Probabilistic micromechanical spatial variability quantification in laminated composites

SN and SS are grateful for the support provided through the Lloyd’s Register Foundation Centre. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.Peer reviewedPostprin

Stochastic natural frequency analysis of damaged thin-walled laminated composite beams with uncertainty in micromechanical properties

This paper presents a stochastic approach to study the natural frequencies of thin-walled laminated composite beams with spatially varying matrix cracking damage in a multi-scale framework. A novel concept of stochastic representative volume element (SRVE) is introduced for this purpose. An efficient radial basis function (RBF) based uncertainty quantification algorithm is developed to quantify the probabilistic variability in free vibration responses of the structure due to spatially random stochasticity in the micro-mechanical and geometric properties. The convergence of the proposed algorithm for stochastic natural frequency analysis of damaged thin-walled composite beam is verified and validated with original finite element method (FEM) along with traditional Monte Carlo simulation (MCS). Sensitivity analysis is carried out to ascertain the relative influence of different stochastic input parameters on the natural frequencies. Subsequently the influence of noise is investigated on radial basis function based uncertainty quantification algorithm to account for the inevitable variability for practical field applications. The study reveals that stochasticity/ system irregularity in structural and material attributes affects the system performance significantly. To ensure robustness, safety and sustainability of the structure, it is very crucial to consider such forms of uncertainties during the analysis

Kriging models for aero-elastic simulations and reliability analysis of offshore wind turbine support structures

This PhD research is funded by Lloyd’s Register Group Services Ltd., Aberdeen. Sriramula’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research.Peer reviewedPostprin

Reliability-centered maintenance and cost optimization for offshore oil and gas components

Funding Information: This research project has been funded and supported by Innovate UK and Optimal as part Knowledge Transfer Partnerships Scheme.Peer reviewedPublisher PD

Ultimate loads and response analysis of a monopile supported offshore wind turbine using fully coupled simulation

This PhD research is funded by Lloyd’s Register Group Services Ltd., Aberdeen. Sriramula’s work within the Lloyd’s Register Foundation Centre for Safety and Reliability Engineering at the University of Aberdeen is supported by Lloyd’s Register Foundation. The Foundation helps to protect life and property by supporting engineering-related education, public engagement and the application of research. We would also like to acknowledge the constant assistance provided by Jason Jonkman on using FAST.Peer reviewedPostprin

Multi-scale reliability-based design optimisation framework for fibre-reinforced composite laminates

Purpose The purpose of this study is to enable performing reliability-based design optimisation (RBDO) for a composite component while accounting for several multi-scale uncertainties using a large representative volume element (LRVE). This is achieved using an efficient finite element analysis (FEA)-based multi-scale reliability framework and sequential optimisation strategy. Design/methodology/approach An efficient FEA-based multi-scale reliability framework used in this study is extended and combined with a proposed sequential optimisation strategy to produce an efficient, flexible and accurate RBDO framework for fibre-reinforced composite laminate components. The proposed RBDO strategy is demonstrated by finding the optimum design solution for a composite component under the effect of multi-scale uncertainties while meeting a specific stiffness reliability requirement. Performing this using the double-loop approach is computationally expensive because of the number of uncertainties and function evaluations required to assess the reliability. Thus, a sequential optimisation concept is proposed, which starts by finding a deterministic optimum solution, then assesses the reliability and shifts the constraint limit to a safer region. This is repeated until the desired level of reliability is reached. This is followed by a final probabilistic optimisation to reduce the mass further and meet the desired level of stiffness reliability. In addition, the proposed framework uses several surrogate models to replace expensive FE function evaluations during optimisation and reliability analysis. The numerical example is also used to investigate the effect of using different sizes of LRVEs, compared with a single RVE. In future work, other problem-dependent surrogates such as Kriging will be used to allow predicting lower probability of failures with high accuracy. Findings The integration of the developed multi-scale reliability framework with the sequential RBDO optimisation strategy is proven computationally feasible, and it is shown that the use of LRVEs leads to less conservative designs compared with the use of single RVE, i.e. up to 3.5% weight reduction in the case of the 1 × 1 RVE optimised component. This is because the LRVE provides a representation of the spatial variability of uncertainties in a composite material while capturing a wider range of uncertainties at each iteration. Originality/value Fibre-reinforced composite laminate components designed using reliability and optimisation have been investigated before. Still, they have not previously been combined in a comprehensive multi-scale RBDO. Therefore, this study combines the probabilistic framework with an optimisation strategy to perform multi-scale RBDO and demonstrates its feasibility and efficiency for an fibre reinforced polymer component designUniversity of Aberdeen Elphinstone scholarship scheme

Increased circulating ANG II and TNF-α represents important risk factors in obese Saudi adults with hypertension irrespective of diabetic status and BMI

Central adiposity is a significant determinant of obesity-related hypertension risk, which may arise due to the pathogenic inflammatory nature of the abdominal fat depot. However, the influence of pro-inflammatory adipokines on blood pressure in the obese hypertensive phenotype has not been well established in Saudi subjects. As such, our study investigated whether inflammatory factors may represent useful biomarkers to delineate hypertension risk in a Saudi cohort with and without hypertension and/or diabetes mellitus type 2 (DMT2). Subjects were subdivided into four groups: healthy lean controls (age: 47.9±5.1 yr; BMI: 22.9±2.1 Kg/m2), non-hypertensive obese (age: 46.1±5.0 yr; BMI: 33.7±4.2 Kg/m2), hypertensive obese (age: 48.6±6.1 yr; BMI: 36.5±7.7 Kg/m2) and hypertensive obese with DMT2 (age: 50.8±6.0 yr; BMI: 35.3±6.7 Kg/m2). Anthropometric data were collected from all subjects and fasting blood samples were utilized for biochemical analysis. Serum angiotensin II (ANG II) levels were elevated in hypertensive obese (p<0.05) and hypertensive obese with DMT2 (p<0.001) compared with normotensive controls. Systolic blood pressure was positively associated with BMI (p<0.001), glucose (p<0.001), insulin (p<0.05), HOMA-IR (p<0.001), leptin (p<0.01), TNF-α (p<0.001) and ANG II (p<0.05). Associations between ANG II and TNF-α with systolic blood pressure remained significant after controlling for BMI. Additionally CRP (p<0.05), leptin (p<0.001) and leptin/adiponectin ratio (p<0.001) were also significantly associated with the hypertension phenotype. In conclusion our data suggests that circulating pro-inflammatory adipokines, particularly ANG II and, TNF-α, represent important factors associated with a hypertension phenotype and may directly contribute to predicting and exacerbating hypertension risk

ACE2 Deficiency Enhances Angiotensin II-Mediated Aortic Profilin-1 Expression, Inflammation and Peroxynitrite Production

Inflammation and oxidative stress play a crucial role in angiotensin (Ang) II-mediated vascular injury. Angiotensin-converting enzyme 2 (ACE2) has recently been identified as a specific Ang II-degrading enzyme but its role in vascular biology remains elusive. We hypothesized that loss of ACE2 would facilitate Ang II-mediated vascular inflammation and peroxynitrite production. 10-week wildtype (WT, Ace2+/y) and ACE2 knockout (ACE2KO, Ace2−/y) mice received with mini-osmotic pumps with Ang II (1.5 mg.kg−1.d−1) or saline for 2 weeks. Aortic ACE2 protein was obviously reduced in WT mice in response to Ang II related to increases in profilin-1 protein and plasma levels of Ang II and Ang-(1–7). Loss of ACE2 resulted in greater increases in Ang II-induced mRNA expressions of inflammatory cytokines monocyte chemoattractant protein-1 (MCP-1), interleukin (IL)-1β, and IL-6 without affecting tumor necrosis factor-α in aortas of ACE2KO mice. Furthermore, ACE2 deficiency led to greater increases in Ang II-mediated profilin-1 expression, NADPH oxidase activity, and superoxide and peroxynitrite production in the aortas of ACE2KO mice associated with enhanced phosphorylated levels of Akt, p70S6 kinase, extracellular signal-regulated kinases (ERK1/2) and endothelial nitric oxide synthase (eNOS). Interestingly, daily treatment with AT1 receptor blocker irbesartan (50 mg/kg) significantly prevented Ang II-mediated aortic profilin-1 expression, inflammation, and peroxynitrite production in WT mice with enhanced ACE2 levels and the suppression of the Akt-ERK-eNOS signaling pathways. Our findings reveal that ACE2 deficiency worsens Ang II-mediated aortic inflammation and peroxynitrite production associated with the augmentation of profilin-1 expression and the activation of the Akt-ERK-eNOS signaling, suggesting potential therapeutic approaches by enhancing ACE2 action for patients with vascular diseases

On quantifying the effect of noise in radial basis function based stochastic free vibration analysis of laminated composite beam

This paper presents the effect of noise on Radial basis function (RBF) based stochastic natural frequency analysis of thin-walled laminated composite beams. The RBF based method is built up on the basis of information acquired regarding the behaviour of the response quantity throughout the entire design space utilizing few algorithmically chosen design points The crucial issue of expensive computation involved in uncertainty quantification of composite structures and the development of radial basis function based uncertainty quantification algorithm to mitigate this lacuna. On the other hand, noise is an inevitable factor in every real life design methods and structural response monitoring for any practical systems. In this paper, a novel algorithm is developed to explore the effect of noise in surrogate based uncertainty quantification methods. The probability distributions for higher modes of natural frequencies (first eight) corresponding to the bending modes has been calculated. The study reveals that stochasticity/ system irregularity in structural and material attributes influences the system performance remarkably. To ensure robustness, safety and sustainability of the structure, it is very crucial to consider such forms of uncertainties during the analysis. The proposed method for quantifying the effect of noise for the proposed computationally efficient RBF based framework in this paper is general in nature and therefore, it can be further extended to explore other surrogate based approach of uncertainty quantification under the influence of noise