Sublimation of snow from confierous forests in a climate model

Essery, R L H, Pomeroy, J W, Parvianen, J & Storck, P, Sublimation of snow from confierous forests in a climate model. Journal of Climate 16, pp 1855-1864 (2003).

Quantum chemical study of the effect of precursor stereochemistry on dissociative chemisorption and surface redox reactions during the atomic layer deposition of the transition metal copper

Using quantum chemical calculations, we investigate surface reactions of copper precursors and diethylzinc as the reducing agent for effective Atomic Layer Deposition (ALD) of Cu. The adsorption of various commonly used Cu(II) precursors is explored. The precursors vary in the electronegativity and conjugation of the ligands and flexibility of the whole molecule. Our study shows that the overall stereochemistry of the precursor governs the adsorption onto its surface. Formation of different Cu(II)/Cu(I)/Cu(0) intermediate complexes from the respective Cu(II) compounds on the surface is also explored. The surface model is a (111) facet of a Cu55 cluster. Cu(I) compounds are found to cover the surface after the precursor pulse, irrespective of the precursor chosen. We provide new information about the surface chemistry of Cu(II) versus Cu(I) compounds. A pair of CuEt intermediates or the dimer Cu2Et2 reacts in order to deposit a new Cu atom and release gaseous butane. In this reaction, two electrons from the Et anions are donated to copper for reduction to metallic form. This indicates that a ligand exchange between the Cu and Zn is important for the success of this transmetalation reaction. The effect of the ligands in the precursor on the electron density before and after adsorption onto the surface has also been computed through population analysis. In the Cu(I) intermediate, charge is delocalized between the Cu precursor and the bare copper surface, indicating metallic bonding as the precursor densifies to the surface.

Computational Journalism: from Answering Question to Questioning Answers and Raising Good Questions

Our media is saturated with claims of ``facts'' made from data. Database research has in the past focused on how to answer queries, but has not devoted much attention to discerning more subtle qualities of the resulting claims, e.g., is a claim ``cherry-picking''? This paper proposes a Query Response Surface (QRS) based framework that models claims based on structured data as parameterized queries. A key insight is that we can learn a lot about a claim by perturbing its parameters and seeing how its conclusion changes. This framework lets us formulate and tackle practical fact-checking tasks --- reverse-engineering vague claims, and countering questionable claims --- as computational problems. Within the QRS based framework, we take one step further, and propose a problem along with efficient algorithms for finding high-quality claims of a given form from data, i.e. raising good questions, in the first place. This is achieved to using a limited number of high-valued claims to represent high-valued regions of the QRS. Besides the general purpose high-quality claim finding problem, lead-finding can be tailored towards specific claim quality measures, also defined within the QRS framework. An example of uniqueness-based lead-finding is presented for ``one-of-the-few'' claims, landing in interpretable high-quality claims, and an adjustable mechanism for ranking objects, e.g. NBA players, based on what claims can be made for them. Finally, we study the use of visualization as a powerful way of conveying results of a large number of claims. An efficient two stage sampling algorithm is proposed for generating input of 2d scatter plot with heatmap, evalutaing a limited amount of data, while preserving the two essential visual features, namely outliers and clusters. For all the problems, we present real-world examples and experiments that demonstrate the power of our model, efficiency of our algorithms, and usefulness of their results.

Decision support systems for eco-friendly electronic products

This paper discusses an optimisation based decision support system and methodology for electronic packaging and product design and development which is capable of addressing in efficient manner specified environmental, reliability and cost requirements. A study which focuses on the design of a flip-chip package is presented. Different alternatives for the design of the flip-chip package are considered based on existing options for the applied underfill and volume of solder material used to form the interconnects. Variations in these design input parameters have simultaneous effect on package aspects such as cost, environmental impact and reliability. A decision system for the design of the flip-chip that uses numerical optimisation approach is used to identify the package optimal specification which satisfies the imposed requirements. The reliability aspect of interest is the fatigue of solder joints under thermal cycling. Transient nonlinear finite element analysis (FEA) is used to simulate the thermal fatigue damage in solder joints subject to thermal cycling. Simulation results are manipulated within design of experiments and response surface modelling framework to provide numerical model for reliability which can be used to quantify the package reliability. Assessment of the environmental impact of the package materials is performed by using so called Toxic Index (TI). In this paper we demonstrate the evaluation of the environmental impact only for underfill and lead-free solder materials. This evaluation is based on the amount of material per flip-chip package. Cost is the dominant factor in contemporary flip-chip packaging industry. In the optimisation based decision support system for the design of the flip-chip package, cost of materials which varies as a result of variations in the design parameters is considered.

A prognostic assessment method for power electronics modules

This paper describes a prognostic method which combines the physics of failure models with probability reasoning algorithm. The measured real time data (temperature vs. time) was used as the loading profile for the PoF simulations. The response surface equation of the accumulated plastic strain in the solder interconnect in terms of two variables (average temperature, and temperature amplitude) was constructed. This response surface equation was incorporated into the lifetime model of solder interconnect, and therefore the remaining life time of the solder component under current loading condition was predicted. The predictions from PoF models were also used to calculate the conditional probability table for a Bayesian Network, which was used to take into account of the impacts of the health observations of each product in lifetime prediction. The prognostic prediction in the end was expressed as the probability for the product to survive the expected future usage. As a demonstration, this method was applied to an IGBT power module used for aircraft applications.

Numerical optimisation techniques applied to evacuation analysis

A common problem faced by fire safety engineers in the field of evacuation analysis concerns the optimal design of an arbitrarily complex structure in order to minimise evacuation times. How does the engineer determine the best solution? In this study we introduce the concept of numerical optimisation techniques to address this problem. The study makes user of the buildingEXODUS evacuation model coupled with classical optimisation theory including Design of Experiments (DoE) and Response Surface Models (RSM). We demonstrate the technique using a relatively simple problem of determining the optimal location for a single exit in a square room.

Response shift in the assessment of quality of life among people attending cardiac rehabilitation

Objectives: To examine whether any response shift in quality of life assessment over the course of a cardiac rehabilitation programme could be explained by changes in individuals’ internal standards (recalibration), values (reprioritization) and/or conceptualization of quality of life and the extent to which any response shift could be explained by health locus of control, optimism and coping strategy. Design: Longitudinal survey design. Methods: The SEIQoL-DW was administered at the beginning and end of a cardiac rehabilitation programme. At the end of the programme, the SEIQoL-DW then-test was also administered to measure response shift. A total of 57 participants completed these measures and other measures to assess health locus of control, optimism and coping. Results: Response shift effects were observed in this population mainly due to recalibration. When response shift was incorporated into the analysis of QoL a larger treatment effect was observed. Active coping as a mechanism in the response shift model was found to have a significant positive correlation with response shift. Conclusion: This study showed that response shift occurs during cardiac rehabilitation. The occurrence of response shift in QoL ratings over time for this population could have implications for the estimation of the effectiveness of the intervention.

A probabilistic modelling scheme for analysis of long-term failure of cemented femoral joint replacements

Reliable prediction of long-term medical device performance using computer simulation requires consideration of variability in surgical procedure, as well as patient-specific factors. However, even deterministic simulation of long-term failure processes for such devices is time and resource consuming so that including variability can lead to excessive time to achieve useful predictions. This study investigates the use of an accelerated probabilistic framework for predicting the likely performance envelope of a device and applies it to femoral prosthesis loosening in cemented hip arthroplasty.
A creep and fatigue damage failure model for bone cement, in conjunction with an interfacial fatigue model for the implant–cement interface, was used to simulate loosening of a prosthesis within a cement mantle. A deterministic set of trial simulations was used to account for variability of a set of surgical and patient factors, and a response surface method was used to perform and accelerate a Monte Carlo simulation to achieve an estimate of the likely range of prosthesis loosening. The proposed framework was used to conceptually investigate the influence of prosthesis selection and surgical placement on prosthesis migration.
Results demonstrate that the response surface method is capable of dramatically reducing the time to achieve convergence in mean and variance of predicted response variables. A critical requirement for realistic predictions is the size and quality of the initial training dataset used to generate the response surface and further work is required to determine the recommendations for a minimum number of initial trials. Results of this conceptual application predicted that loosening was sensitive to the implant size and femoral width. Furthermore, different rankings of implant performance were predicted when only individual simulations (e.g. an average condition) were used to rank implants, compared with when stochastic simulations were used. In conclusion, the proposed framework provides a viable approach to predicting realistic ranges of loosening behaviour for orthopaedic implants in reduced timeframes compared with conventional Monte Carlo simulations.

Formal calibration methodology for CFD models of naturally ventilated indoor environments

Well planned natural ventilation strategies and systems in the built environments may provide healthy and comfortable indoor conditions, while contributing to a significant reduction in the energy consumed by buildings. Computational Fluid Dynamics (CFD) is particularly suited for modelling indoor conditions in naturally ventilated spaces, which are difficult to predict using other types of building simulation tools. Hence, accurate and reliable CFD models of naturally ventilated indoor spaces are necessary to support the effective design and operation of indoor environments in buildings. This paper presents a formal calibration methodology for the development of CFD models of naturally ventilated indoor environments. The methodology explains how to qualitatively and quantitatively verify and validate CFD models, including parametric analysis utilising the response surface technique to support a robust calibration process. The proposed methodology is demonstrated on a naturally ventilated study zone in the library building at the National University of Ireland in Galway. The calibration process is supported by the on-site measurements performed in a normally operating building. The measurement of outdoor weather data provided boundary conditions for the CFD model, while a network of wireless sensors supplied air speeds and air temperatures inside the room for the model calibration. The concepts and techniques developed here will enhance the process of achieving reliable CFD models that represent indoor spaces and provide new and valuable information for estimating the effect of the boundary conditions on the CFD model results in indoor environments. © 2012 Elsevier Ltd.

Arsenic removal from soil with high iron content using a natural surfactant and phosphate

An environment friendly arsenic removal technique from contaminated soil with high iron content has been studied. A natural surfactant extracted from soapnut fruit, phosphate solution and their mixture was used separately as extractants. The mixture was most effective in desorbing arsenic, attaining above 70 % efficiency in the pH range of 4–5. Desorption kinetics followed Elovich model. Micellar solubilization by soapnut and arsenic exchange mechanism by phosphate are the probable mechanisms behind arsenic desorption. Sequential extraction reveals that the mixed soapnut–phosphate system is effective in desorbing arsenic associated with amphoteric–Fe-oxide forms. No chemical change to the wash solutions was observed by Fourier transform-infrared spectra. Soil:solution ratio, surfactant and phosphate concentrations were found to affect the arsenic desorption process. Addition of phosphate boosted the performance of soapnut solution considerably. Response surface methodology approach predicted up to 80 % desorption of arsenic from soil when treated with a mixture of ≈1.5 % soapnut, ≈100 mM phosphate at a soil:solution ratio of 1:30.

Hexavalent Chromium Adsorption by a Novel Activated Carbon Prepared by Microwave Activation

Microwave heating reduces the preparation time and improves the adsorption quality of activated carbon. In this study, activated carbon was prepared by impregnation of palm kernel fiber with phosphoric acid followed by microwave activation. Three different types of activated carbon were prepared, having high surface areas of 872 m2 g-1, 1256 m2 g-1, and 952 m2 g-1 and pore volumes of 0.598 cc g-1, 1.010 cc g-1, and 0.778 cc g-1, respectively. The combined effects of the different process parameters, such as the initial adsorbate concentration, pH, and temperature, on adsorption efficiency were explored with the help of Box-Behnken design for response surface methodology (RSM). The adsorption rate could be expressed by a polynomial equation as the function of the independent variables. The hexavalent chromium adsorption rate was found to be 19.1 mg g-1 at the optimized conditions of the process parameters, i.e., initial concentration of 60 mg L-1, pH of 3, and operating temperature of 50 oC. Adsorption of Cr(VI) by the prepared activated carbon was spontaneous and followed second-order kinetics. The adsorption mechanism can be described by the Freundlich Isotherm model. The prepared activated carbon has demonstrated comparable performance to other available activated carbons for the adsorption of Cr(VI).

DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

This paper presents a surrogate-model based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine’s previous operational performance, the DFIG’s stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization (PSO)-based surrogate optimization techniques are used in conjunction with the finite element method (FEM) to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Investigation of Utilizing Single Surface Depressions in Optimization of NLF Aerofoil Design

An environment has been created for the optimisation of aerofoil profiles with inclusion of small surface features. For TS wave dominated flows, the paper examines the consequences of the addition of a depression on the aerodynamic optimisation of an NLF aerofoil, and describes the geometry definition fidelity and optimisation algorithm employed in the development process. The variables that define the depression for this optimisation investigation have been fixed, however a preliminary study is presented demonstrating the sensitivity of the flow to the depression characteristics. Solutions to the optimisation problem are then presented using both gradient-based and genetic algorithm techniques, and for accurate representation of the inclusion of small surface perturbations it is concluded that a global optimisation method is required for this type of aerofoil optimisation task due to the nature of the response surface generated. When dealing with surface features, changes in the transition onset are likely to be of a non-linear nature so it is highly critical to have an optimisation algorithm that is robust, suggesting that for this framework, gradient-based methods alone are not suited.

Reciclagem termoquímica de resíduos de plásticos e de pneus por pirólise

A sociedade moderna encontra-se cada vez mais dependente dos combustíveis líquidos bem como de produtos derivados do petróleo. Em virtude do limitado tempo de vida das reservas naturais de petróleo, torna-se imperativo encontrar fontes alternativas de produção de hidrocarbonetos. A pirólise de resíduos de pneus e plásticos pode ser uma dessas possíveis fontes. Neste processo, o tratamento termoquímico implementado aos resíduos permite, não só, a valorização económica resultante da sua transformação em produtos de valor acrescido, como também a recuperação do conteúdo orgânico. O referido processo conduz à formação de hidrocarbonetos em fase líquida que podem ser utilizados pela indústria como combustíveis líquidos e/ou como matéria-prima. O presente trabalho tem como objectivo principal a definição das condições experimentais mais propícias à obtenção de combustíveis líquidos (maximização) resultantes da pirólise de misturas de resíduos de borracha de pneus e plásticos nomeadamente polietileno (PE), polipropileno (PP) e poliestireno (PS). Como instrumento de optimização das condições experimentais optou-se pela Metodologia dos Planos Factoriais de Ensaios. Os resultados experimentais obtidos mostram que as taxas de conversão em fase líquida podem atingir valores superiores a 80% (m/m) dependendo das condições experimentais utilizadas bem como do tipo e mistura de resíduos a pirolisar. Os rendimentos das fracções gasosa e sólida podem atingir valores na ordem dos 5% e 12% (respectivamente). Foi também estudado o efeito das condições experimentais nomeadamente a temperatura de reacção, pressão inicial, tempo de reacção e composição da mistura. Este estudo revelou que a maximização da fracção líquida é favorecida por uma temperatura de ensaio de 370ºC, uma pressão inicial de 0,48MPa e um tempo de ensaio de 15 minutos. Relativamente à composição da mistura, os melhores resultados foram obtidos com 30% (m/m) de resíduos de borracha de pneus (BP) associados a uma mistura de 70% (m/m) de resíduos de plásticos composta por 20% polietileno, 30% polipropileno e 20% poliestireno. Igualmente foi feita a caracterização física e química da matéria-prima e dos produtos obtidos pelo referido processo, bem como, o estudo da presença de diferentes substâncias potencialmente doadores de hidrogénio ao meio reaccional de forma a melhorar o rendimento líquido. Por último, foram realizados estudos cinéticos das reacções químicas de formação dos diferentes produtos aos resíduos de borracha de pneus (BP), misturas de resíduos de plástico (PE, PP e PS) e suas misturas. Ainda, foram ajustados os resultados obtidos pelo modelo teórico aos resultados experimentais, propostos mecanismos reaccionais de formação dos produtos e calculados os parâmetros cinéticos. De acordo com os resultados obtidos, a pirólise pode representar um papel significativo na valorização energética e orgânica destes resíduos apesar de, ainda, ser necessário o desenvolvimento de alguns aspectos tecnológicos de modo a tornar mais atraente a implementação desta tecnologia à escala industrial.

Cimentos de fosfato de magnésio: consolidação e caracterização

A reação entre o óxido de magnésio (MgO) e o fosfato de monoamónio (MAP), à temperatura ambiente, origina os cimentos de fosfato de magnésio, materiais caracterizados pela sua presa rápida e pelas excelentes propriedades mecânicas adquiridas precocemente. As propriedades finais são dependentes, essencialmente, da composição do cimento (razão molar magnésia:fosfato e utilização de retardantes de presa) mas também são influenciadas pela reatividade da magnésia utilizada. Neste trabalho, a reação foi caracterizada através do estudo da influência da razão molar MgO:MAP (variando de 1:1 até 8:1), da presença e teor de aditivos retardantes (ácido bórico, ácido cítrico e tripolifosfato de sódio) e da variação da área superficial específica da magnésia (conseguida por calcinação do óxido), no tempo de presa, na temperatura máxima atingida e nas fases cristalinas finais formadas. A reação de presa pode ser comparada à hidratação do cimento Portland, com a existência de 4 estágios (reação inicial, indução, aceleração e desaceleração), com a diferença que estes estágios ocorrem a velocidade muito mais alta nos cimentos de fosfato de magnésio. Este estudo foi realizado utilizando a espetroscopia de impedâncias, acompanhada pela monitorização da evolução de temperatura ao longo do tempo de reação e, por paragem de reação, identificando as fases cristalinas formadas. A investigação do mecanismo de reação foi complementada com a observação da microestrutura dos cimentos formados e permitiu concluir que a origem da magnésia usada não afeta a reação nem as propriedades do cimento final. A metodologia de superfície de resposta foi utilizada para o estudo e otimização das características finais do produto, tendo-se mostrado um método muito eficaz. Para o estudo da variação da área superficial específica da magnésia com as condições de calcinação (temperatura e tempo de patamar) usou-se o planeamento fatorial de experiências tendo sido obtido um modelo matemático que relaciona a resposta da área superficial específica da magnésia com as condições de calcinação. As propriedades finais dos cimentos (resistência mecânica à compressão e absorção de água) foram estudadas utilizando o planeamento simplex de experiências, que permitiu encontrar modelos que relacionam a propriedade em estudo com os valores das variáveis (razão molar MgO:MAP, área superficial específica da magnésia e quantidade de ácido bórico). Estes modelos podem ser usados para formular composições e produzir cimentos com propriedades finais específicas.