Many industries, such as nuclear power plants, chemical industry, oil and gas industry have dangerous working environments and hazardous conditions for employees. Maintenance, inspection and decommissioning activities in these safety-critical areas mean a serious risk, downtime is a significant financial loss. The Virtual Reality Training Platform is reflecting on this shortcoming, by providing the possibility for maintenance workers to be trained and prepared for unexpected scenarios, and to learn complex maintenance protocols without being exposed to unnecessary danger, like high temperature, radiation, etc. Employees can have training for equipment maintenance, dismantling of facilities at closed NPP Units. One of the most significant and unique added value of the immersive virtual reality solution is that the operator can experience lifelike emergencies (detonation, shutdown) under psychological pressure, while all of the physiology indicators can be monitored like eye-tracking. Users can work together anywhere in the world. A huge financial outage in industrial production is the preparation and maintenance downtime, which can be significantly reduced by the Virtual Training platform. This method can increase the accuracy, safety, reliability, and accountability of the maintenance and decommissioning procedures, while operational costs can be reduced as well.
A numerical investigation is performed addressing the optimal design of stiff structures accounting for uncertainty in loading amplitudes. A minimum volume problem is endowed with a stochastic compliance constraint handling normal distributions and solved adopting mathematical programming. The formulation, originally conceived for a single load case, is extended to handle multiple load cases. Numerical simulations are performed to test the proposed algorithms, pointing out features of the numerical procedures and peculiarities of the stochastic-based optimal solutions achieved for different values of the second order moments. Comparisons with respect to conventional deterministic layouts are provided, as well.
The aim of this study is to compare two available numerical tools for solving of partial differential equations for the optimal design of structures. In the past years numerous methods were developed for topology optimization, from these we have adopted the optimality criteria (OC) approach. The main idea is that we state the optimal conditions, that the minimizer has to fulfil at the end of an iterative proves. This method however is not a general one, only advantageous in the case of separable problems, but comes with fast speed, easy programming, and a relative insensitivity of computational time to the number of variables. In the paper we suggest a new method for the elimination of a numerical error, the so called ‘checkerboard pattern’. In the presented examples we applied one loading case and an elastic material behaviour. The cost function is the net weight of the structure and upper bound of the compliance is set as the optimality constraint.
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