Computational approach for reliable and robust system-in-package design

A computational modelling approach integrated with optimisation and statistical methods that can aid the development of reliable and robust electronic packages and systems is presented. The design for reliability methodology is demonstrated for the design of a SiP structure. In this study the focus is on the procedure for representing the uncertainties in the package design parameters, their impact on reliability and robustness of the package design and how these can be included in the design optimisation modelling framework. The analysis of thermo-mechanical behaviour of the package is conducted using non-linear transient finite element simulations. Key system responses of interest, the fatigue life-time of the lead-free solder interconnects and warpage of the package, are predicted and used subsequently for design purposes. The design tasks are to identify the optimal SiP designs by varying several package input parameters so that the reliability and the robustness of the package are improved and in the same time specified performance criteria are also satisfied

Introduction to the BASIN Special Issue: State of art, past present a view to the future

Marine ecosystems are complex networks of organisms interacting either directly or indirectly while under the influence of the physical and chemical properties of the medium they inhabit. The interplay between these biological agents and their abiotic environment results in complex non-linear responses to individual and multiple stressors, influenced by feedbacks between these organisms and their environment. These ecosystems provide key services that benefit humanity such as food provisioning via the transfer of energy to exploited fish populations or climate regulation via the sinking, subsequent mineralization and ultimately storage of carbon in the ocean interior. These key characteristics or emergent features of marine ecosystems are subject to rapid change (e.g. regime shifts; Alheit et al., 2005 and Scheffer et al., 2009), with outcomes that are largely unpredictable in a deterministic sense. The North Atlantic Ocean is host to a number of such systems which are collectively being influenced by the unique physical and chemical features of this ocean basin, such as the Atlantic Meridional Overturning Circulation (AMOC), the basin’s ventilation with the Arctic Ocean, the dynamics of heat transport via the Gulf Stream and the formation of deep water at high latitudes. These features drive the solubility and biological pumps and support the production and environments that results in large exploited fish stocks. Our knowledge of its functioning as a coupled system, and in particular how it will respond to change, is still limited despite the scientific effort exerted over more than 100 years. This is due in part to the difficulty of providing synoptic overviews of a vast area, and to the fact that most fieldwork provides only snapshots of the complex physical, chemical and biological processes and their interactions. These constraints have in the past limited the development of a mechanistic understanding of the basin as a whole, and thus of the services it provides.

Modelling and Prediction of NOx Emission in a Coal-Fired Power Generation Plant

In this paper NOx emissions modelling for real-time operation and control of a 200 MWe coal-fired power generation plant is studied. Three model types are compared. For the first model the fundamentals governing the NOx formation mechanisms and a system identification technique are used to develop a grey-box model. Then a linear AutoRegressive model with eXogenous inputs (ARX) model and a non-linear ARX model (NARX) are built. Operation plant data is used for modelling and validation. Model cross-validation tests show that the developed grey-box model is able to consistently produce better overall long-term prediction performance than the other two models.

Integration of shading and texture cues: testing the linear model

One of the first attempts to develop a formal model of depth cue integration is to be found in Maloney and Landy's (1989) "human depth combination rule". They advocate that the combination of depth cues by the visual sysetem is best described by a weighted linear model. The present experiments tested whether the linear combination rule applies to the integration of texture and shading. As would be predicted by a linear combination rule, the weight assigned to the shading cue did vary as a function of its curvature value. However, the weight assigned to the texture cue varied systematically as a function of the curvature value of both cues. Here we descrive a non-linear model which provides a better fit to the data. Redescribing the stimuli in terms of depth rather than curvature reduced the goodness of fit for all models tested. These results support the hypothesis that the locus of cue integration is a curvature map, rather than a depth map. We conclude that the linear comination rule does not generalize to the integration of shading and texture, and that for these cues it is likely that integration occurs after the recovery of surface curvature.

Vision and reality: community involvement in Irish urban regeneration

This article examines the processes and outcomes of community involvement in six Irish urban regeneration case studies, three in Dublin and three in Belfast. The findings are part of a wider study using a Complex Adaptive Systems perspective to analyse public sector decision making. Key points included: (1) the community ‘vision’ of the regeneration as an emergent property, which converged towards the vision held by the implementing agencies in the four most successful programmes; and (2) the identification of three features that contribute to non-linear (unpredictable) behaviour: a history of community involvement; the availability of resources; and the intervention of key individuals at crisis points.

Geometric bonding effects in the X2A1, A2∑+u, and B2IIg states of Li2F

Published ab-initio and pseudopotential calculations for the dialkali halide systems suggest that the preferred co-linear geometry is for the metal to approach the metal end of the alkali halide. Here, ab-initio calculations on the Li2F system reveal that the well depth on the halide side in this radical is much deeper and is a local saddle-point associated with the ionic non-linear global minima. Although many features of the pseudopotential surfaces are confirmed, significant differences are apparent including the existence of a linear excited state instead of a triangular one, a considerably deeper global minimum some 50% lower in energy and a close approach between the X2A1 and the states, with the minimum 87 kJ mol-1 below the ground state asymptote. All the results can be rationalised as the avoided crossings between a long range, covalent potential dominant within the LiLiF geometry and an ionic state that forms the global minimum. Calculations on the 3rd 2A' potential indicate that even for Li + LiF collisions at ultracold temperatures the collision dynamics could involve as many as three electronic states.

Application of auto-associative neural networks to transient fault detection in an IC engine

The tailpipe emissions from automotive engines have been subject to steadily reducing legislative limits. This reduction has been achieved through the addition of sub-systems to the basic four-stroke engine which thereby increases its complexity. To ensure the entire system functions correctly, each system and / or sub-systems needs to be continuously monitored for the presence of any faults or malfunctions. This is a requirement detailed within the On-Board Diagnostic (OBD) legislation. To date, a physical model approach has been adopted by me automotive industry for the monitoring requirement of OBD legislation. However, this approach has restrictions from the available knowledge base and computational load required. A neural network technique incorporating Multivariant Statistical Process Control (MSPC) has been proposed as an alternative method of building interrelationships between the measured variables and monitoring the correct operation of the engine. Building upon earlier work for steady state fault detection, this paper details the use of non-linear models based on an Auto-associate Neural Network (ANN) for fault detection under transient engine operation. The theory and use of the technique is shown in this paper with the application to the detection of air leaks within the inlet manifold system of a modern gasoline engine whilst operated on a pseudo-drive cycle. Copyright © 2007 by ASME.

Plant-wide predictive control for a thermal power plant based on a physical plant model

A constrained non-linear, physical model-based, predictive control (NPMPC) strategy is developed for improved plant-wide control of a thermal power plant. The strategy makes use of successive linearisation and recursive state estimation using extended Kalman filtering to obtain a linear state-space model. The linear model and a quadratic programming routine are used to design a constrained long-range predictive controller One special feature is the careful selection of a specific set of plant model parameters for online estimation, to account for time-varying system characteristics resulting from major system disturbances and ageing. These parameters act as nonstationary stochastic states and help to provide sufficient degrees-of-freedom to obtain unbiased estimates of controlled outputs. A 14th order non-linear plant model, simulating the dominant characteristics of a 200 MW oil-fired pou er plant has been used to test the NPMPC algorithm. The control strategy gives impressive simulation results, during large system disturbances and extremely high rate of load changes, right across the operating range. These results compare favourably to those obtained with the state-space GPC method designed under similar conditions.

Amplitude banded RLS approach to time variant channel equalization

This paper proposes a non-linear adaptive algorithm, the amplitude banded RLS (ABRLS) algorithm, as an adaptation procedure for time variant channel equalizers. In the ABRLS algorithm, a coefficient matrix is updated based on the amplitude level of the received sequence. To enhance the capability of tracking for the ABRLS algorithm, a parallel adaptation scheme is utilized which involves the structures of decision feedback equalizer (DFE). Computer simulations demonstrate that the novel ABRLS based equalizer provides a significant improvement relative to the conventional RLS DFE on a rapidly time variant communication channel.

Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

An Analytical Study of Surplus Value using a Value Driven Design Methodology

People are now becoming more environmentally aware and as a consequence of this, industries such as the aviation industry are striving to design more environmentally friendly products. To achieve this, the current design methodologies must be modified to ensure these issues are considered from product conception through to disposal. This paper discusses the environmental problems in relation to the aviation industry and highlights some logic for making the change from the traditional Systems Engineering approach to the recent design paradigm known as Value Driven Design. Preliminary studies have been undertaken to aid in the understanding of this methodology and the existing surplus value objective function. The main results from the work demonstrate that surplus value works well bringing disparate issues such as manufacture and green taxes together to aid decision making. Further, to date studies on surplus value have used simple sensitivity analysis, but deeper consideration shows non-linear interactions between some of the variables and further work will be needed to fully account for complex issues such as environmental impact and taxes.

An Energy Conserving Finite Difference Scheme for Simulation of Collisions

Nonlinear phenomena play an essential role in the sound production process of many musical instruments. A common source of these effects is object collision, the numerical simulation of which is known to give rise to stability
issues. This paper presents a method to construct numerical schemes that conserve the total energy in simulations of one-mass systems involving collisions, with no conditions imposed on any of the physical or numerical parameters.
This facilitates the adaptation of numerical models to experimental data, and allows a more free parameter adjustment in sound synthesis explorations. The energy preservedness of the proposed method is tested and demonstrated though several examples, including a bouncing ball and a non-linear oscillator, and implications regarding the wider applicability are discussed.

Parameter estimation and equation formulation in Business Dynamics

System Dynamics enables modelling and simulation of highly non-linear feedback systems to predict future system behaviour. Parameter estimation and equation formulation are techniques in System Dynamics, used to retrieve the values of parameters or the equations for ?ows and/or variables. These techniques are crucial for the annotations and thereafter the simulation. This paper critically examines existing and well established approaches in parameter estimation and equation formulation along with their limitations, identifying performance gaps as well as providing directions for potential future research.

A New Principal Curve Algorithm for Nonlinear Principal Component Analysis

This paper emerged from work supported by EPSRC grant GR/S84354/01 and proposes a method of determining principal curves, using spline functions, in principal component analysis (PCA) for the representation of non-linear behaviour in process monitoring. Although principal curves are well established, they are difficult to implement in practice if a large number of variables are analysed. The significant contribution of this paper is that the proposed method has minimal complexity, assuming simple spline geometry, thus enabling efficient computation. The paper provides a foundation for further work where multiple curves may be required to represent underlying non-linear information in complex data.

Implementation of a non-orthogonal model for the finite element simulation of textile composite draping

In the pursuit of producing high quality, low-cost composite aircraft structures, out-of-autoclave manufacturing processes for textile reinforcements are being simulated with increasing accuracy. This paper focuses on the continuum-based, finite element modelling of textile composites as they deform during the draping process. A non-orthogonal constitutive model tracks yarn orientations within a material subroutine developed for Abaqus/Explicit, resulting in the realistic determination of fabric shearing and material draw-in. Supplementary material characterisation was experimentally performed in order to define the tensile and non-linear shear behaviour accurately. The validity of the finite element model has been studied through comparison with similar research in the field and the experimental lay-up of carbon fibre textile reinforcement over a tool with double curvature geometry, showing good agreement.