Modeling Temperature in Coupled Electrical and Thermal Simulations of the Electroconsolidation® Process

Electroconsolidation® is a process for densifying complex-shaped parts by using electrically conductive particulate solids as a pressure-transmitting medium. The part is immersed in a bed of the particulate medium contained in a die chamber. Sintering temperature is achieved by resistive heating of the medium while applying compaction pressure. The process is capable of ultrahigh temperatures and short cycle times and offers the potential for low processing costs.

Control of the process and selection of process conditions require knowledge of the temperatures within the die. Temperature gradients exist because of the high heating rate and because of variations of density and electrical resistivity of the medium due to the presence of the part. Direct measurement of temperature with thermocouples or other conventional means is impractical because of the high temperatures, high currents, and high pressures that are involved. Therefore, a computer model was developed to predict temperature as a function of time and applied voltage for any location in the die. The computer model is composed of three parts: a geometrical model to approximate the density and resistivity variations in the medium, a finite-element model to calculate the rate of resistive heating within each element, and a finite-difference model to calculate the temperature distribution based on solution of the heat-transfer equations. Predicted temperatures have been shown to be in excellent agreement with measurements, and numerical simulation provided encouraging consistency and reasonably accurate predictions of temperature profiles within the die. The model demonstrated the feasibility of a new process to achieve simultaneous application of pressure and heat to powder densification in Electroconsolidation.     

Controlling the losing probability in a monotone game

We deal with a complex game between Alice and Bob where each contender’s probability of victory grows monotonically by unknown amounts with the resources employed. For a fixed effort on Alice’s part, Bob increases his resources on the basis of the results for each round (victory, tie or defeat) with the aim of reducing the probability of defeat to below a given threshold. We read this goal in terms of computing a confidence interval for the probability of losing and realize that the moves in some contests may bring in an indeterminacy trap: in certain games Bob cannot simultaneously have both a low probability-of-defeat measure and a narrow confidence interval. We use the inferential mechanism called twisting argument to compute the above interval on the basis of two joint statistics. Careful use of such statistics allows us to avoid indeterminacy.     

Computational materials: Multi-scale modeling and simulation of nanostructured materials

The paper provides details on the current approach to multi-scale modeling and simulation of advanced materials for structural applications. Examples are given that illustrate the suggested approaches to predicting the behavior and influencing the design of nanostructured materials such as high-performance polymers, composites, and nanotube-reinforced polymers. Primary simulation and measurement methods applicable to multi-scale modeling are outlined. Key challenges including verification and validation are highlighted and discussed.     

亚齐示范屋与生态技术

亚齐示范屋是在传承印度尼西亚当地住宅传统的基础上，海啸灾区重建的示范性建筑。从当地传统的传承、设计理念及生态技术方面对该示范屋进行了分析、研究，结合我国的情况得出我国生态建筑的发展策略。     

Modeling of a multisector ecological economic system with lags

A model of a diversified ecological economic system with lags is proposed and investigated using sufficient optimality conditions. A turnpike solution of the problem, boundary trajectories, and control switchpoints are found. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 114–122, March–April 2007.     

非线性动态系统“黑箱”建模方法的研究

本文研究弱非线性动态系统“黑箱”建模的理论和方法，并简要给出根据此方法建模的结果。     

KNOWLEDGE-BASED FEATURE DISCOVERY FOR EVALUATION FUNCTIONS

Since Samuel's work on checkers over thirty years ago, much effort has been devoted to learning evaluation functions. However, all such methods are sensitive to the feature set chosen to represent the examples. If the features do not capture aspects of the examples significant for problem solving, the learned evaluation function may be inaccurate or inconsistent. Typically, good feature sets are carefully handcrafted and a great deal of time and effort goes into refining and tuning them. This paper presents an automatic knowledge-based method for generating features for evaluation functions. The feature set is developed iteratively: features are generated, then evaluated, and this information is used to develop new features in turn. Both the contribution of a feature and its computational expense are considered in determining whether and how to develop it further.
This method has been applied to two problem-solving domains: the Othello board game and the domain of telecommunications network management. Empirical results show that the method is able to generate many known features and several novel features and to improve concept accuracy in both domains.     

Discourse cues to deception in the case of multiple receivers

Behavioral cues to deception are instrumental in detecting deception. As one of the primary sources of deception behavior, text has been analyzed at the level of sub-sentence or message but not the discourse of interaction. Additionally, empirical studies on cues to deception in the case of multiple receivers remain nonexistent. To fill these voids, we propose a discourse framework and six hypotheses about deception behaviors in a multi-receiver environment. The deception behaviors are operationalized by discourse features based on an analysis of real-world data. The results of statistical analysis validate the efficacy of discourse features in discriminating deceivers from truth-tellers.     

Human interaction with policy flight simulators

Policy flight simulators are designed for the purpose of exploring alternative management policies at levels ranging from individual organizations to national strategy. This article focuses on how such simulators are developed and on the nature of how people interact with these simulators. These interactions almost always involve groups of people rather than individuals, often with different stakeholders in conflict about priorities and courses of action. The ways in which these interactions are framed and conducted are discussed, as well as the nature of typical results.     

A new approach of audio emotion recognition

A new architecture of intelligent audio emotion recognition is proposed in this paper. It fully utilizes both prosodic and spectral features in its design. It has two main paths in parallel and can recognize 6 emotions. Path 1 is designed based on intensive analysis of different prosodic features. Significant prosodic features are identified to differentiate emotions. Path 2 is designed based on research analysis on spectral features. Extraction of Mel-Frequency Cepstral Coefficient (MFCC) feature is then followed by Bi-directional Principle Component Analysis (BDPCA), Linear Discriminant Analysis (LDA) and Radial Basis Function (RBF) neural classification. This path has 3 parallel BDPCA + LDA + RBF sub-paths structure and each handles two emotions. Fusion modules are also proposed for weights assignment and decision making. The performance of the proposed architecture is evaluated on eNTERFACE’05 and RML databases. Simulation results and comparison have revealed good performance of the proposed recognizer.