Postbuckling delamination of a stiffened composite panel using finite element methods

A combined numerical and experimental study is carried out for the postbuckling behavior of a stiffened composite panel. The panel is rectangular and is subjected to static in-plane compression on two opposite edges to the collapse level. Nonlinear (large deflection) plate theory is employed, together with an experimentally based failure criterion. It is found that the stiffened composite panel can exhibit significant postbuckling strength

Almost Classically Damped Linear Discrete Systems

The present work investigates dynamic response of a class of linear oscillators. The common characteristic of the systems analyzed is that they possess damping properties close to those resulting in classical normal modes. Regular perturbation expansions arc utilized for analyzing the eigenproblem as well as the vibration response Of such systems. The analysis is based on a proper splitting of the damping matrix. The advantage of this approach is that it sets the stage for application of standard modal analysis methodologies, reducing the main mathematical problem to that of finding the frequencies and mode shapes of the corresponding undamped model. The validity and effectiveness of the present analysis is illustrated and verified by a numerical example

Periodic steady state response of large scale mechanical models with local nonlinearities

AbstractLong term dynamics of a class of mechanical systems is investigated in a computationally efficient way. Due to geometric complexity, each structural component is first discretized by applying the finite element method. Frequently, this leads to models with a quite large number of degrees of freedom. In addition, the composite system may also possess nonlinear properties. The method applied overcomes these difficulties by imposing a multi-level substructuring procedure, based on the sparsity pattern of the stiffness matrix. This is necessary, since the number of the resulting equations of motion can be so high that the classical coordinate reduction methods become inefficient to apply. As a result, the original dimension of the complete system is substantially reduced. Subsequently, this allows the application of numerical methods which are efficient for predicting response of small scale systems. In particular, a systematic method is applied next, leading to direct determination of periodic steady state response of nonlinear models subjected to periodic excitation. An appropriate continuation scheme is also applied, leading to evaluation of complete branches of periodic solutions. In addition, the stability properties of the located motions are also determined. Finally, respresentative sets of numerical results are presented for an internal combustion car engine and a complete city bus model. Where possible, the accuracy and validity of the applied methodology is verified by comparison with results obtained for the original models. Moreover, emphasis is placed in comparing results obtained by employing the nonlinear or the corresponding linearized models

Finite element model updating of an experimental vehicle model using measured modal characteristics

Methods for modal identification and structural model updating are employed to develop high fidelity finite element models of an experimental vehicle model using acceleration measurements. The identification of modal characteristics of the vehicle is based on ac-celeration time histories obtained from impulse hammer tests. An available modal identification software is used to obtain the modal characteristics from the analysis of the various sets of vibration measurements. A high modal density modal model is obtained. The modal characteristics are then used to update an increasingly complex set of finite element models of the vehicle. A multi-objective structural identification method is used for estimating the parameters of the finite element structural models based on minimizing the modal residu-als. The method results in multiple Pareto optimal structural models that are consistent with the measured modal data and the modal residuals used to measure the discrepancies between the measured modal values and the modal values predicted by the model. Single objective structural identification methods are also evaluated as special cases of the proposed multi-objective identification method. The multi-objective framework and the corresponding compu-tational tools provide the whole spectrum of optimal models and can thus be viewed as a gen-eralization of the available conventional methods. The results indicate that there is wide variety of Pareto optimal structural models that trade off the fit in various measured quanti-ties. These Pareto optimal models are due to uncertainties arising from model and measure-ment errors. The size of the observed variations depends on the information contained in the measured data, as well as the size of model and measurement errors. The effectiveness of the updated models and the predictive capabilities of the Pareto vehicle models are assessed

Computational Advances in Drug Safety: Systematic and Mapping Review of Knowledge Engineering Based Approaches

Drug Safety (DS) is a domain with significant public health and social impact. Knowledge Engineering (KE) is the Computer Science discipline elaborating on methods and tools for developing “knowledge-intensive” systems, depending on a conceptual “knowledge” schema and some kind of “reasoning” process. The present systematic and mapping review aims to investigate KE-based approaches employed for DS and highlight the introduced added value as well as trends and possible gaps in the domain. Journal articles published between 2006 and 2017 were retrieved from PubMed/MEDLINE and Web of Science® (873 in total) and filtered based on a comprehensive set of inclusion/exclusion criteria. The 80 finally selected articles were reviewed on full-text, while the mapping process relied on a set of concrete criteria (concerning specific KE and DS core activities, special DS topics, employed data sources, reference ontologies/terminologies, and computational methods, etc.). The analysis results are publicly available as online interactive analytics graphs. The review clearly depicted increased use of KE approaches for DS. The collected data illustrate the use of KE for various DS aspects, such as Adverse Drug Event (ADE) information collection, detection, and assessment. Moreover, the quantified analysis of using KE for the respective DS core activities highlighted room for intensifying research on KE for ADE monitoring, prevention and reporting. Finally, the assessed use of the various data sources for DS special topics demonstrated extensive use of dominant data sources for DS surveillance, i.e., Spontaneous Reporting Systems, but also increasing interest in the use of emerging data sources, e.g., observational healthcare databases, biochemical/genetic databases, and social media. Various exemplar applications were identified with promising results, e.g., improvement in Adverse Drug Reaction (ADR) prediction, detection of drug interactions, and novel ADE profiles related with specific mechanisms of action, etc. Nevertheless, since the reviewed studies mostly concerned proof-of-concept implementations, more intense research is required to increase the maturity level that is necessary for KE approaches to reach routine DS practice. In conclusion, we argue that efficiently addressing DS data analytics and management challenges requires the introduction of high-throughput KE-based methods for effective knowledge discovery and management, resulting ultimately, in the establishment of a continuous learning DS system

Exploring the Capacity of Open, Linked Data Sources to Assess Adverse Drug Reaction Signals

Abstract. In this work, we explore the capacity of open, linked data sources to assess adverse drug reaction (ADR) signals. Our study is based on a set of drugrelated Bio2RDF data sources and three reference datasets, containing both positive and negative ADR signals, which were used for benchmarking. We present the overall approach for this assessment and refer to some early findings based on the analysis performed so far

Analysis of bilinear oscillators under harmonic loading using nonlinear output frequency response functions

In this paper, the new concept of Nonlinear Output Frequency Response Functions (NOFRFs) is extended to the harmonic input case, an input-independent relationship is found between the NOFRFs and the Generalized Frequency Response Functions (GFRFs). This relationship can greatly simplify the application of the NOFRFs. Then, beginning with the demonstration that a bilinear oscillator can be approximated using a polynomial type nonlinear oscillator, the NOFRFs are used to analyze the energy transfer phenomenon of bilinear oscillators in the frequency domain. The analysis provides insight into how new frequency generation can occur using bilinear oscillators and how the sub-resonances occur for the bilinear oscillators, and reveals that it is the resonant frequencies of the NOFRFs that dominate the occurrence of this well-known nonlinear behaviour. The results are of significance for the design and fault diagnosis of mechanical systems and structures which can be described by a bilinear oscillator model

What does it take to make integrated care work? A ‘cookbook’ for large-scale deployment of coordinated care and telehealth

The Advancing Care Coordination & Telehealth Deployment (ACT) Programme is the first to explore the organisational and structural processes needed to successfully implement care coordination and telehealth (CC&TH) services on a large scale. A number of insights and conclusions were identified by the ACT programme. These will prove useful and valuable in supporting the large-scale deployment of CC&TH. Targeted at populations of chronic patients and elderly people, these insights and conclusions are a useful benchmark for implementing and exchanging best practices across the EU. Examples are: Perceptions between managers, frontline staff and patients do not always match; Organisational structure does influence the views and experiences of patients: a dedicated contact person is considered both important and helpful; Successful patient adherence happens when staff are engaged; There is a willingness by patients to participate in healthcare programmes; Patients overestimate their level of knowledge and adherence behaviour; The responsibility for adherence must be shared between patients and health care providers; Awareness of the adherence concept is an important factor for adherence promotion; The ability to track the use of resources is a useful feature of a stratification strategy, however, current regional case finding tools are difficult to benchmark and evaluate; Data availability and homogeneity are the biggest challenges when evaluating the performance of the programmes

Rising phenomena and the multi-sliding bifurcation in a two-degree of freedom impact oscillator

We consider the rising phenomena which occur in sticking solutions of a two-degree of freedom impact oscillator. We describe a mathematical formulation for modelling such a systems during both free flight and during sticking solutions for each of the masses in the system. Simulations of the sticking solutions are carried out, and rising events are observed when the forcing frequency parameter is varied. We show how the time of sticking reduces significantly as a rising event occurs. Then within the sticking region we show how rising is qualitatively similar to the multi-sliding bifurcation for sliding orbits