Multi-objective Estimation of Distribution Algorithm Based on Joint Modeling of Objectives and Variables

This paper proposes a new multi-objective estimation of distribution algorithm (EDA) based on joint modeling of objectives and variables. This EDA uses the multi-dimensional Bayesian network as its probabilistic model. In this way it can capture the dependencies between objectives, variables and objectives, as well as the dependencies learnt between variables in other Bayesian network-based EDAs. This model leads to a problem decomposition that helps the proposed algorithm to find better trade-off solutions to the multi-objective problem. In addition to Pareto set approximation, the algorithm is also able to estimate the structure of the multi-objective problem. To apply the algorithm to many-objective problems, the algorithm includes four different ranking methods proposed in the literature for this purpose. The algorithm is applied to the set of walking fish group (WFG) problems, and its optimization performance is compared with an evolutionary algorithm and another multi-objective EDA. The experimental results show that the proposed algorithm performs significantly better on many of the problems and for different objective space dimensions, and achieves comparable results on some compared with the other algorithms.

Analysis of the stress state of a halved and tabled traditional timber scarf joint with the Finite Element Method

The purpose of this study is to determine the stress distribution in the carpentry joint of halved and tabled scarf joint with the finite element method (FEM) and its comparison with the values obtained using the theory of Strength of Materials. The stress concentration areas where analyzed and the influence of mesh refinement was studied on the results in order to determine the mesh size that provides the stress values more consistent with the theory. In areas where stress concentration is lower, different mesh sizes show similar stress values. In areas where stress concentration occurs, the same values increase considerably with the refinement of the mesh. The results show a central symmetry of the isobar lines distribution where the centre of symmetry corresponds to the geometric centre of the joint. Comparison of normal stress levels obtained by the FEM and the classical theory shows small differences, except at points of stress concentration.

Estimating the modal parameters from multiple measurement setups using a joint state space model

Computing the modal parameters of structural systems often requires processing data from multiple non-simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors, which are fixed for all measurements, while the other sensors change their position from one setup to the next. One possibility is to process the setups separately resulting in different modal parameter estimates for each setup. Then, the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global mode shapes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a new state space model that processes all setups at once. The result is that the global mode shapes are obtained automatically, and only a value for the natural frequency and damping ratio of each mode is estimated. We also investigate the estimation of this model using maximum likelihood and the Expectation Maximization algorithm, and apply this technique to simulated and measured data corresponding to different structures.

Operational modal analisys using joint statistical analysis of multiple records

In Operational Modal Analysis (OMA) of a structure, the data acquisition process may be repeated many times. In these cases, the analyst has several similar records for the modal analysis of the structure that have been obtained at di�erent time instants (multiple records). The solution obtained varies from one record to another, sometimes considerably. The differences are due to several reasons: statistical errors of estimation, changes in the external forces (unmeasured forces) that modify the output spectra, appearance of spurious modes, etc. Combining the results of the di�erent individual analysis is not straightforward. To solve the problem, we propose to make the joint estimation of the parameters using all the records. This can be done in a very simple way using state space models and computing the estimates by maximum-likelihood. The method provides a single result for the modal parameters that combines optimally all the records.

Joint assessment of water and agricultural policies: a Pan-European multidimensional modelling approach.

Sustainability and the food-water-environment nexus. Food-water linkages in global agro-economic models. The CAPRI water module. Potential to jointly assess food and water policies. Pilot case study. Further development.

Analysis and Modelling of the Structural Components of the Elbow Joint

A recent application of computer simulation is its use for the human body, which resembles a mechanism that is complemented by torques in the joints that are caused by the action of muscles and tendons. Among others, the application can be used to provide training in surgical procedures or to learn how the body works. Some of the other applications are to make a biped walk upright, to build robots that are designed on the human body or to make prostheses or robot arms to perform specific tasks. One of the uses of simulation is to optimise the movement of the human body by examining which muscles are activated and which should or should not be activated in order to improve a person?s movements. This work presents a model of the elbow joint, and by analysing the constraint equations using classic methods we go on to model the bones, muscles and tendons as well as the logic linked to the force developed by them when faced with a specific movement. To do this, we analyse the reference bibliography and the software available to perform the validation.

Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes

Computing the modal parameters of large structures in Operational Modal Analysis often requires to process data from multiple non simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. One possibility is to process the setups separately what result in different modal parameter estimates for each setup. Then the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global modes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a state space model that can be used to process all setups at once so the global mode shapes are obtained automatically and subsequently only a value for the natural frequency and damping ratio of each mode is computed. We also present how this model can be estimated using maximum likelihood and the Expectation Maximization algorithm. We apply this technique to real data measured at a footbridge.

Use of the energy-release rate in a 2 scale damage analysis of a bonded joint

Stress singularities appear at the extremities of an adhesive bond. They can produce a damage mechanism that we assimilate in this Note to a crack. The energy release rate permits to characterize its evolution. But a very refined mesh would be necessary for a real structure. Using an asymptotic method based on the small thickness of the bond a limit model with a different local behaviour is suggested. It leads to an approximation of the energy release rate

Joint 4-D variational stereo reconstruction and camera calibration refinement for oceanic sea state measurements

Validating modern oceanographic theories using models produced through stereo computer vision principles has recently emerged. Space-time (4-D) models of the ocean surface may be generated by stacking a series of 3-D reconstructions independently generated for each time instant or, in a more robust manner, by simultaneously processing several snapshots coherently in a true ?4-D reconstruction.? However, the accuracy of these computer-vision-generated models is subject to the estimations of camera parameters, which may be corrupted under the influence of natural factors such as wind and vibrations. Therefore, removing the unpredictable errors of the camera parameters is necessary for an accurate reconstruction. In this paper, we propose a novel algorithm that can jointly perform a 4-D reconstruction as well as correct the camera parameter errors introduced by external factors. The technique is founded upon variational optimization methods to benefit from their numerous advantages: continuity of the estimated surface in space and time, robustness, and accuracy. The performance of the proposed algorithm is tested using synthetic data produced through computer graphics techniques, based on which the errors of the camera parameters arising from natural factors can be simulated.

Influence of acrylic adhesive viscosity and surface roughness on the properties of adhesive joint

In adhesion, the wetting process depends on three fundamental factors: the surface topography of the adherend, the viscosity of the adhesive, and the surface energy of both. The aim of this paper is to study the influence of viscosity and surface roughness on the wetting and their effect on the bond strength. For this purpose, an acrylic adhesive with different viscosities was synthesized and some properties, such as viscosity and surface tension, were studied before adhesive curing took place. Furthermore, the contact angle and the lap-shear strength were analyzed using aluminum adherends with two different roughnesses. Scanning electron microscopy was used to determine the effect of the viscosity and the roughness on the joint interface. The results showed that the adhesive exhibits an optimal value of viscosity. Below this value, at low viscosities, the low neoprene content produces poor bond strength due to the reduced toughness of the adhesive. Additionally, it also produces a high shrinkage during curing, which leads to the apparition of residual stresses that weakens the interfacial strength. However, once the optimum value, an increase in the viscosity produces a negative effect on the joint strength as a result of an important decrease in the wettability.

An Adjustable Compliant Joint for Lower-Limb Exoskeletons

The field of exoskeletons and wearable devices for walking assistance and rehabilitation has advanced considerably over the past few years. Currently, commercial devices contain joints with stiff actuators that cannot adapt to unpredictable environments. These actuators consume more energy and may not be appropriate for human-machine interactions. Thus, adjustable compliant actuators are being cautiously incorporated into new exoskeletons and active orthoses. Some simulation-based studies have evaluated the benefits of incorporating compliant joints into such devices. Another reason that compliant actuators are desirable is that spasticity and spasmodic movements are common among patients with motor deficiencies; compliant actuators could efficiently absorb these perturbations and improve joint control. In this paper, we provide an overview of the requirements that must be fulfilled by these actuators while evaluating the behavior of leg joints in the locomotion cycle. A brief review of existing compliant actuators is conducted, and our proposed variable stiffness actuator prototype is presented and evaluated. The actuator prototype is implemented in an exoskeleton knee joint operated by a state machine that exploits the dynamics of the leg, resulting in a reduction in actuation energy demand and better adaptability to disturbances.

Modeling the Real-Time Use of Reserves in the Joint Energy and Reserve Hourly Scheduling of a Pumped Storage Plant

This paper studies the impact that different approaches of modeling the real-time use of the secondary regulation reserves have in the joint energy and reserve hourly scheduling of a price-taker pumped-storage hydropower plant. The unexpected imbalance costs due to the error between the forecasted real-time use of the reserves and the actual value are also studied and evaluated for the different approaches. The proposed methodology is applied to a daily-cycle and closed-loop pumped-storage hydropower plant. Preliminary results show that the deviations in the water volume at the end of the day are important when the percentage of the real-time use of reserves is unknown in advance, and also that the total income in all approaches after correcting these deviations is significantly lower than the maximum theoretical income.