Shape and force control of cable structures with minimal actuators and actuation

Shape adjustment and stress control can be considered as one of the effective parameters in prestressed cable structures since such structures are widely constructed nowadays due to their characteristics. The assembly errors and applied loads hugely affect the cables’ nodal positions and stress due to their delicacy. The former could disturb the shape, which affects the appearance and the function of the structure. In contrast, the latter may increase the stress in some cables above the upper limit or induce slack in some others. Accordingly, a technique has been proposed that combined fmincon optimization that relies on four different algorithms with a controlling approach based on the force method. The presented method aims to minimize the total amount of actuation and miniaturize the number of actuators. The targets of previously confirmed techniques can be obtained with less actuation and fewer actuators by using the current technique. Based on the verified examples, the advantage of the current approach over the quoted methods is up to 55% and 37% in terms of the number of actuators and the total amount of actuation, respectively.

Prediction of Inhomogeneous Stress in Metal Structures: A Hybrid Approach Combining Eddy Current Technique and Finite Element Method

Concentrated stresses and residual ones are critical for the metal structures’ health, because they can cause microcracks that require emergency maintenance or can result in potential accidents. Therefore, an accurate approach to the measurement of stresses is key for ensuring the health of metal structures. The eddy current technique is an effective approach to detect the stress according to the piezoresistive effect. However, it is limited to detect the surface stress due to the skin effect. In engineering, the stress distribution is inhomogeneous; therefore, to predict the inhomogeneous stress distribution, this paper proposes a nondestructive approach which combines the eddy current technique and finite element (FE) method. The experimental data achieved through the eddy current technique determines the relationship between the applied force and the magnetic flux density, while numerical simulations through the FE method bridge the relationship between the magnetic flux density and the stress distribution in different directions. Therefore, we can predict the inhomogeneous stress nondestructively. As a case study, the applied stress in a three-point-bending simply supported beam was evaluated, and the relative error is less than 8% in the whole beam. This approach can be expected to predict the residual stress in metal structures, such as rail and vehicle structures, if the stress distribution pattern is known.

INTEGRATION OF BAYESIAN MODEL AND ADAPTIVE CLUSTERED SAMPLING INTO CONTACT TRACING TO CURB THE SPREAD OF COVID -19 CASES

Covid-19 is a communicable virus that causes serious illness (Severe acutepiratory syndrome (SARS)) and middle east respiratory syndrome (MARS)). İts outbreak started in Wuhan, China on December 8, 2019. Fever, cough, tiredness are its signs and symptoms and appear between two to fourteen days after exposure. The severity of COVID-19 can include complications; pneumonia, heart problems, acute kidney injuries. Covid-19 careers should be identified in order to curb the spread of the virus within a population. In this regards, contact tracing is the current technique in use to identify and track the Covid-19 carriers. The aim is to curb the spread of the virus within the population. In order to achieve this goal effectively, appropriate technique is required in the identification of Covid-19 carriers and Modeling. It is known that Covid-19 carriers are hidden, clustered and very difficult to identify in the population. At this point, the Adaptive Cluster Sampling, which is a specialized sampling for identification of hidden and clustered event and Bayesian Model, comes to the practice. Therefore, in this study, Adaptive Cluster Sampling which is capable of tracking hidden and clustered events and Bayesian Model are integrated in contact tracing, and the application on how this technique is used is included