Using low fidelity simulation in interactive workshops for undergraduate medical and midwifery students

There is recognition of the need to continuously improve inter-professional relationships within clinical practice. Mutual respect, effective communication and working together are factors which will contribute to higher standards of care (Miers et al, 2005; Begley, 2008). An inter-professional education initiative, using low-fidelity simulation has been piloted and subsequently embedded within a pre-registration midwifery curriculum. The aim of the collaboration is to enhance inter-professional learning by providing an opportunity for final year midwifery students and 4th year medical students within a non-threatening environment to interact and communicate prior to obstetric clinical placements. The midwifery students are provided with an outline agenda for the workshop, but are encouraged to use creative license with regard to workshop delivery. Preliminary evaluations have been positive from both midwifery and medical students. The teaching sessions have provided an opportunity to learn about and respect each other’s roles. The midwifery students have commented on the enjoyable aspects of team working during preparation and the confidence gained from teaching medical students. The medical students felt that the sessions lowered their anxiety levels going into the labour setting. This workshop will demonstrate how low-fidelity simulation can effectively enhance the students experience promoting team working and self-confidence.

A new battery modelling method based on simulation error minimization

A new battery modelling method is presented based on the simulation error minimization criterion rather than the conventional prediction error criterion. A new integrated optimization method to optimize the model parameters is proposed. This new method is validated on a set of Li ion battery test data, and the results confirm the advantages of the proposed method in terms of the model generalization performance and long-term prediction accuracy.

A Computational Approach for Simulating P-type Silicon Piezoresistor Using Four Point Bending Setup

The piezoresistance effect is defined as change in resistance due to applied stress. Silicon has a relatively large piezoresistance effect which has been known since 1954. A four point bending setup is proposed and designed to analyze the piezoresistance effect in p-type silicon. This setup is used to apply uniform and uniaxial stress along the <110> crystal direction. The main aim of this work is to investigate the piezoresistive characteristic of p-type resistors as a function of doping concentrations using COMSOL Multiphysics. Simulation results are compared with experimental data.

3D FEM simulation of helical milling hole process for titanium alloy Ti-6Al-4V

As an emerging hole-machining methodology, helical milling process has become increasingly popular in aeromaterials manufacturing research, especially in areas of aircraft structural parts, dies, and molds manufacturing. Helical milling process is highly demanding due to its complex tool geometry and the progressive material failure on the workpiece. This paper outlines the development of a 3D finite element model for helical milling hole of titanium alloy Ti-6Al-4V using commercial FE code ABAQUS/Explicit. The proposed model simulates the helical milling hole process by taking into account the damage initiation and evolution in the workpiece material. A contact model at the interface between end-mill bit and workpiece has been established and the process parameters specified. Furthermore, a simulation procedure is proposed to simulate different cutting processes with the same failure parameters. With this finite element model, a series of FEAs for machined titanium alloy have been carried out and results compared with laboratory experimental data. The effects of machining parameters on helical milling have been elucidated, and the capability and advantage of FE simulation on helical milling process have been well presented.

NanoStreams: Codesigned Microservers for Edge Analytics in Real Time

NanoStreams explores the design, implementation,and system software stack of micro-servers aimed at processingdata in-situ and in real time. These micro-servers can serve theemerging Edge computing ecosystem, namely the provisioningof advanced computational, storage, and networking capabilitynear data sources to achieve both low latency event processingand high throughput analytical processing, before consideringoff-loading some of this processing to high-capacity datacentres.NanoStreams explores a scale-out micro-server architecture thatcan achieve equivalent QoS to that of conventional rack-mountedservers for high-capacity datacentres, but with dramaticallyreduced form factors and power consumption. To this end,NanoStreams introduces novel solutions in programmable & con-figurable hardware accelerators, as well as the system softwarestack used to access, share, and program those accelerators.Our NanoStreams micro-server prototype has demonstrated 5.5×higher energy-efficiency than a standard Xeon Server. Simulationsof the microserver’s memory system extended to leveragehybrid DDR/NVM main memory indicated 5× higher energyefficiencythan a conventional DDR-based system. 

Contributions to the theory of maximum entropy estimation for ill-posed models

As técnicas estatísticas são fundamentais em ciência e a análise de regressão linear é, quiçá, uma das metodologias mais usadas. É bem conhecido da literatura que, sob determinadas condições, a regressão linear é uma ferramenta estatística poderosíssima. Infelizmente, na prática, algumas dessas condições raramente são satisfeitas e os modelos de regressão tornam-se mal-postos, inviabilizando, assim, a aplicação dos tradicionais métodos de estimação. Este trabalho apresenta algumas contribuições para a teoria de máxima entropia na estimação de modelos mal-postos, em particular na estimação de modelos de regressão linear com pequenas amostras, afetados por colinearidade e outliers. A investigação é desenvolvida em três vertentes, nomeadamente na estimação de eficiência técnica com fronteiras de produção condicionadas a estados contingentes, na estimação do parâmetro ridge em regressão ridge e, por último, em novos desenvolvimentos na estimação com máxima entropia. Na estimação de eficiência técnica com fronteiras de produção condicionadas a estados contingentes, o trabalho desenvolvido evidencia um melhor desempenho dos estimadores de máxima entropia em relação ao estimador de máxima verosimilhança. Este bom desempenho é notório em modelos com poucas observações por estado e em modelos com um grande número de estados, os quais são comummente afetados por colinearidade. Espera-se que a utilização de estimadores de máxima entropia contribua para o tão desejado aumento de trabalho empírico com estas fronteiras de produção. Em regressão ridge o maior desafio é a estimação do parâmetro ridge. Embora existam inúmeros procedimentos disponíveis na literatura, a verdade é que não existe nenhum que supere todos os outros. Neste trabalho é proposto um novo estimador do parâmetro ridge, que combina a análise do traço ridge e a estimação com máxima entropia. Os resultados obtidos nos estudos de simulação sugerem que este novo estimador é um dos melhores procedimentos existentes na literatura para a estimação do parâmetro ridge. O estimador de máxima entropia de Leuven é baseado no método dos mínimos quadrados, na entropia de Shannon e em conceitos da eletrodinâmica quântica. Este estimador suplanta a principal crítica apontada ao estimador de máxima entropia generalizada, uma vez que prescinde dos suportes para os parâmetros e erros do modelo de regressão. Neste trabalho são apresentadas novas contribuições para a teoria de máxima entropia na estimação de modelos mal-postos, tendo por base o estimador de máxima entropia de Leuven, a teoria da informação e a regressão robusta. Os estimadores desenvolvidos revelam um bom desempenho em modelos de regressão linear com pequenas amostras, afetados por colinearidade e outliers. Por último, são apresentados alguns códigos computacionais para estimação com máxima entropia, contribuindo, deste modo, para um aumento dos escassos recursos computacionais atualmente disponíveis.

A computational study of ionic liquids used in the production of fuels and biofuels

For the past decades it has been a worldwide concern to reduce the emission of harmful gases released during the combustion of fossil fuels. This goal has been addressed through the reduction of sulfur-containing compounds, and the replacement of fossil fuels by biofuels, such as bioethanol, produced in large scale from biomass. For this purpose, a new class of solvents, the Ionic Liquids (ILs), has been applied, aiming at developing new processes and replacing common organic solvents in the current processes. ILs can be composed by a large number of different combinations of cations and anions, which confer unique but desired properties to ILs. The ability of fine-tuning the properties of ILs to meet the requirements of a specific application range by mixing different cations and anions arises as the most relevant aspect for rendering ILs so attractive to researchers. Nonetheless, due to the huge number of possible combinations between the ions it is required the use of cheap predictive approaches for anticipating how they will act in a given situation. Molecular dynamics (MD) simulation is a statistical mechanics computational approach, based on Newton’s equations of motion, which can be used to study macroscopic systems at the atomic level, through the prediction of their properties, and other structural information. In the case of ILs, MD simulations have been extensively applied. The slow dynamics associated to ILs constitutes a challenge for their correct description that requires improvements and developments of existent force fields, as well as larger computational efforts (longer times of simulation). The present document reports studies based on MD simulations devoted to disclose the mechanisms of interaction established by ILs in systems representative of fuel and biofuels streams, and at biomass pre-treatment process. Hence, MD simulations were used to evaluate different systems composed of ILs and thiophene, benzene, water, ethanol and also glucose molecules. For the latter molecules, it was carried out a study aiming to ascertain the performance of a recently proposed force field (GROMOS 56ACARBO) to reproduce the dynamic behavior of such molecules in aqueous solution. The results here reported reveal that the interactions established by ILs are dependent on the individual characteristics of each IL. Generally, the polar character of ILs is deterministic in their propensity to interact with the other molecules. Although it is unquestionable the advantage of using MD simulations, it is necessary to recognize the need for improvements and developments of force fields, not only for a successful description of ILs, but also for other relevant compounds such as the carbohydrates.

Multiphysics Simulation of Nanostructured Semiconductor Devices

Thesis (Ph.D.)--University of Washington, 2013

Simulation model for driving dynamics, energy use and power supply

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Offshore wind turbine simulation: multibody drive train. Bacl-to-back NPC (Neutral Point Clamped) converters: Fractional-order control

This paper is on offshore wind energy conversion systems installed on the deep water and equipped with back-to-back neutral point clamped full-power converter, permanent magnet synchronous generator with an AC link. The model for the drive train is a five-mass model which incorporates the dynamic of the structure and the tower in order to emulate the effect of the moving surface. A three-level converter and a four-level converter are the two options with a fractional-order control strategy considered to equip the conversion system. Simulation studies are carried out to assess the quality of the energy injected into the electric grid. Finally, conclusions are presented. (C) 2014 Elsevier Ltd. All rights reserved.

Simulation and dynamics of freeway traffic

This paper presents the new package entitled Simulator of Intelligent Transportation Systems (SITS) and a computational oriented analysis of traffic dynamics. The SITS adopts a microscopic simulation approach to reproduce real traffic conditions considering different types of vehicles, drivers and roads. A set of experiments with the SITS reveal the dynamic phenomena exhibited by this kind of system. For this purpose a modelling formalism is developed that embeds the statistics and the Laplace transform. The results make possible the adoption of classical system theory tools and point out that it is possible to study traffic systems taking advantage of the knowledge gathered with automatic control algorithms. A complementary perspective for the analysis of the traffic flow is also quantified through the entropy measure.