Strukturoptimierung für Bruchwiderstand von Heterogenen Materialien

In the realm of structural optimization, a key objective is the maximization of the service life of structures, while avoiding premature failure due to unexpected, brittle fracture. Cracks, which can arise from manufacturing defects or stress concentrations, may propagate through the structure due to fatigue or corrosion. The incorporation of tailored heterogeneous materials can enhance macroscopic fracture toughness by virtue of the interaction between cracks and the heterogeneities. While optimization methods for structural compliance, which consider predefined stationary cracks with volume and/or stress constraints, are well-established, methods that account for propagating cracks are still in an early stage of development. In this work, we propose three optimization frameworks incorporating crack propagation in heterogeneous materials under mode-I loading in a two-dimensional setting, where the shape/material parameters of the embedded elliptical heterogeneities are optimized. The first is an adjoint sensitivity-based optimization framework that enhances interfacial fracture resistance quantified by external mechanical work with respect to orientations of the orthotropic material, considering a small number of potential crack paths. This method is designed to optimize for the worst-case scenario among the defined crack paths. In the second, we propose a novel derivative-free approach for use in a stochastic optimization setting to produce robust designs with respect to shape parameters under noise. Here, an approximate gradient based on Monte Carlo estimation and nearest-neighbor interpolation of the available data is used to take the next optimization step. The third framework employs a Bayesian optimization strategy with Gaussian processes to optimize resistance to bulk fracture, modeled using the phase-field method. An interior-point monolithic solver is used, along with adaptive mesh refinement near the crack tip and subsequent coarsening along the tail of the crack to reduce the computational burden of the fracture simulation. The goal is to maximize the peak J-integral value under surfing boundary conditions, while also considering the high sensitivity of the initial crack's location relative to the periodic microstructure. The presented optimization experiments demonstrate significant improvements in the fracture resistance with justifiable computational cost

On optimization of heterogeneous materials for enhanced resistance to bulk fracture

We propose a novel approach to optimize the design of heterogeneous materials, with the goal of enhancing their effective fracture toughness under mode-I loading. The method employs a Gaussian processes-based Bayesian optimization framework to determine the optimal shapes and locations of stiff elliptical inclusions within a periodic microstructure in two dimensions. To model crack propagation, the phase-field fracture method with an efficient interior-point monolithic solver and adaptive mesh refinement, is used. To account for the high sensitivity of fracture properties to initial crack location with respect to heterogeneities, we consider multiple cases of initial crack and optimize the material for the worst-case scenario. We also impose a minimum clearance constraint between the inclusions to ensure design feasibility. Numerical experiments demonstrate that the method significantly improves the fracture toughness of the material compared to the homogeneous case

The Stress of COVID-19: Playing Havoc with the Hormones-A Review

Severe acute respiratory syndrome coronavirus- 2 (SARS-CoV-2) has affected millions of people across the world engendering an unprecedented pandemic. Coronavirus disease (COVID)-19 can present asymptomatic or in the form of the acute respiratory syndrome, viral pneumonia,or sepsis. Due to the novelty of the disease, the endocrine manifestations are not fully understood. It becomes indispensable to address the underlying endocrine disruptions contributing to the severe form of illness and thereby increasing the mortality.We discuss here the SARS-CoV-2 virus and endocrine reverberations based on the research with structurally similar SARS-COV-1. SARS-CoV-2 enters the body via its attachment to the angiotensin-converting enzyme 2 (ACE2) receptors. Apart from lungs,ACE2 expression on various organs can lead to endocrine perturbations.In COVID-19 infection, pre-existing endocrine disorders warrant cautious management and may require replacement therapy. COVID-19 and its repercussions on hormones are discussed extensively in this review

Robust design optimization for enhancing delamination resistance of composites

Abstract Recent developments in the field of computational modeling of fracture have opened up possibilities for designing structures against failure. A special case, called interfacial fracture or delamination, can occur in loaded composite structures where two or more materials are bonded together at comparatively weak interfaces. Due to the potential crack growth along these interfaces, the structural problem suffers from snap‐back/snap‐through instabilities and bifurcations with respect to the model parameters, leading to noisy and discontinuous responses. For such a case, the design optimization problem for a selected quantity of interest is ill‐posed, since small variations in the design parameters can lead to large jumps in the structural response. To this end, this article presents a stochastic optimization approach to maximize delamination resistance that is less sensitive to small perturbations of the design and thereby leads to a robust solution. To overcome the intractability of Monte Carlo methods for estimating the expected value of the expensive‐to‐evaluate response function, a global, piecewise‐constant surrogate is constructed based on nearest‐neighbor interpolation that is iteratively refined during the optimization run. We found that by taking a large stochastic region at the beginning of the optimization and gradually reducing it to the desired one can help overcome poor local optima. Our results demonstrate the effectiveness of the proposed framework using an example of shape optimization of hard inclusions embedded in a double‐cantilever beam, which significantly enhances delamination resistance

Amalgamation of management information system into anaesthesiology practice: A boon for the modern anaesthesiologists

Over the years, traditional anaesthesia record keeping system has been the backbone of anaesthesiology ever since its introduction in the 1890s by Dr. Harvey Cushing and Dr. Ernest A. Codman. Besides providing the important information regarding patients′ vital physiologic parameters, paper records had been a reliable source for various clinical research activities. The introduction of electronic monitoring gadgets and electronic record keeping systems has revolutionised the anaesthesiology practice to a large extent. Recently, the introduction of anaesthesia information management system (AIMS), which incorporates all the features of monitoring gadgets, such as electronic storage of large accurate data, quality assurance in anaesthesia, enhancing patient safety, ensuring legal protection, improved billing services and effecting an organisational change, is almost a revolution in modern-day anaesthesiology practice. The clinical research activities that are responsible for taking anaesthesiology discipline to higher peaks have also been boosted by the amalgamation of AIMS, enabling multicenter studies and sharing of clinical data. Barring few concerns in its installation, cost factors and functional aspects, the future of AIMS seems to be bright and will definitely prove to be a boon for modern-day anaesthesiology practice

Analysis of the Critical Flows of One-Component Fluids in Tubes

Two-phase critical discharge phenomena have been under investigation for some time now. Most models developed so far have necessitated a knowledge of the critical pressure to predict the critical flow rate. This type of analysis has limited application, as in most cases, only the stagnation conditions are fixed and it is the critical exit pressure that adjusts itself to the stagnation conditions. Thus to be most useful, a model is required to predict both the critical pressure and the critical mass flux from the stagnation conditions only. A model has been developed that is useful in predicting the, adiabatic one-component, two-phase, critical flow of fluids in circular tubes of length to diameter ratios greater than 8. This model which emphasized the flow pattern that is occurring, allows predictions to be made using the stagnation temperature and pressure and L/D only. For a particular stagnation enthalpy the critical mass flux was found to be a function of the conditions at the exit only. The procedure begins by using a trial exit pressure and the actual stagnation enthalpy to find a critical mass flux. Using this critical mass flux, the stagnation pressure is found by integrating upstream from the exit conditions..