CPU runtime optimization in data damage tracking quarantine and recovery (DTQR) scheme based on customized ANN

Database Management Systems (DBMS) are regularly used to store and process touchy endeavour information. In any case, it is beyond the realm of imagination to expect to verify the information by depending on the entrance control and security instruments of such frameworks alone; clients may handle their benefits or go around security systems to malevolently adjust and get to the information. Hence, we have developed a reliable, secure, and real-time data damage tracking Quarantine and recovery scheme using Customized ANN approach. The proposed DTQR scheme recovers the accurate data from any newer data and eliminates the fraudulent data. The approach also provides a solution for runtime problems occurring in the DBMS. Moreover, the proposed technique implemented in the working platform of JAVA and the results are analyzed with existing techniques to prove the efficiency of the proposed system.

Strain Mapping and Damage Tracking in Carbon Fiber Reinforced Epoxy Composites during Dynamic Bending Until Fracture with Quantum Resistive Sensors in Array

The sustained development of wind energies requires a dramatic rising of turbine blade size especially for their off-shore implantation, which requires as well composite materials with higher performances. In this context, the monitoring of the health of these structures appears essential to decrease maintenance costs, and produce a cheaper kwh. Thus, the input of quantum resistive sensors (QRS) arrays, to monitor the strain gradient in area of interest and anticipate damage in the core of composite structures, without compromising their mechanical properties, sounds promising. QRS are nanostructured strain and damage sensors, transducing strain at the nanoscale into a macroscopic resistive signal for a consumption of only some µW. QRS can be positioned on the surface or in the core of the composite material between plies, and this homogeneously as they are made of the same resin as the composite. The embedded QRS had a gauge factor of 3, which was found more than enough to follow the strain from 0.01% to 1.4% at the final failure. The spatial deployment of four QRS in array made possible for the first time the experimental visualization of a strain field comparable to the numerical simulation. QRS proved also to be able to memorize damage accumulation within the sample and thus could be used to attest the mechanical history of composites.

Reveal of Internal, Early-Load Interfacial Debonding on Cement Textile-Reinforced Sandwich Insulated Panels

Internal interfacial debonding (IID) phenomena on sandwich façade insulated panels are detected and tracked by acoustic emission (AE). The panels are made of a thin and lightweight cementitious composite skin. In the lab, the panels are tested under incremental bending simulating service loads (i.e., wind). Local (up to 150 mm wide) skin-core detachments are reported in the early loading stage (at 5% of ultimate load) and are extensively investigated in this study, since IID can detrimentally affect the long-term durability of the structural element. A sudden rise in the AE hits rate and a shift in the wave features (i.e., absolute energy, amplitude, rise time) trends indicate the debonding onset. AE source localization, validated by digital image correlation (DIC) principal strains and out-of-plane full-field displacement mapping, proves that early debonding occurs instantly and leads to the onset of cracks in the cementitious skin. At higher load levels, cracking is accompanied by local debonding phenomena, as proven by RA value increases and average frequency drops, a result that extends the state-of-the-art in the fracture assessment of concrete structures (Rilem Technical Committee 212-ACD). Point (LVDT) and full-field (AE/DIC) measurements highlight the need for a continuous and full-field monitoring methodology in order to pinpoint the debonded zones, with the DIC technique accurately reporting surface phenomena while AE offers in-volume damage tracking.

Data Compression Approach for Long-Term Monitoring of Pavement Structures

Pavement structures are designed to withstand continuous damage during their design life. Damage starts as soon as the pavement is open to traffic and increases with time. If maintenance activities are not considered in the initial design or considered but not applied during the service life, damage will grow to a point where rehabilitation may be the only and most expensive option left. In order to monitor the evolution of damage and its severity in pavement structures, a novel data compression approach based on cumulative measurements from a piezoelectric sensor is presented in this paper. Specifically, the piezoelectric sensor uses a thin film of polyvinylidene fluoride to sense the energy produced by the micro deformation generated due to the application of traffic loads. Epoxy solution has been used to encapsulate the membrane providing hardness and flexibility to withstand the high-loads and the high-temperatures during construction of the asphalt layer. The piezoelectric sensors have been exposed to three months of loading (approximately 1.0 million loads of 65 kN) at the French Institute of Science and Technology for Transport, Development and Networks (IFSTTAR) fatigue carrousel. Notably, the sensors survived the construction and testing. Reference measurements were made with a commercial conventional strain gauge specifically designed for measurements in hot mix asphalt layers. Results from the carrousel successfully demonstrate that the novel approach can be considered as a good indicator of damage progression, thus alleviating the need to measure strains in pavement for the purpose of damage tracking.