Integrated control in monitoring historic buildings; the case of wall structures of Palazzo Ducale in Venice

This paper deals with in situ assessment of safety and state of preservation of historic buildings. This is a current issue since the need for reliability analysis of historic buildings is nowadays becoming more and more urgent. At the same time, monitoring techniques are continuously evolving. The research group CdSM of the University IUAV of Venice sets up an integrated procedure for non-destructive and microdestructive control aimed to locate possible weaknesses in the façades of Palazzo Ducale, in Venice. This is a delicate issue, because the building is very complex and deserves non-destructive diagnostics to be planned; moreover, a stone element has recently fallen from the south façade in a sudden and unexpected way. This paper illustrates the proposed methodologies for the integrated monitoring the wall structures of Palazzo Ducale, in particular those related to the assessment of the façades’ state of preservation and to integrated experimental and analytical procedures, and illustrates the expected outcomes

Validation of a zero-dimensional model for prediction of NOx and engine performance for electronically controlled marine two-stroke diesel engines

The aim of this paper is to derive a methodology suitable for energy system analysis for predicting the performance and NOx emissions of marine low speed diesel engines. The paper describes a zero-dimensional model, evaluating the engine performance by means of an energy balance and a two zone combustion model using ideal gas law equations over a complete crank cycle. The combustion process is divided into intervals, and the product composition and flame temperature are calculated in each interval. The NOx emissions are predicted using the extended Zeldovich mechanism. The model is validated using experimental data from two MAN B&W engines; one case being data subject to engine parameter changes corresponding to simulating an electronically controlled engine; the second case providing data covering almost all model input and output parameters. The first case of validation suggests that the model can predict specific fuel oil consumption and NOx emissions within the 95% confidence intervals given by the experimental measurements. The second validation confirms the capability of the model to match measured engine output parameters based on measured engine input parameters with a maximum 5% deviation