Modelling and computation of acrylic bone cement injection and curing within the framework of vertebroplasty

This contribution deals with the simulation based investigation of processes related to the surgical treatment of vertebroplasty. In this regard, a simulation framework has been developed, which includes the generation of microstructural computer models of cancellous bone structures, the simulation of bone cement injection by computational fluid dynamics (CFD) methods and finite element (FE) simulations of bone cement curing processes. The modelling and computation strategy is illustrated and different material modelling approaches for the representation of acrylic bone cements as a non-linear fluid and a non-linear viscoelastic solid with curing dependent properties are outlined. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Experiments,modelling and simulation of adhesive curing processes in bonded three dimensional curved piezo metal composite structures

This contribution deals with the modelling and simulation of curing phenomena in adhesively bonded piezo metal composites which consists of a piezoelectric module enclosed by an adhesive layer which in turn is surrounded by two metal sheets. A short survey on the neccessary experimental investigations to characterise the adhesive's material behaviour is given and important aspects on the corresponding phenomenological modelling approach are presented. Both steps take into account the curing reaction, changes of volume, like chemical shrinkage, and inelastic mechanical behaviour which is temperature and curing dependent. Finally, the simulation strategy for the modelling within a finite element environment is depicted. By this, residual stresses, secondary deformations and loads on the piezo modules can be predicted, which is exemplified by a comparative study verifying a novel manufacturing strategy. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A general modelling framework and specific mechanical approaches to simulate curing phenomena in polymers

Polymers are employed as adhesives, filling or sealing materials, among others. Within these applications, a chemical reaction (e.g. polymerization) leads the materials to cure from a liquid to a solid. In this contribution, first a general continuum mechanical modelling framework for the simulation of curing phenomena is highlighted. It takes into account the main chemical, thermal and mechanical phenomena of polymeric curing processes. Secondly, different mechanical models to capture the mechanical behaviour of polymeric curing processes are regarded. It is shown that elastic, viscoelastic and viscoplastic models at large deformations can be employed. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Modelling and Simulation of Curing Processes of Epoxy Resin

During the curing reaction, the adhesive changes its thermomechanical material behaviour from a viscous fluid to a viscoelastic solid. This phase transition is an exothermal chemical reaction which is accompanied by thermal expansion, chemical shrinkage and changes in temperature. In this work the numerical simulation of the curing process will be presented. The material model for the implementation is presented in [1]. For the implementation of the material model the consistent tangent operator has been derived. In the presentation, experimental data and simulation are shown. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Extension of the Arruda-Boyce model to the modelling of the curing process of polymers

A phenomenologically motivated finite strain general framework to simulate the curing of polymer have been developed and discussed in our recently published papers [2,4]. The Arruda-Boyce model is a classical hyperelastic model for polymeric materials. This contribution presents an extension of the Arruda-Boyce model towards modelling the curing process of polymers following our previous framework. In this paper, we will show how to model the elastic behaviour and shrinkage effects of the polymer curing process in the isothermal case using the Arruda-Boyce model. Several numerical examples have been demonstrated to verify our newly proposed modified approach in case of curing process. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Carbon Fibre Prepregs: Simulation of a Thermo-Mechanical-Chemical Coupled Problem

In automotive industry research is done to replace high strength steel by combinations of steel and carbon-fibre prepregs (pre-impregnated fibres). It is planned to form both steel and uncured prepregs in one step followed by the curing process under pressure in the forming die. The ability to simulate the mechanical behaviour during forming and curing would allow more economical processes. The simulation of prepregs must regard highly anisotropic, viscoelastic and thermal- chemical properties. For this the model is split into an anisotropic elastic part, which represents the fibre fraction and an isotropic, viscoelastic part, representing the matrix. This part also contains curing, causing a dependency on time and temperature. During deep-drawing large deformations are occurring, so a large strain model regarding anisotropy, viscoelasticity and curing has been developed. Also experiments were made to validate this model. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

A one-dimensional approach to the chemical and thermo-mechanical coupled modeling of curing adhesives including plasticity

The modeling and simulation of curing adhesives is of great importance for industrial applications, mainly for the automotive industry. The one-dimensional model proposed here combines known viscoelastic models for curing material with effects of plasticity. To describe these plasticity effects, a yield stress with isotropic hardening is formulated as an equation of temperature and degree of cure. The proposed model therefore includes viscoelastic properties, thermo-chemical shrinkage and the aforementioned plasticity characteristics, all as functions of temperature and degree of cure. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Facilitated modelling with discrete-event simulation: Reality or myth?

Is it possible for discrete-event simulation to be used in a facilitated workshop environment? Over the last decade there have been various attempts to use simulation in this way, but we argue here that none have been successful in achieving a fully facilitated mode where the model is both developed and used in the workshop. We attempt to use a discrete-event simulation in a facilitated mode as part of a lean improvement workshop in a hospital setting. The model was successfully developed and used within the 3 day period of the workshop. Although the intervention was successful, we still had to build the model in the ‘back-office’, meaning that a fully facilitated mode was not achieved. The paper concludes by discussing how fully facilitated modelling with discrete-event simulation might be made possible; the answer is more about changing mind-sets than about technological challenge.     

Nonuniform isothermal curing of cylindrical products made of polymeric composites

Conclusion By increasing the curing temperature and reducing the winding rate, it is possible to obtain compressive radial stresses in a cylindrical product during the entire curing stage — which should prevent loss of integrity during the curing operation. When the duration of the curing process is limited, the magnitude of the compressive stresses will depend in an extreme manner on curing temperature. Meanwhile, in the general case, ensuring minimal residual stresses will not ensure the absence of tensile radial stresses during curing.Translated from Mekhanika Kompozitnykh Materialov, No. 5, pp. 873–877, September–October, 1988.     

Improved OR education through the use of spreadsheet models

The first and major part of this presentation shows how OR education may be improved through the use of spreadsheets, with several examples:

• •in decision theory, where the drawing capabilities of Excel are used to represent decision trees and where window switching and macros allow the educator to animate his presentation;
• •in linear programming, where the solver is used (remarks are made relating to the adequacy of the solver's solutions), and where the spreadsheet's graphing capabilities are used both to represent the feasible set and the objective function, and to interactively animate the objective function or constraint movements;
• •in dynamic programming, deterministic or stochastic, where it is shown that several standard spreadsheet functions facilitate the development of specialized models;
• •in simulation, where it will be seen how stochastic simulation may be facilitated through the use of an add-in, and how a decision support system may thus be built from scratch in less than 10 minutes.

A creative use of the spreadsheet in business OR models is presented in the second part of this presentation, with an example in process simulation: airport luggage traffic simulation. A short third part presents the possibilities offered by spreadsheet add-ins.     

The availability of unmanned air vehicles: a post-case study

An Unmanned Air Vehicle (UAV) is an unmanned, remotely controlled, small air vehicle. It has an important role in anti-surface warfare. This implies over-the-horizon detection, classification, targeting and battle damage assessment. To perform these tasks several UAVs are needed to assist or interchange with each other. An important problem is to determine how many UAVs are needed in this respect. The answer depends on the characteristics of the UAV and its mission. The UAV availability problem is very complex and the usual method to solve such a problem is simulation. A disadvantage of simulation is that it can be very time-consuming. Hence it is not very suitable for sensitivity analysis. Moreover, since simulation gives mere approximations and is not very generic, theoretical insights are hardly gained. In this paper we show how such a complex problem can still be tackled analytically by using a basic model from reliability theory, viz., a 1-out-of-n system with cold standby, ample repair facility and general life time and repair distributions.     

Nonparametric estimation of cumulative incidence functions for competing risks data with missing cause of failure

In this paper, we develop a fully nonparametric approach for the estimation of the cumulative incidence function with Missing At Random right-censored competing risks data. We obtain results on the pointwise asymptotic normality as well as the uniform convergence rate of the proposed nonparametric estimator. A simulation study that serves two purposes is provided. First, it illustrates in detail how to implement our proposed nonparametric estimator. Second, it facilitates a comparison of the nonparametric estimator to a parametric counterpart based on the estimator of Lu and Liang (2008). The simulation results are generally very encouraging.     

A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare

Existing approaches to conceptual modelling (CM) in discrete-event simulation do not formally support the participation of a group of stakeholders. Simulation in healthcare can benefit from stakeholder participation as it makes possible to share multiple views and tacit knowledge from different parts of the system. We put forward a framework tailored to healthcare that supports the interaction of simulation modellers with a group of stakeholders to arrive at a common conceptual model. The framework incorporates two facilitated workshops. It consists of a package including: three key stages and sub-stages; activities and guidance; tools and prescribed outputs. The CM framework is tested in a real case study of an obesity system. The benefits of using this framework in healthcare studies and more widely in simulation are discussed. The paper also considers how the framework meets the CM requirements.     

Target training with soft computing tools

The personal capabilities and intentions of employees indicate their performance within their organization. It is important for the organization to capture this kind of tacit knowledge since the workforce are the true experts in perceiving the organization's current reality and evaluating which assets require development – including themselves as knowledge assets. The collective inner voice of the workforce helps the organization's management to steer the company and its assets in a sustainable direction.This article presents how the collective inner voice of the workforce can be captured and how it can be used for the benefit of the organization and its employees. The objective is to support individuals’ personal aspirations, as well as to save the money, time and resources that an organization spends on personnel training.The focus of this article is on demonstrating a possible soft-computing method used for competency simulation. The process starts with a linguistic self-evaluation conducted by employees, where individuals’ own perception of current and target competence levels is captured. The self-evaluation is conducted with the help of fuzzy logic. Clusters are formed from the result dataset using an unsupervised neural network clustering method: self-organizing maps. A demonstrator tool is then used to perform a “what-if” type of analysis/simulation on the clusters in the results. With the demonstrator tool, employees can roughly test the impact of alternative training scenarios for themselves. For individuals this may open up new directions for self-development, and for organizations this may allow the efficient use of training resources. We tested the approach with a dataset from a real human resource development project among nuclear power plant operators.The case study reveals the potential of soft-computing based collective competency simulation as one part of personnel development projects in the future. Yet the techniques and the demonstrator tool used in this experiment are far from being products that employees could easily use as part of their training project. Possible benefits of the proposed approach are demonstrated in this article.     

A new nonparametric approach for multiplicity control:Optimal Subset procedures

Summary  A new approach for multiplicity control (Optimal Subset) is presented. This is based on the selection of the best subset of partial (univariate) hypotheses producing the minimal p-value. In this work, we show how to perform this new procedure in the permutation framework, choosing suitable combining functions and permutation strategies. The optimal subset approach can be very useful in exploratory studies because it performs a weak control for multiplicity which can be a valid alternative to the False Discovery Rate (FDR). A comparative simulation study and an application to neuroimaging real data shows that it is particularly useful in presence of a high number of hypotheses. We also show how stepwise regression may be a special case of Optimal Subset procedures and how to adjust the p-value of the selected model taking into account for the multiplicity arising from the possible different models selected by a stepwise regression.     

Provider and customer expectations of successful simulation projects

It is crucial that simulation projects are successful, but defining what is meant by success is far from straightforward, surprising though this may seem. This paper describes an analysis of interviews with simulation providers and customers. What emerges is (a) a definition of success and (b) that the two parties have different views of what constitutes a successful simulation project. The definition of success is based on a four stage model of changing perceptions and it assumes that success is not a simple binary variable, but can vary considerably throughout the life of a project. This suggests that simulation providers need to be careful in managing the expectations of their customers and in how they deliver the work. It is the authors' belief that this may also be true for Operational Research interventions other than those involving computer simulation.     

A Trajectory for Validating Computational Emulation Models of Organizations

Validation of complex simulation models is a challenging problem in computational organization theory research. In this paper, we describe a validation strategy suitable for emulation simulation systems, and show how a comprehensive validation consists of a sequence of steps that evaluate different aspects of a computational organizational simulation model. We demonstrate how this strategy can be applied to the evaluation of the Virtual Team Alliance (VTA), an emulation simulation system designed to guide managers charged with organizational change. VTA required a &201C;trajectory&201D; of successive validation experiments, before managers where willing to follow the recommendations of VTA. Ultimately, we believe this validation approach can be applied to a wide range of different simulation systems, and will make identification of the strengths and weaknesses of organizational simulations easier.     

Relevance assumed: a case study of balanced scorecard development using system dynamics

The balanced scorecard (BSC) has become a popular concept for performance measurement. It focuses attention of management on only a few performance measures and bridges different functional areas as it includes both financial and non-financial measures. However, doubts frequently arise regarding the quality of the BSCs developed as well as the quality of the process in which this development takes place. This article describes a case study in which system dynamics (SD) modelling and simulation was used to overcome both kinds of problems. In a two-stage modelling process (qualitative causal loop diagramming followed by quantitative simulation), a BSC was developed for management of one organizational unit of a leading Dutch insurer. This research illustrates how, through their involvement in this development process, management came to understand that seemingly contradictory goals such as customer satisfaction, employee satisfaction and employee productivity were, in fact, better seen as mutually reinforcing. Also, analysis of the SD model showed how, contrary to ex ante management intuition, performance would first have to drop further before significant improvements could be realized. Finally, the quantitative modelling process also helped to evaluate several improvement initiatives that were under consideration at the time, proving some of them to have unclear benefits, others to be very promising indeed.     

Simulation of Deep Drawing of Carbon Fibre Prepregs

The simulation of prepregs must regard highly anisotropic, viscoelastic and thermal-chemical properties. To this end a constitutive model is split into an anisotropic elastic part, which represents the fibre fraction and an isotropic, viscoelastic part, representing the matrix. The second part also contains curing, causing a dependency on time and temperature. During real deep-drawing processes large deformations up to 50 % occur, which is considered in a formulation at large strains. This model contains an anisotropic elastic part based on a Neo-Hooke law enhanced by an anisotropic part. A viscoelastic part is added using Hencky-strains and the work-conjugate Hill-stress to transfer a model for small strains into large strains. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)