In aerospace applications, Commercial-Off-The-Shelf (COTS) Field programmable Gate Array (FPGA) is becoming increasingly attractive by offering low-cost solutions, simplicity and flexibility.
This research faces the problem of disturbance induced by high energy particles on electronic devices. Based on detailed analysis of this phenomenon, the work is divided into two parts: in the first part evaluation of effects of the Single Event Upset (SEU) has been carried out with the aim of determining diagnostic techniques and the mitigation of this disturbance, taking into account the fact that testing is one of the fundamental points in electronic programmable devices; in the second part a fault tolerant technique has been devised so as to achieve the requirements demanded on a real avionic system. For this purpose, a model of calculation to establish whether the system respond to specific requirements has been developed.

This paper present and discuss a method that, starting from the information of a public weather station and a reference panel, gives usefu1 information about the efficiency of a photovoltaic plant. The aim of this paper is to give a method to analyse the effects of the dust on the panel surface comparing, for a given solar radiation level, the energy production of a reference panel estimated in clean condition with the energy produced by the panel in actual condition. The novelty of the method is based on the simplification of the monitoring system devoted to the energy evaluation considering in a suitable way the information collected by public weather stations.

Oil & Gas environment, during the last ten years, has experienced the need to improve product performance covering aspects going from its increased functionality, maintenance, reliability and safety, towards reduced time delivery and cost. Some of them have been required by customer and some of them are indeed essential to meet even more stringing international regulations, imposing high standard of product quality. Nowadays the product process improvement has scored by implementing lesson learnt, rose during the manufacturing phase or by means of feedback coming from field. It’s easy to understand that, this way of product improvement affects, consistently and negatively, cost, time and, above all, customer satisfaction. The emphasis on products performances development has encouraged designer to look at strategic management, engineering, marketing, and other disciplines to study the new design process focused, not only on reaching a good compromise among the afore mentioned aspects, but the optimum. Deep Analysis on this obsolete product improvement process, has carried out the necessity to move the validation and verification phase product directly during the design phase, looking at it as, not only an isolate design phase, but inserted in a design cycle where solutions on product functionality and its reliability are continuously validated and verified. This new way to conceive design, directly on the early stage of a project, leads towards the optimum compromise between: functionality, maintenance, reliability, safety, and reduced time delivery, cost reduction, and reduce cycle time to better incorporate customer and supplier requirements in the product and process design. Computer aided design, modelling and simulation of product, involving different design disciplines, (system, instrumentation, control and reliability) in the same environment, becomes an imperative to target this goal.

The paper offers a comprehensive study performed in order to design a fault management system, intended to be applied to monitor a Wireless Active Guardrail System (WAGS). An architectural overview of the WAGS sensing capabilities and a list of its possible faults are reported. Two stages of fault detection: (i) sensing node built-in fault detection, and (ii) server side built-in fault diagnostic, are argued and proposed for the future implementation.

The paper presents a study, via Monte Carlo simulations, of the effect of truncation in sequential sampling plans. In sequential sampling plans, truncation is needed to avoid an excessive sample size, which can occur in same cases: on the other hand, truncation affects both the Operating Characteristic (OC) and the Average Sample Number (ASN). In the paper, the approximate analytical formulas used in the literature to determine OC and ASN are compared with the actual curves obtained via Monte Carlo simulations, taking into consideration three different truncation thresholds. Besides, a fourth truncation threshold is empirically determined: it yields approximately the best correspondence between theoretical and Monte Carlo OC and ASN.