle from a reference geometric form (e.g. a circle or ellipse), were calculated as outputs of the image-processing treatment. Statistical analysis was then applied to determine the convergence of shape parameter distributions and also the repeatability of measurements. 45 fertilizers, with grain shapes ranging from highly irregular to nearly spherical, were prepared and imaged. For all these fertilizers, the distribution of shape parameters was quantitative, representative, repeatable and reproducible using the machine-vision system developed. In order to investigate the best parameters for characterizing particle morphology, statistical correlation was applied to deduce a list of independent shape parameters. These parameters were relevant and could further be used to characterize the morphology of any fertilizer. The independent parameters thus obtained were subsequently used to detect the correlation between morphology and distance traveled by fertilizer particles thrown out by a centrifugal spreader. Experimental tests were conducted using the CEMIB device to determine fertilizer spread pattern from spinning discs. Results showed that, within the same range of size, mass density and spreader operating parameters, spherical and rounded particles traveled further than elongated and angular particles. The angularity index parameter, denoted by ANGInd (which characterizes whether a particle is rounded or angular), showed most potential application to explain the aerodynamic behavior of irregular particles spread by spinning discs.

Probabilistic mechanical modelling of concrete creep based on the boundary element method

The prediction of the future structural behaviour is an essential activity during the design phase. In this study, a novel numerical framework is proposed for investigating the future structural behaviour of two-dimensional structures. The model utilizes the boundary element method for obtaining the mechanical responses. The constitutive material is admitted to manifest viscoelastic response, which enables it to creep. The input parameters such as material, loads parameters and geometry dimensions are considered to possess random characteristics. A probabilistic criterion is proposed using metamodelling by the response surface method. All these features make the proposed numerical model more realistic. As an application, a specific structure is utilized, which is inspired from the real world. The results demonstrate that small geometric deviations do not necessarily impact the global reliability of the structure. At the same time, load estimations have major influence on the global structural reliability. The numerical framework proposed can be utilized for preliminary investigations on the design phase in order to aid the engineers into the decision-making process. Moreover, these observations demonstrate that the boundary element method can be efficiently coupled to other numerical strategies in order to elaborate new robust numerical frameworks able to represent realistically engineering problems.

On-the-field simulation of fertilizer spreading: Part 1 – Modeling

Abstract The field elevation and its variation represent a disturbance in the spreading process that is not handled yet by centrifugal spreaders. This stems in part from the knowledge gap regarding the possible application errors of fertilizer on non-flat fields. To address this issue, a new model has been developed, integrating both the field elevation and the tractor motion. The model was employed in the paper (“On-the-field simulation of fertilizer spreading: Part 2 – Uniformity investigation”). The model was based on transformation matrices to update the initial conditions of the ballistic flight of particles in the field coordinate system at each new position of the tractor, as it moves along a given trajectory on a given DEM (digital elevation model). An experimental validation was conducted using a radial bench in different static configurations, which also provided the unknown input data for the model. High correlation coefficients were found between the characteristics of the simulated and measured spread patterns, even where, in the simulation, the model parameters were fixed and the spreader inclination varied. Thus, in addition to proving the reliability of the model, the measurements also helped determining the limits of validity of the assumptions within which on-the-field simulations can be carried out.

On-the-field simulation of fertilizer spreading: Part 2 – Uniformity investigation

Abstract Modern centrifugal spreaders use active control devices to manage various disturbances affecting the spreading uniformity on flat fields. Yet, non-flat fields that are also likely to cause application errors, are still not taken into consideration. This was highlighted in some experimental studies, limited to the case of single spread patterns on regular non-flat fields. In this study, overall spread patterns uniformity was investigated through simulation. The model used was presented in the paper (“On-the-field simulation of fertilizer spreading: Part 1 – Modeling”). Using computer generated DEMs (digital elevation models), several cases were investigated: regular fields were represented by a longitudinal and side slope, and irregular fields by a longitudinal and side slope break. The results obtained were in the form of application rate maps, showing the areas of overapplication and underapplication. These areas were also characterized by the mean longitudinal and transverse application rates, which gave the application errors magnitudes. The latter were in the case of irregular fields, up to a maximum of +45%, and a minimum of −25%, around the theoretical value of 100% for a perfectly uniform area. These application errors were mainly attributable to altered ballistic flights range, caused by the difference between the tractor and spread surface inclination, and to a lesser extent, by the work of the gravity. These results allow bridging the knowledge gap around overall spread patterns uniformity on non-flat fields. They can also help in developing new active control devices.