An experimentally based "bubble' model for clay

In order to extend the Cam clay model an inner kinematically hardening bubble is added in order to match experimentally observed hysteretic response. The new model is found to be quite successful in reproducing patterns of response observed in slow cyclic oedometer and triaxial tests. -from Authors

Transient thermal analysis of power devices based on Fourier-series thermal model

A new thermal model based on Fourier series expansion method has been presented for dynamic thermal analysis on power devices. The thermal model based on the Fourier series method has been programmed in MATLAB SIMULINK and integrated with a physics-based electrical model previously reported. The model was verified for accuracy using a two-dimensional Fourier model and a two-dimensional finite difference model for comparison. To validate this thermal model, experiments using a 600V 50A IGBT module switching an inductive load, has been completed under high frequency operation. The result of the thermal measurement shows an excellent match with the simulated temperature variations and temperature time-response within the power module. ©2008 IEEE.

Model-based influences on humans' choices and striatal prediction errors.

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.

Effective handling of dialogue state in the hidden information state POMDP-based dialogue manager

Effective dialogue management is critically dependent on the information that is encoded in the dialogue state. In order to deploy reinforcement learning for policy optimization, dialogue must be modeled as a Markov Decision Process. This requires that the dialogue statemust encode all relevent information obtained during the dialogue prior to that state. This can be achieved by combining the user goal, the dialogue history, and the last user action to form the dialogue state. In addition, to gain robustness to input errors, dialogue must be modeled as a Partially Observable Markov Decision Process (POMDP) and hence, a distribution over all possible states must be maintained at every dialogue turn. This poses a potential computational limitation since there can be a very large number of dialogue states. The Hidden Information State model provides a principled way of ensuring tractability in a POMDP-based dialogue model. The key feature of this model is the grouping of user goals into partitions that are dynamically built during the dialogue. In this article, we extend this model further to incorporate the notion of complements. This allows for a more complex user goal to be represented, and it enables an effective pruning technique to be implemented that preserves the overall system performance within a limited computational resource more effectively than existing approaches. © 2011 ACM.

Steady-state analytical model for the trench insulated gate bipolar transistor

A steady-state, physically-based analytical model for the Trench Insulated Gate Bipolar Transistor which accounts for a combined PIN diode - PNP transistor carrier dynamics is proposed. Previous models (i.e. PIN model and PNP transistor model) cannot account properly for the carrier dynamics in Trench IGBT since neither the PNP transistor nor the PIN diode effect can be neglected. An optimized Trench IGBT with a large ratio between the accumulation layer and the cell size leads to substantially improved on-state characteristics, which makes the Trench IGBT potentially the most attractive device in the area of high voltage fast switching devices.

Optimal design of Functionally Graded Materials using a procedural model and Particle Swarm Optimization

A new method for the optimal design of Functionally Graded Materials (FGM) is proposed in this paper. Instead of using the widely used explicit functional models, a feature tree based procedural model is proposed to represent generic material heterogeneities. A procedural model of this sort allows more than one explicit function to be incorporated to describe versatile material gradations and the material composition at a given location is no longer computed by simple evaluation of an analytic function, but obtained by execution of customizable procedures. This enables generic and diverse types of material variations to be represented, and most importantly, by a reasonably small number of design variables. The descriptive flexibility in the material heterogeneity formulation as well as the low dimensionality of the design vectors help facilitate the optimal design of functionally graded materials. Using the nature-inspired Particle Swarm Optimization (PSO) method, functionally graded materials with generic distributions can be efficiently optimized. We demonstrate, for the first time, that a PSO based optimizer outperforms classical mathematical programming based methods, such as active set and trust region algorithms, in the optimal design of functionally graded materials. The underlying reason for this performance boost is also elucidated with the help of benchmarked examples. © 2011 Elsevier Ltd. All rights reserved.

Steering manufacturing firms towards service business model innovation

Increasingly, manufacturing firms are turning to services as a new way of creating and capturing value. Despite its potential benefits, many new product-service providers struggle to deploy service activities effectively, not least because they fail to refect the presence of service activities in their performance management systems. This article reports the results of an in-depth case study, which examines how manufacturers can steer the transition towards services. It shows that manufacturing firms need to emphasize two separate but related dimensions of the market performance of service activities: "service adoption," refecting the proportion of customers who purchase the manufacturer's services; and "service coverage," signaling the range of service elements or the comprehensiveness of the service contract that customers opt for. These two indicators, refecting service market performance, should be supplemented with a "complementarity index" designed to disclose whether the relationship between products and services is reinforcing or substitutive. When combined, these indicators allow manufacturing firms to deploy a service-based business model in an integrated and sustainable manner. © 2013 by The Regents of the University of California. All rights reserved.