Response Surface Modeling and Optimisation for Reliable Electronic Products

The aim of integrating computational mechanics (FEA and CFD) and optimization tools is to speed up dramatically the design process in different application areas concerning reliability in electronic packaging. Design engineers in the electronics manufacturing sector may use these tools to predict key design parameters and configurations (i.e. material properties, product dimensions, design at PCB level. etc) that will guarantee the required product performance. In this paper a modeling strategy coupling computational mechanics techniques with numerical optimization is presented and demonstrated with two problems. The integrated modeling framework is obtained by coupling the multi-physics analysis tool PHYSICA - with the numerical optimization package - Visua/DOC into a fuJly automated design tool for applications in electronic packaging. Thermo-mechanical simulations of solder creep deformations are presented to predict flip-chip reliability and life-time under thermal cycling. Also a thermal management design based on multi-physics analysis with coupled thermal-flow-stress modeling is discussed. The Response Surface Modeling Approach in conjunction with Design of Experiments statistical tools is demonstrated and used subsequently by the numerical optimization techniques as a part of this modeling framework. Predictions for reliable electronic assemblies are achieved in an efficient and systematic manner.

The impact of the passenger response time distribution on ship evacuation performance

The International Maritime Organisation (IMO) has adopted the use of computer simulation to assist in the assessment of the assembly time for passenger ships. A key parameter required for this analysis and specified as part of the IMO guidelines is the passenger response time distribution. It is demonstrated in this paper that the IMO specified response time distribution assumes an unrealistic mathematical form. This unrealistic mathematical form can lead to serious congestion issues being overlooked in the evacuation analysis and lead to incorrect conclusions concerning the suitability of vessel design. In light of these results, it is vital that IMO undertake research to generate passenger response time data suitable for use in evacuation analysis of passenger ships. Until this type of data becomes readily available, it is strongly recommended that rather than continuing to use the artificial and unrepresentative form of the response time distribution, IMO should adopt plausible and more realistic response time data derived from land based applications. © 2005: Royal Institution of Naval Architects.

Investigating the impact of occupant response time on computer simulations of the WTC North Tower evacuation

This work explores the impact of response time distributions on high-rise building evacuation. The analysis utilises response times extracted from printed accounts and interviews of evacuees from the WTC North Tower evacuation of 11 September 2001. Evacuation simulations produced using these “real” response time distributions are compared with simulations produced using instant and engineering response time distributions. Results suggest that while typical engineering approximations to the response time distribution may produce reasonable evacuation times for up to 90% of the building population, using this approach may underestimate total evacuation times by as much as 61%. These observations are applicable to situations involving large high-rise buildings in which travel times are generally expected to be greater than response times

Reliability analysis for power electronics modules

This paper discusses the reliability of power electronics modules. The approach taken combines numerical modeling techniques with experimentation and accelerated testing to identify failure modes and mechanisms for the power module structure and most importantly the root cause of a potential failure. The paper details results for two types of failure (i) wire bond fatigue and (ii) substrate delamination. Finite element method modeling techniques have been used to predict the stress distribution within the module structures. A response surface optimisation approach has been employed to enable the optimal design and parameter sensitivity to be determined. The response surface is used by a Monte Carlo method to determine the effects of uncertainty in the design.

Evacuation modelling analysis within the operational research context: a combined approach for improving enclosure designs

Evacuation models have been playing an important function in the transition process from prescriptive fire safety codes to performance-based ones over the last three decades. In fact, such models became also useful tools in different tasks within fire safety engineering field, such as fire risks assessment and fire investigation. However, there are some difficulties in this process when using these models. For instance, during the evacuation modelling analysis, a common problem faced by fire safety engineers concerns the number of simulations which needs to be performed. In other terms, which fire designs (i.e., scenarios) should be investigated using the evacuation models? This type of question becomes more complex when specific issues such as the optimal positioning of exits within an arbitrarily structure needs to be addressed. Therefore, this paper presents a methodology which combines the use of evacuation models with numerical techniques used in the operational research field, such as Design of Experiments (DoE), Response Surface Models (RSM) and the numerical optimisation techniques. The methodology here presented is restricted to evacuation modelling analysis, nevertheless this same concept can be extended to fire modelling analysis.

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.

Ultra-wideband cognitive interrogator network for indoor location tracking - part 1: system architecture and network performance analysis

We explore the potential application of cognitive interrogator network (CIN) in remote monitoring of mobile subjects in domestic environments, where the ultra-wideband radio frequency identification (UWB-RFID) technique is considered for accurate source localization. We first present the CIN architecture in which the central base station (BS) continuously and intelligently customizes the illumination modes of the distributed transceivers in response to the systempsilas changing knowledge of the channel conditions and subject movements. Subsequently, the analytical results of the locating probability and time-of-arrival (TOA) estimation uncertainty for a large-scale CIN with randomly distributed interrogators are derived based upon the implemented cognitive intelligences. Finally, numerical examples are used to demonstrate the key effects of the proposed cognitions on the system performance

Chapter 2: Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis

Nistor, N., Dascalu, M., Stavarache, L.L., Tarnai, C., & Trausan-Matu, S. (2015). Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. In Y. Li, M. Chang, M. Kravcik, E. Popescu, R. Huang, Kinshuk & N.-S. Chen (Eds.), State-of-the-Art and Future Directions of Smart Learning (Vol. Lecture Notes in Educational Technology, pp. 13–17). Berlin, Germany: Springer-Verlag Singapur

Coccolithophore bloom size variation in response to the regional environment of the subarctic North Atlantic

Several environmental/physical variables derived from satellite and in situ data sets were used to understand the variability of coccolithophore abundance in the subarctic North Atlantic. The 7-yr (1997–2004) time-series analysis showed that the combined effects of high solar radiation, shallow mixed layer depth (<20 m), and increased temperatures explained >89% of the coccolithophore variation. The June 1998 bloom, which was associated with high light intensity, unusually high sea-surface temperature, and a very shallow mixed layer, was found to be one of the most extensive (>995,000 km2) blooms ever recorded. There was a pronounced sea-surface temperature shift in the mid-1990s with a peak in 1998, suggesting that exceptionally large blooms are caused by pronounced environmental conditions and the variability of the physical environment strongly affects the spatial extent of these blooms. Consequently, if the physical environment varies, the effects of these blooms on the atmospheric and oceanic environment will vary as well.

The response of phytoplankton to climate variability associated with the North Atlantic Oscillation

Inter-annual variability in the timing of phytoplankton spring bloom and phytoplankton community structure in the central North Atlantic Ocean was quantified using ocean color data and continuous plankton recorder (CPR) data. This variability was related to the North Atlantic Oscillation using correlation analysis and multivariate auto-regression models. The initiation of the spring bloom derived from CPR phytoplankton color index data is similar to that derived from satellite chlorophyll, and exhibits a nominal correlation with the sea surface temperature (SST) and the North Atlantic Oscillation (NAO). The extrapolated spring bloom timing suggested later initiation of blooms in the mid-1980s and earlier initiation of blooms in the 1990s. The climatological phytoplankton community structure in the central North Atlantic is dominated by diatoms, except for a shift in community composition favoring dinoflagellates in August. The ratio of diatoms to total phytoplankton abundance and the ratio of dinoflagellates to total phytoplankton abundance are both closely correlated with the NAO and SST. The extended time series of phytoplankton community structure between 1985 and 2009, deduced from the time series of SST and NAO over the same interval, showed a decadal shift away from diatoms towards dinoflagellates. The linkages between the NAO, and changes in stratification and phytoplankton processes occur over a larger scale than previously observed.

Are jellyfish increasing in response to ocean acidification?

Ocean acidification may negatively affect calcifying plankton, opening ecological space for non-calcifying species. Recently, a study of climate-forcing of jellyfish reported the first analysis suggesting that there were more jellyfish (generally considered a noncalcifying group) when conditions were more acidic (lower pH) from one area within the North Sea. We examine this suggestion for a number of areas in the North Sea and beyond in the Northeast Atlantic using coelenterate records from the Continuous Plankton Recorder and pH data from the International Council for the Exploration of the Sea for the period 1946-2003. We could find no significant relationships between jellyfish abundance and acidic conditions in any of the regions investigated. We conclude that the role of pH in structuring zooplankton communities in the North Sea and further afield at present is tenuous.

Development and validation of a molecular technique for the analysis of archived formalin-preserved phytoplankton samples permits retrospective assessment of Emiliania huxleyi communities

The coccolithophores, particularly the species Emiliania huxleyi (Lohmann) Hay & Mohler, account for the bulk of global calcium carbonate production and as such play a fundamental role in global CO2 cycling and the carbonate chemistry of the oceans. To evaluate the response of this functional group to the effects of climate change, we undertook a feasibility study to determine whether a retrospective approach could be used on archived coccolithophore datasets. We demonstrate for the first time a technique for the extraction of E. huxleyi nucleic acids from archived formalin-fixed samples of the long-term Continuous Plankton Recorder. Molecular analysis of a nine year old formalin-fixed sample reveals the presence of a diverse population of E. huxleyi genotypes within a developing coccolithophore bloom. In addition, E. huxleyi sequences were amplified from a number of formalin-fixed samples, the earliest of which was collected in August 1972. This molecular assay promises the possibility of studying global variations in the distribution and genetic make-up of E. huxleyi communities over extensive periods of time. (c) 2008 Elsevier B.V. All rights reserved.

1H NMR metabolomics reveals contrasting response by male and female mussels exposed to reduced seawater pH, increased temperature and a pathogen

Human activities are fundamentally altering the chemistry of the world's oceans. Ocean acidification (OA) is occurring against a background of warming and an increasing occurrence of disease outbreaks, posing a significant threat to marine organisms, communities, and ecosystems. In the current study, (1)H NMR spectroscopy was used to investigate the response of the blue mussel, Mytilus edulis, to a 90-day exposure to reduced seawater pH and increased temperature, followed by a subsequent pathogenic challenge. Analysis of the metabolome revealed significant differences between male and female organisms. Furthermore, males and females are shown to respond differently to environmental stress. While males were significantly affected by reduced seawater pH, increased temperature, and a bacterial challenge, it was only a reduction in seawater pH that impacted females. Despite impacting males and females differently, stressors seem to act via a generalized stress response impacting both energy metabolism and osmotic balance in both sexes. This study therefore has important implications for the interpretation of metabolomic data in mussels, as well as the impact of environmental stress in marine invertebrates in general.

Potential impacts of climate change on the primary production of regional seas: A comparative analysis of five European seas

Regional seas are potentially highly vulnerable to climate change, yet are the most directly societally important regions of the marine environment. The combination of widely varying conditions of mixing, forcing, geography (coastline and bathymetry) and exposure to the open-ocean makes these seas subject to a wide range of physical processes that mediates how large scale climate change impacts on these seas’ ecosystems. In this paper we explore the response of five regional sea areas to potential future climate change, acting via atmospheric, oceanic and terrestrial vectors. These include the Barents Sea, Black Sea, Baltic Sea, North Sea, Celtic Seas, and are contrasted with a region of the Northeast Atlantic. Our aim is to elucidate the controlling dynamical processes and how these vary between and within these seas. We focus on primary production and consider the potential climatic impacts on: long term changes in elemental budgets, seasonal and mesoscale processes that control phytoplankton’s exposure to light and nutrients, and briefly direct temperature response. We draw examples from the MEECE FP7 project and five regional model systems each using a common global Earth System Model as forcing. We consider a common analysis approach, and additional sensitivity experiments. Comparing projections for the end of the 21st century with mean present day conditions, these simulations generally show an increase in seasonal and permanent stratification (where present). However, the first order (low- and mid-latitude) effect in the open ocean projections of increased permanent stratification leading to reduced nutrient levels, and so to reduced primary production, is largely absent, except in the NE Atlantic. Even in the two highly stratified, deep water seas we consider (Black and Baltic Seas) the increase in stratification is not seen as a first order control on primary production. Instead, results show a highly heterogeneous picture of positive and negative change arising from complex combinations of multiple physical drivers, including changes in mixing, circulation and temperature, which act both locally and non-locally through advection.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at × 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 × 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.