• Smart Structures and Systems
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• v.4 no.2
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• pp.221-232
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• 2008

This paper represents the final results of a research program sponsored by the European Commission through project WIND-CHIME ($\underline{W}$ide Range Non-$\underline{IN}$trusive $\underline{D}$evices toward $\underline{C}$onservation of $\underline{HI}$storical Monuments in the $\underline{ME}$diterranean Area), in which the possibility of using advanced seismic protection technologies to preserve historical monuments in the Mediterranean area is investigated. In the current research, the dynamic characteristics of two outstanding Mamluk-Style minarets, which similar minarets were reported to experience extensive damage during Dahshur 1992 earthquake, are investigated. The first minaret is the Qusun minaret (1337 A.D, 736 Hijri Date (H.D)) located in El-Suyuti cemetery on the southern side of the Salah El-Din citadel. The minaret is currently separated from the surrounding building and is directly resting on the ground (no vaults underneath). The total height of the minaret is 40.28 meters with a base rectangular shaft of about 5.42 ${\times}$ 5.20 m. The second minaret is the southern minaret of Al-Sultaniya (1340 A.D, 739 H.D). It is located about 30.0 meters from Qusun minaret, and it is now standing alone but it seems that it used to be attached to a huge unidentified structure. The style of the minaret and its size attribute it to the first half of the fourteenth century. The minaret total height is 36.69 meters and has a 4.48 ${\times}$ 4.48 m rectangular base. Field investigations were conducted to obtain: (a) geometrical description of the minarets, (b) material properties of the minarets' stones, and (c) soil conditions at the minarets' location. Ambient vibration tests were performed to determine the modal parameters of the minarets such as natural frequencies and mode shapes. A $1/16^{th}$ scale model of Qusun minaret was constructed at Cairo University Concrete Research Laboratory and tested under free vibration with and without SMA wire dampers. The contribution of SMA wire dampers to the structural damping coefficient was evaluated under different vertical loads and vibration amplitudes. Experimental results were used along with the field investigation data to develop a realistic 3-D finite element model that can be used for seismic risk evaluation of the minarets. Examining the updated finite element models under different seismic excitations indicated the vulnerability of such structures to earthquakes with medium to high a/v ratio. The use of SMA wire dampers was found feasible for reducing the seismic risk for this type of structures.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.