A Novel Magnetic Hardening Mechanism for Nd-Fe-B Permanent Magnets Based on Solid-State Phase Transformation

Permanent magnets based on neodymium-iron-boron (Nd-Fe-B) alloys provide the highest performance and energy density, finding usage in many high-tech applications. Their magnetic performance relies on the intrinsic properties of the hard-magnetic Nd₂Fe₁₄B phase combined with control over the microstructure during production. In this study, a novel magnetic hardening mechanism is described in such materials based on a solid-state phase transformation. Using modified Nd-Fe-B alloys of the type Nd₁₆Fe_bal-x-y-zCo_xMo_yCu_zB₇ for the first time it is revealed how the microstructural transformation from the metastable Nd₂Fe₁₇B_x phase to the hard-magnetic Nd₂Fe₁₄B phase can be thermally controlled, leading to an astonishing increase in coercivity from ≈200 kAm⁻¹ to almost 700 kAm⁻¹. Furthermore, after thermally treating a quenched sample of Nd₁₆Fe₅₆Co₂₀Mo₂Cu₂B₇, the presence of Mo leads to the formation of fine FeMo₂B₂ precipitates, in the range from micrometers down to a few nanometers. These precipitates are responsible for the refinement of the Nd₂Fe₁₄B grains and so for the high coercivity. This mechanism can be incorporated into existing manufacturing processes and can prove to be applicable to novel fabrication routes for Nd-Fe-B magnets, such as additive manufacturing.     

Special issue on information systems quality management in practice

Software Quality Journal -     

Nanocrystalline Nd–Fe–B Anisotropic Magnets by Flash Spark Plasma Sintering

Flash spark plasma sintering (flash SPS) is an attractive method to obtain Nd–Fe–B magnets with anisotropic magnetic properties when starting from melt-spun powders. Compared to the benchmark processing route via hot pressing with subsequent die upsetting, flash SPS promises electroplasticity as an additional deformation mechanism and reduced tool wear, while maximizing magnetic properties by tailoring the microstructure—fully dense and high texture. A detailed parameter study is conducted to understand the influence of Flash SPS parameters on the densification and magnetic properties of commercial MQU-F powder. It is revealed that the presintering conditions and preheating temperature before applying the power pulse play a major role for tailoring grain size and texture in the case of hot deformation via Flash SPS. Detailed microstructure and magnetic domain evaluation disclose the texture enhancement with increasing flash SPS temperature at the expense of coercivity. The best compromise between remanence and coercivity (1.37 T and 1195 kA m⁻¹, respectively) is achieved through a combination of presintering at 500 °C for 120 s and preheating temperature of 600 °C, resulting in a magnet with energy product (BH)_max of 350 kJm⁻³. These findings show the potential of flash SPS to obtain fully dense anisotropic nanocrystalline magnets with high magnetic performance.     

Robust solutions to Stackelberg games: Addressing bounded rationality and limited observations in human cognition

How do we build algorithms for agent interactions with human adversaries? Stackelberg games are natural models for many important applications that involve human interaction, such as oligopolistic markets and security domains. In Stackelberg games, one player, the leader, commits to a strategy and the follower makes her decision with knowledge of the leader's commitment. Existing algorithms for Stackelberg games efficiently find optimal solutions (leader strategy), but they critically assume that the follower plays optimally. Unfortunately, in many applications, agents face human followers (adversaries) who — because of their bounded rationality and limited observation of the leader strategy — may deviate from their expected optimal response. In other words, human adversaries' decisions are biased due to their bounded rationality and limited observations. Not taking into account these likely deviations when dealing with human adversaries may cause an unacceptable degradation in the leader's reward, particularly in security applications where these algorithms have seen deployment. The objective of this paper therefore is to investigate how to build algorithms for agent interactions with human adversaries.To address this crucial problem, this paper introduces a new mixed-integer linear program (MILP) for Stackelberg games to consider human adversaries, incorporating: (i) novel anchoring theories on human perception of probability distributions and (ii) robustness approaches for MILPs to address human imprecision. Since this new approach considers human adversaries, traditional proofs of correctness or optimality are insufficient; instead, it is necessary to rely on empirical validation. To that end, this paper considers four settings based on real deployed security systems at Los Angeles International Airport (Pita et al., 2008 [35]), and compares 6 different approaches (three based on our new approach and three previous approaches), in 4 different observability conditions, involving 218 human subjects playing 2960 games in total. The final conclusion is that a model which incorporates both the ideas of robustness and anchoring achieves statistically significant higher rewards and also maintains equivalent or faster solution speeds compared to existing approaches.     

A new discretized Lyapunov–Krasovskii functional for stability analysis and control design of time‐delayed TS fuzzy systems

This paper proposes a new Lyapunov–Krasovskii functional to cope with stability analysis and control design for time‐delay nonlinear systems modeled in the Takagi–Sugeno (TS) fuzzy form. The delay‐dependent conditions are formulated as linear matrix inequalities (LMIs), solvable through several numerical tools. By using the Gu's discretization technique and by employing an appropriated fuzzy functional, less conservative conditions are obtained. Numerical results illustrate the efficiency of the proposed methods. Copyright © 2010 John Wiley & Sons, Ltd.     

Information fusion for automotive applications – An overview

This article focusses on the fusion of information from various automotive sensors like radar, video, and lidar for enhanced safety and traffic efficiency. Fusion is not restricted to data from sensors onboard the same vehicle but vehicular communication systems allow to propagate and fuse information with sensor data from other vehicles or from the road infrastructure as well. This enables vehicles to perceive information from regions that are hardly accessible otherwise and represents the basis for cooperative driving maneuvers. While the Bayesian framework builds the basis for information fusion, automobile environments are characterized by their a priori unknown topology, i.e., the number, type, and structure of the perceived objects is highly variable. Multi-object detection and tracking methods are a first step to cope with this challenge. Obviously, the existence or non-existence of an object is of paramount importance for safe driving. Such decisions are highly influenced by the association step that assigns sensor measurements to object tracks. Methods that involve multiple sequences of binary assignments are compared with soft-assignment strategies. Finally, fusion based on finite set statistics that (theoretically) avoid an explicit association are discussed.     

Learning a generic 3D face model from 2D image databases using incremental Structure-from-Motion

Over the last decade 3D face models have been extensively used in many applications such as face recognition, facial animation and facial expression analysis. 3D Morphable Models (MMs) have become a popular tool to build and fit 3D face models to images. Critical to the success of MMs is the ability to build a generic 3D face model. Major limitations in the MMs building process are: (1) collecting 3D data usually involves the use of expensive laser scans and complex capture setups, (2) the number of available 3D databases is limited, and typically there is a lack of expression variability and (3) finding correspondences and registering the 3D model is a labor intensive and error prone process.