Rainbow metamaterials for broadband multi-frequency vibration attenuation: Numerical analysis and experimental validation

In this study, we propose a ‘rainbow’ metamaterial to achieve broadband multi-frequency vibration attenuation. The rainbow metamaterial is constituted of a Π-shaped beam partitioned into substructures by parallel plates insertions with two attached cantilever-mass acting as local resonators. Both resonators inside each substructure can be non-symmetric such that the metamaterial can have multi-frequency bandgaps. Furthermore, these cantilever-mass resonators have a progressively variant design along the beam, namely rainbow-shaped, for the purpose of achieving broader energy stop bands. Π-shaped beams partitioned by parallel plate insertions can be extended to honeycomb sandwich composites, hence the proposed rainbow metamaterial can serve as a precursor for future honeycomb composites with superior vibration attenuation for more industrial applications. A mathematical model is first developed to estimate the frequency response functions of the metamaterial. Interaction forces between resonators and the backbone structure are calculated by solving the displacement of the cantilever-mass resonators. The plate insertions are modeled as attached masses with both their translational and rotational motion considered. Subsequently, the mathematical model is verified by comparison with experimental results. Metamaterials fabricated through an additive manufacturing technique are tested with a laser doppler receptance measuring system. After the validation of the mathematical model, a numerical study is conducted to explore the influences of the resonator spatial distributions on the frequency response functions of structures. Results show that for metamaterials with both symmetric and non-symmetric resonators, rainbow-shaped resonators can introduce inertial forces inside wider frequency range when compared to the periodic resonators of the same total mass, hence broader bandgaps. Meanwhile, the attenuation inside the bandgaps decreases when the bandgap become broader. Metamaterials with broadband multi-frequency range vibration attenuation can be achieved with non-symmetric sinusoidally varying resonators

Vandetanib Blocks the Cytokine Storm in SARS-CoV-2-Infected Mice

The portfolio of SARS-CoV-2 small molecule drugs is currently limited to a handful that are either approved (remdesivir), emergency approved (dexamethasone, baricitinib, paxlovid, and molnupiravir), or in advanced clinical trials. Vandetanib is a kinase inhibitor which targets the vascular endothelial growth factor receptor (VEGFR), the epidermal growth factor receptor (EGFR), as well as the RET-tyrosine kinase. In the current study, it was tested in different cell lines and showed promising results on inhibition versus the toxic effect on A549-hACE2 cells (IC500.79 μM) while also showing a reduction of >3 log TCID50/mL for HCoV-229E. The in vivo efficacy of vandetanib was assessed in a mouse model of SARS-CoV-2 infection and statistically significantly reduced the levels of IL-6, IL-10, and TNF-α and mitigated inflammatory cell infiltrates in the lungs of infected animals but did not reduce viral load. Vandetanib also decreased CCL2, CCL3, and CCL4 compared to the infected animals. Vandetanib additionally rescued the decreased IFN-1β caused by SARS-CoV-2 infection in mice to levels similar to that in uninfected animals. Our results indicate that the FDA-approved anticancer drug vandetanib is worthy of further assessment as a potential therapeutic candidate to block the COVID-19 cytokine storm

Wave propagation and response statistics of short fibre composites from experimental estimation of material properties

Typically there is variability in the material and geometrical properties of fibre-reinforced composites and this variability is often spatially correlated. Numerical models can predict the response of such panels, but the spatially correlated nature of the variability must be represented within the model. However, characterising the variability, and especially the spatial correlation, is problematic. In this study data is first generated by an automated optical process: light transmissibility measurements are taken of a dry chopped strand mat panel. The intensity of the consequent image is post-processed to describe the fibre density as a random field using the Karhunen-Loeve decomposition. The panel is then cut into beams, from which mobility measurements are taken, providing an ensemble of mobility and natural frequency information. The WKB (after Wentzel, Kramers and Brillouin) approximation, is used in order to find a suitable wave solutions for finite waveguides considering the given random field. Subsequent realisations of the random field are then used to predict the statistics of the vibration response of the beams. Numerical and experimental results show a very good agreement. This approach significantly reduces the computational time when compared to standard Finite Element calculations and provides a suitable framework to account for randomness in the properties. <br/

Robust optimised design of 3D printed elastic metastructures: A trade-off between complexity and vibration attenuation

In this work, a strategy for optimal design of mechanical metastructure is proposed taken into account uncertainties arising from additive manufacturing. A locally resonant Π-shaped beam with parallel plate-like insertions and two cantilever mass resonators at each unit cell is manufactured through a selective laser sintering process. The variability of the material properties introduced by the additive manufacturing procedure is experimentally obtained. Given that such manufacturing approaches are predominantly employed for producing complex metastructure architectures, it can significantly compromise the optimality of the design. A transfer matrix approach is employed to propagate variability at a structural level and predict the structural receptance due to a point harmonic force in the finite length metastructure. Then, the mass ratio of the metastructure is optimised for maximising vibration attenuation considering different numbers of added resonators and relative masses. A cost function is introduced in the classical robust design approach in order to favour designs with least complexity, represented by the number of added resonators. It is exhibited in several cases that the robustly optimal design is away from the deterministic optimal one, emphasising the relevance of the proposed approach in the optimisation of complex and locally resonant structures. Moreover, it is shown that the frequency range of interest plays a major role on the derived optimal design for each number of implemented resonators. The presented results show that even small variability in the Young's modulus of up to 3% and in the mass density of up to 1% can still affect the robustness of the optimal design for locally resonant metastructure as due to the consequent mistuning of the added resonators. © 2022 Elsevier Lt

Robust optimal sensor configuration using the value of information

Sensing is the cornerstone of any functional structural health monitoring technology, with sensor number and placement being a key aspect for reliable monitoring. We introduce for the first time a robust methodology for optimal sensor configuration based on the value of information that accounts for (1) uncertainties from updatable and nonupdatable parameters, (2) variability of the objective function with respect to nonupdatable parameters, and (3) the spatial correlation between sensors. The optimal sensor configuration is obtained by maximizing the expected value of information, which leads to a cost-benefit analysis that entails model parameter uncertainties. The proposed methodology is demonstrated on an application of structural health monitoring in plate-like structures using ultrasonic guided waves. We show that accounting for uncertainties is critical for an accurate diagnosis of damage. Furthermore, we provide critical assessment of the role of both the effect of modeling and measurement uncertainties and the optimization algorithm on the resulting sensor placement. The results on the health monitoring of an aluminum plate indicate the effectiveness and efficiency of the proposed methodology in discovering optimal sensor configurations. © 2022 The Authors. Structural Control and Health Monitoring published by John Wiley & Sons Ltd

Overcoming the Interobserver Variability in Lung Adenocarcinoma Subtyping.

The accurate identification of different lung adenocarcinoma histologic subtypes is important for determining prognosis but can be challenging because of overlaps in the diagnostic features, leading to considerable interobserver variability. To provide an overview of the diagnostic agreement for lung adenocarcinoma subtypes among pathologists and to create a ground truth using the clustering approach for downstream computational applications. Three sets of lung adenocarcinoma histologic images with different evaluation levels (small patches, areas with relatively uniform histology, and whole slide images) were reviewed by 18 international expert lung pathologists. Each image was classified into one or several lung adenocarcinoma subtypes. Among the 4702 patches of the first set, 1742 (37%) had an overall consensus among all pathologists. The overall Fleiss κ score for the agreement of all subtypes was 0.58. Using cluster analysis, pathologists were hierarchically grouped into 2 clusters, with κ scores of 0.588 and 0.563 in clusters 1 and 2, respectively. Similar results were obtained for the second and third sets, with fair-to-moderate agreements. Patches from the first 2 sets that obtained the consensus of the 18 pathologists were retrieved to form consensus patches and were regarded as the ground truth of lung adenocarcinoma subtypes. Our observations highlight discrepancies among experts when assessing lung adenocarcinoma subtypes. However, a subsequent number of consensus patches could be retrieved from each cluster, which can be used as ground truth for the downstream computational pathology applications, with minimal influence from interobserver variability