Wavelet Transform-Based Damage Identification in Bladed Disks and Rotating Blades

Blade vibration and blade clearance are effective diagnostic features for the identification of blade damage in rotating machines. Blade tip-timing (BTT) is a noncontact method that is often used to monitor the vibration and clearance of blades in a rotating machinery. Standard signal processing of BTT measurements give one blade response sample per revolution of the machine which is often insufficient for the diagnosis of damage. This paper uses the raw data signals from the sensors directly and employs a wavelet energy-based mistuning index (WEBMI) to predict the presence and locations of damage in rotating blades. The Lipschitz exponent is derived from the wavelet packet coefficients and used to estimate the severity of the damage. In this study, experiments were conducted to obtain BTT measurements on rotating blades at  rpm using three different sensors: an active eddy current sensor, a passive eddy current sensor, and an optical sensor. In addition, hammer excitation experiments were conducted for various added mass (damage) cases to compute the damage severity for a bladed disk. To simulate the damage experimentally in the bladed disk and rotating blades, masses were added to the blades to alter their dynamics and mimic the damage. The results indicate that the WEBMI can detect the presence and location of damage in rotating blades using measurements from common BTT sensors. To check the robustness of the proposed damage severity index, the experimental results were compared with numerical simulation for the bladed disk and showed good agreement

An equivalent model of a nonlinear bolted flange joint

The dynamic response of individual components in an assembled structure shows high accuracy compared to experimental measurements of the system response. However, when it comes to assemblies, the conventional linear approaches fail to deliver good accuracy, due to the uncertain linear and nonlinear mechanisms in the contact interface of the joints. Therefore, the inherent dynamics of the contact interfaces needs to be considered in modeling assembled structures. In this paper the prediction of the nonlinear dynamic response in a bolted flange joint was obtained in two ways. First, a 3D detailed finite element model capable of representing the micro-slip mechanism was made using a quasi-static time stepping analysis. The linear characteristics and nonlinear mechanisms developing in the contact interface of a bolted joint are investigated by using the 3D detailed model. Moreover, the natural frequencies of the assembled structure (representing the linear response) and the micro-slip behavior in terms of hysteresis loops (representing the nonlinear response) are obtained using the detailed model. Second, an equivalent model composed of beam elements and an appropriate joint model is then constructed for the assembled structure. An identification approach is proposed, and the parameters of the joint model are identified using both linear and nonlinear characteristics, i.e. natural frequencies and hysteresis loops. Comparing the hysteresis loops obtained from the detailed and equivalent models verifies the accuracy of the joint model used to represent the contact interface and the identification approach proposed for parameter quantification

Development of a digital twin operational platform using Python Flask

The digital twin concept has developed as a method for extracting value from data, and is being developed as a new technique for the design and asset management of high-value engineering systems such as aircraft, energy generating plant, and wind turbines. In terms of implementation, many proprietary digital twin software solutions have been marketed in this domain. In contrast, this paper describes a recently released open-source software framework for digital twins, which provides a browser-based operational platform using Python and Flask. The new platform is intended to maximize connectivity between users and data obtained from the physical twin. This paper describes how this type of digital twin operational platform (DTOP) can be used to connect the physical twin and other Internet-of-Things devices to both users and cloud computing services. The current release of the software—DTOP-Cristallo—uses the example of a three-storey structure as the engineering asset to be managed. Within DTOP-Cristallo, specific engineering software tools have been developed for use in the digital twin, and these are used to demonstrate the concept. At this stage, the framework presented is a prototype. However, the potential for open-source digital twin software using network connectivity is a very large area for future research and development

On variants and vaccines: The effectiveness of Covid-19 monoclonal antibody therapy during two distinct periods in the pandemic

BACKGROUND: While Covid-19 monoclonal antibody therapies (Mab) have been available in the outpatient setting for over a year and a half, little is known about the impact of emerging variants and vaccinations on the effectiveness of Mab therapies. We sought to determine the effectiveness of Covid-19 Mab therapies during the first two waves of the pandemic in Los Angeles County and assess the impact of vaccines, variants, and other confounding factors. METHODS AND FINDINGS: We retrospectively examined records for 2209 patients of with confirmed positive molecular SARS-CoV2 test either referred for outpatient Mab therapy or receiving Mab treatment in the emergency department (ED) between December 2020 and 2021. Our primary outcome was the combined 30-day incidence of ED visit, hospitalization, or death following the date of referral. Additionally, SARS-CoV2 isolates of hospitalized patients receiving Mabs were sequenced. The primary outcome was significantly reduced with combination therapy compared to bamlanivimab or no treatment (aHR 0·60; 95% CI ·37, ·99), with greater benefit in unvaccinated, moderate-to-high-risk patients (aHR ·39; 95% CI ·20, ·77). Significant associations with the primary outcome included history of lung disease (HR 7·13; 95% CI 5·12, 9·95), immunocompromised state (HR 6·59; 95% CI 2·91–14·94), and high social vulnerability (HR 2·29, 95% CI 1·56–3·36). Two predominant variants were noted during the period of observation: the Epsilon variant and the Delta variant. CONCLUSIONS: Only select monoclonal antibody therapies significantly reduced ED visits, hospitalizations, and death due to COVID-19 during. Vaccination diminished effectiveness of Mabs. Variant data and vaccination status should be considered when assessing the benefit of novel COVID-19 treatments