Computational model for prediction of particle degradation during dilute phase pneumatic conveying: the use of a laboratory scale degradation tester for the determination of degradation propensity

The overall objective of this work is to develop a computational model of particle degradation during dilute-phasepneumatic conveying. A key feature of such a model is the prediction of particle breakage due to particle–wall collisions in pipeline bends. This paper presents a method for calculating particle impact degradation propensity under a range of particle velocities and particle sizes. It is based on interpolation on impact data obtained in a new laboratory-scale degradation tester. The method is tested and validated against experimental results for degradation at 90± impact angle of a full-size distribution sample of granulated sugar. In a subsequent work, the calculation of degradation propensity is coupled with a ow model of the solids and gas phases in the pipeline.

Computational model for prediction of particle degradation during dilute-phase pneumatic conveying: modeling of dilute-phase pneumatic conveying

A complete model of particle impact degradation during dilute-phase pneumatic conveying is developed, which combines a degradation model, based on the experimental determination of breakage matrices, and a physical model of solids and gas flow in the pipeline. The solids flow in a straight pipe element is represented by a model consisting of two zones: a strand-type flow zone immediately downstream of a bend, followed by a fully suspended flow region after dispersion of the strand. The breakage matrices constructed from data on 90° angle single-impact tests are shown to give a good representation of the degradation occurring in a pipe bend of 90° angle. Numerical results are presented for degradation of granulated sugar in a large scale pneumatic conveyor.

Solder life prediction in a thermal analysis software environment

This paper describes recent developments made to the stress analysis module within FLOTHERM, extending its capability to handle viscoplastic behavior. It also presents the validation of this approach and results obtained for an SMT resistor as an illustrative example. Lifetime predictions are made using the creep strain energy based models of Darveaux. Comment is made about the applicability of the damage model to the geometry of the joint under study.

Support vector machines for regression and applications to software quality prediction

Software metrics are the key tool in software quality management. In this paper, we propose to use support vector machines for regression applied to software metrics to predict software quality. In experiments we compare this method with other regression techniques such as Multivariate Linear Regression, Conjunctive Rule and Locally Weighted Regression. Results on benchmark dataset MIS, using mean absolute error, and correlation coefficient as regression performance measures, indicate that support vector machines regression is a promising technique for software quality prediction. In addition, our investigation of PCA based metrics extraction shows that using the first few Principal Components (PC) we can still get relatively good performance.

Lifetime prediction for power electronics module substrate mount-down solder interconnect

A numerical modeling method for the prediction of the lifetime of solder joints of relatively large solder area under cyclic thermal-mechanical loading conditions has been developed. The method is based on the Miner's linear damage accumulation rule and the properties of the accumulated plastic strain in front of the crack in large area solder joint. The nonlinear distribution of the damage indicator in the solder joints have been taken into account. The method has been used to calculate the lifetime of the solder interconnect in a power module under mixed cyclic loading conditions found in railway traction control applications. The results show that the solder thickness is a parameter that has a strong influence on the damage and therefore the lifetime of the solder joint while the substrate width and the thickness of the baseplate are much less important for the lifetime

Integrated reliability and prognostics prediction methodology for power electronic modules

The article consists of a PowerPoint presentation on integrated reliability and prognostics prediction methodology for power electronic modules. The areas discussed include: power electronics flagship; design for reliability; IGBT module; design for manufacture; power module components; reliability prediction techniques; failure based reliability; etc.

A framework for state-based time-series analysis and prediction

Time-series analysis and prediction play an important role in state-based systems that involve dealing with varying situations in terms of states of the world evolving with time. Generally speaking, the world in the discourse persists in a given state until something occurs to it into another state. This paper introduces a framework for prediction and analysis based on time-series of states. It takes a time theory that addresses both points and intervals as primitive time elements as the temporal basis. A state of the world under consideration is defined as a set of time-varying propositions with Boolean truth-values that are dependent on time, including properties, facts, actions, events and processes, etc. A time-series of states is then formalized as a list of states that are temporally ordered one after another. The framework supports explicit expression of both absolute and relative temporal knowledge. A formal schema for expressing general time-series of states to be incomplete in various ways, while the concept of complete time-series of states is also formally defined. As applications of the formalism in time-series analysis and prediction, we present two illustrating examples.

Prediction of reinforcement corrosion in concrete and its effects on concrete cracking and strength reduction

Based on extensive research on reinforcing steel corrosion in concrete in the past decades, it is now possible to estimate the effect of the progression of reinforcement corrosion in concrete infrastructure on its structural performance. There are still areas of considerable uncertainty in the models and in the data available, however This paper uses a recently developed model for reinforcement corrosion in concrete to improve the estimation process and to indicate the practical implications. In particular stochastic models are used to estimate the time likely to elapse for each phase of the whole corrosion process: initiation, corrosion-induced concrete cracking, and structural strength reduction. It was found that, for practical flexural structures subject to chloride attacks, corrosion initiation may start quite early in their service life. It was also found that, once the structure is considered to be unserviceable due to corrosion-induced cracking, there is considerable remaining service life before the structure can be considered to have become unsafe. The procedure proposed in the paper has the potential to serve as a rational tool for practitioners, operators, and asset managers to make decisions about the optimal timing of repairs, strengthening, and/or rehabilitation of corrosion-affected concrete infrastructure. Timely intervention has the potential to prolong the service life of infrastructure.

Regime shifts in marine ecosystems: detection prediction and management

Regime shifts are abrupt changes between contrasting, persistent states of any complex system. The potential for their prediction in the ocean and possible management depends upon the characteristics of the regime shifts: their drivers (from anthropogenic to natural), scale (from the local to the basin) and potential for management action (from adaptation to mitigation). We present a conceptual framework that will enhance our ability to detect, predict and manage regime shifts in the ocean, illustrating our approach with three well-documented examples: the North Pacific, the North Sea and Caribbean coral reefs. We conclude that the ability to adapt to, or manage, regime shifts depends upon their uniqueness, our understanding of their causes and linkages among ecosystem components and our observational capabilities.

Causes and prediction of abrupt climate-driven ecosystem shifts in the North Atlantic

Warming of the global climate is now unequivocal and its impact on Earth’ functional units has become more apparent. Here, we show that marine ecosystems are not equally sensitive to climate change and reveal a critical thermal boundary where a small increase in temperature triggers abrupt ecosystem shifts seen across multiple trophic levels. This large-scale boundary is located in regions where abrupt ecosystem shifts have been reported in the North Atlantic sector and thereby allows us to link these shifts by a global common phenomenon. We show that these changes alter the biodiversity and carrying capacity of ecosystems and may, combined with fishing, precipitate the reduction of some stocks of Atlantic cod already severely impacted by exploitation. These findings offer a way to anticipate major ecosystem changes and to propose adaptive strategies for marine exploited resources such as cod in order to minimize social and economic consequences.