Integrated fluid-thermal-structural numerical analysis for the quenching of metallic components

The quenching of a metal component with a channel section in a water tank is numerically simulated. Computational fluid dynamics (CFD) is used to model the multiphase flow and the heat transfer in film boiling, nucleate boiling and convective cooling processes to calculate the difference in heat transfer rate around the component and then combining with the thermal simulation and structure analysis of the component to study the effect of heat transfer rate on the distortion of the U-channel component. A model is also established to calculate the residual stress produced by quenching. The coupling fluid-thermal-structural simulation provides an insight into the deformation of the component and can be used to perform parameter analysis to reduce the distortion of the component. © 2011 Shanghai Jiaotong University and Springer-Verlag Berlin Heidelberg.

Damage identification of civil infrastructure in the time domain using FEM calibrated ARMAX model

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. First, a high quality finite element model is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then developed and calibrated. The calibrated ARMAX model can be used to identify damage in different scenarios through model updating process using clonal selection algorithm (CSA). The identification results demonstrate the performance of the proposed methodology, which has the potential to be used for damage identification in practices.

The effects of website quality on adoption of e-government service : an empirical study applying UTAUT model using SEM

In today’s global age, e-government services have become the main channel for online communication between the government and its citizens. They aim to provide citizens with more accessible, accurate, real-time and high quality services. Therefore, the quality of government websites which provide e-services is an essential factor in the successful adoption of e-government services by the public. This paper discusses an investigation of the effect of the Website Quality (WQ) factor on the acceptance of using e-government services (G2C) in the Kingdom of Saudi Arabia (KSA) by adopting the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. Survey Data collected from 400 respondents were examined using the structural equation modelling (SEM) technique and utilising AMOS tools. This study found that the factors that significantly influenced the Use Behaviour of e-government services in KSA (USE) include Performance Expectancy (PE), Effort expectancy (EE), Facilitating Conditions (FC) and Website Quality (WQ), while the construct known Social Influence (SI) did not. Moreover, the results confirm the importance of quality government websites and support systems as one of the main significant and influential factors of e-government services adoption. The results of this study can be helpful to Saudi’s governmental sectors to adjust their corporate strategies and plans to advance successful adoption and diffusion of e-government services (G2C) in KSA.

Service quality in a higher education context : an integrated model

Purpose – The aim of this study is to develop and empirically test an integrated model incorporating the antecedents and consequences of service quality in a higher education context.

Design/methodology/approach – This research employed both qualitative and quantitative research methods. The data from three focus groups, conducted at the Central Queensland University (CQU), Rockhampton, Australia, generated key themes and their interrelationships. The theoretical model was then tested using structural equation modelling technique on a sample of 528 university students.

Findings – The findings show that information (marketing communications) is more statistically significant than past experience as the antecedents of service quality. The consequences of service quality are composed of trust, satisfaction, and image. Overall, the results suggest a good validity of the theoretical model and the key paths in the model are found statistically significant, except past experience affecting service quality.

Originality/value – The model provides a good explanation of a university brand image, and perceived service quality was found playing an important role in this model. Universities intending to enhance their image are encouraged to consider focusing their efforts on marketing communication information, service quality, student satisfaction and trust.

FEM calibrated ARMAX model updating method for time domain damage identification

Due to environmental loads, mechanical damages, structural aging and human factors, civil infrastructure inevitably deteriorate during their service lives. Since their damage may claim human lives and cause significant economic losses, how to identify damages and assess structural conditions timely and accurately has drawn increasingly more attentions from structural engineering community worldwide. In this study, a fast and sensitive time domain damage identification method will be developed. To do this, a finite element model of a steel pipe laid on the soil is built and the structural responses are simulated under different damage scenarios. Based on the simulated data, an Auto Regressive Moving Average Exogenous (ARMAX) model is then built and calibrated. The calibrated ARMAX model is used to identify different damage scenarios through model updating process using clonal selection algorithm (CSA). The results demonstrate the application potential of the proposed method in identifying the pipeline conditions. To further verify its performance, laboratory tests of a steel pipe laid on the soil with and without soil support (free span damage) are carried out. The identification results of pipe-soil system show that the proposed method is capable of identifying damagein a complex structural system. Therefore, it can be applied to identifying pipeline conditions.

Construction cost performance of structural frames in Australia

This research is concerned with the comparative cost of building structural frames in Australia. The research has been undertaken to evaluate the cost performance of a number of technologies that are typically used in medium-rise commercial buildings of ten storeys. The research methodology is based on pricing a number of standard building frame designs in five Australian cities. The results represent the cost of producing the same building using different building construction designs. By utilising a standard model, project variables like building quality, ground conditions and access were eradicated, thereby facilitating an unbiased comparison of cost performance. The second stage of the research invoiced a focus group of industry experts who were asked to validate the results of the cost study. In addition, participants of the focus group were asked to comment on the preferred construction practice for each of the typical building designs. Results suggest that post-tensioned in situ concrete frames have the best cost performance for most buildings. However, other designs can have good cost performance under some circumstances. Findings suggest that the Australian construction industry has long cultural preference for the use of in situ concrete in structural frames.

The cost-effectiveness of the Dose Adjustment for Normal Eating (DAFNE) structured education programme: an update using the Sheffield Type 1 Diabetes policy model

AIMS: 
To estimate the cost-effectiveness of training in flexible intensive insulin therapy [as provided in the Dose Adjustment for Normal Eating (DAFNE) structured education programme] compared with no training for adults with Type 1 diabetes mellitus in the UK using the Sheffield Type 1 Diabetes Policy Model.

METHODS: 
The Sheffield Type 1 Diabetes Policy Model was used to simulate the development of long-term microvascular and macrovascular diabetes-related complications and the occurrence of diabetes-related adverse events in 5000 adults with Type 1 diabetes. Total costs and quality-adjusted life years were estimated from a National Health Service perspective over a lifetime horizon, discounted at a rate of 3.5%. The treatment effectiveness of DAFNE was modelled as a reduction in HbA1c that affected the risk of developing long-term diabetes-related complications. Probabilistic and structural sensitivity analyses were conducted.

RESULTS:
DAFNE resulted in greater life expectancy and reduced incidence of some diabetes-related complications compared with no DAFNE. DAFNE was found to generate an average of 0.0294 additional quality-adjusted life years for an additional cost of £426 per patient, leading to an incremental cost-effectiveness ratio of £14 400 compared with no DAFNE. There was a 54% probability that DAFNE would be cost-effective at a willingness-to-pay threshold of £20 000 per quality-adjusted life year.

CONCLUSIONS: 
The results of this study suggest that DAFNE is a cost-effective structured education programme for people with Type 1 diabetes and support its provision by the National Health Service in the UK.

Finite element model updating using estimation of distribution algorithm

Finite Element (FE) model updating has been attracting research attentions in structural engineering fields for over 20 years. Its immense importance to the design, construction and maintenance of civil and mechanical structures has been highly recognised. However, many sources of uncertainties may affect the updating results. These uncertainties may be caused by FE modelling errors, measurement noises, signal processing techniques, and so on. Therefore, research efforts on model updating have been focusing on tackling with uncertainties for a long time. Recently, a new type of evolutionary algorithms has been developed to address uncertainty problems, known as Estimation of Distribution Algorithms (EDAs). EDAs are evolutionary algorithms based on estimation and sampling from probabilistic models and able to overcome some of the drawbacks exhibited by traditional genetic algorithms (GAs). In this paper, a numerical steel simple beam is constructed in commercial software ANSYS. The various damage scenarios are simulated and EDAs are employed to identify damages via FE model updating process. The results show that the performances of EDAs for model updating are efficient and reliable.

Vibration based damage identification of a scale-model steel frame structure subjected to bolt connection failures

Large-span steel frame structures prove to be an ideal choice for their speed of construction, relatively low cost, strength, durability and structural design flexibility. For this type of structure, the beam-column connections are critical for its structural integrity and overall stability. This is because a steel frame generally fails first at its connectors, due to the change in stress redistribution with adjacent members and material related failures, caused by various factors such as fire, seismic activity or material deterioration. Since particular attention is required at a steel frame’s connection points, this study explores the applicability of a comprehensive structural health monitoring (SHM) method to identify early damage and prolong the lifespan of connection points of steel frames. An impact hammer test was performed on a scale-model steel frame structure, recording its dynamic response to the hammer strike via an accelerometer. The testing procedure included an intact scenario and two damage scenarios by unfastening four bolt connections in an accumulating order. Based entirely on time-domain experimental data for its calibration, an Auto Regressive Average Exogenous (ARMAX) model is used to create a simple and accurate model for vibration simulation. The calibrated ARMAX model is then used to identify various bolt-connection related damage scenarios via R² value. The findings in this study suggest that the proposed time-domain approach is capable of identifying structural damage in a parsimonious manner and can be used as a quick or initial solution.

Structural equation modeling for evaluating the user perceptions of E-learning effectiveness in higher education

A crucial prerequisite for sustainable e-learning is the understanding of learners’ preferences for various pedagogical strategies, technologies, and the management of learning resources. This paper presents an empirical study aiming to empirically test the theoretical (pedagogies, technologies and management) (PTM) model on the preference of learners and on the perceived impact of the effectiveness of e-learning. This study uses structural equation modelling (SEM) to identify the critical dimensions in the PTM model for augmenting the effectiveness of e-learning. This leads to the development of a PTM model with the path coefficients showing weak to strong relationships ranging from 0.15 to 0.42 with acceptable significance levels. The results support the hypothesis that management, technology, resources and metadata ontology dimensions affect the effectiveness of elearning both directly and indirectly through enhancing the management effectiveness of learning resources. However, the result does not support positive influence of pedagogical strategy per se on e-learning effectiveness. The implications of this study indicate the criticality of effective management of learning resources to enhance e-learning effectiveness.

Identifying affinity classes of inorganic materials binding sequences via a graph-based model

Rapid advances in bionanotechnology have recently generated growing interest in identifying peptides that bind to inorganic materials and classifying them based on their inorganic material affinities. However, there are some distinct characteristics of inorganic materials binding sequence data that limit the performance of many widely-used classification methods when applied to this problem. In this paper, we propose a novel framework to predict the affinity classes of peptide sequences with respect to an associated inorganic material. We first generate a large set of simulated peptide sequences based on an amino acid transition matrix tailored for the specific inorganic material. Then the probability of test sequences belonging to a specific affinity class is calculated by minimizing an objective function. In addition, the objective function is minimized through iterative propagation of probability estimates among sequences and sequence clusters. Results of computational experiments on two real inorganic material binding sequence data sets show that the proposed framework is highly effective for identifying the affinity classes of inorganic material binding sequences. Moreover, the experiments on the structural classification of proteins (SCOP) data set shows that the proposed framework is general and can be applied to traditional protein sequences.

A unit root model for trending time-series energy variables

In this paper, we propose a GARCH-based unit root test that is flexible enough to account for; (a) trending variables, (b) two endogenous structural breaks, and (c) heteroskedastic data series. Our proposed model is applied to a range of time-series, trending, and heteroskedastic energy variables. Our two main findings are: first, the proposed trend-based GARCH unit root model outperforms a GARCH model without trend; and, second, allowing for a time trend and two endogenous structural breaks are important in practice, for doing so allows us to reject the unit root null hypothesis.

The potential utility of a staging model as a course specifier: a bipolar disorder perspective.

Staging models are widely used in clinical medicine, and offer an insight into the progressive nature of many disorders. In general, the earlier stages of illness may be associated with a better prognosis and a higher treatment response. Once chronicity is reached, more complex and invasive treatments may be required, and the utility of treatments may decline. There is evidence that treatment response is greatest in the early phases of the disorder. There is also a progressive social and psychological burden of ongoing illness. This is paralleled by the twin notions of neuroprotection, which is supported by increasing evidence that structural changes in the disorder may be progressive and reversible with algorithm appropriate treatment, and that of early intervention, which posits that the optimal window for intervention is early in the illness course. A staging model compliments existing and proposed classifications of bipolar disorder, adding a temporal dimension to a cross sectional view. It may inform treatment choice and prognosis, and could have utility as a course specifier.

Farmland prices, structural breaks and panel data

Previous time series evidence has indicated that farmland prices and cash rents are not cointegrated, a finding at odds with the present value model of farmland prices. We argue that this failure to find cointegration may be due to low power of tests and to the presence of structural change representing a shifting risk premium on farmland investments. To accommodate this possibility, we use panel unit root and cointegration methods that are more powerful than conventional time series methods and allow for breaks in the cointegration relationship. Our results, based on a large panel covering 31 US states between 1960 and 2000, suggest that the present value model of farmland prices cannot be rejected. © Oxford University Press and Foundation for the European Review of Agricultural Economics 2007; all rights reserved.

Panel cointegration and the monetary exchange rate model

This paper re-examines the validity of the monetary exchange rate model during the post-Bretton Woods era for 18 OECD countries. Our analysis simultaneously considers the presence of both cross-sectional dependence and multiple structural breaks, which have not received much attention in previous studies of the monetary model. The empirical results indicate that the monetary model emerges only when the presence of structural breaks and cross-country dependence has been taken into account. Evidence is also provided suggesting that the breaks in the monetary model can be derived from the underlying purchasing power parity relation. © 2008 Elsevier B.V. All rights reserved.