Optimized Characterization of Thermoelectric Generators for Automotive Application

New developments in the field of thermoelectric materials bring the prospect of consumer devices for recovery of some of the waste heat from internal combustion engines closer to reality. Efficiency improvements are expected due to the development of high-temperature thermoelectric generators (TEG). In contrast to already established radioisotope thermoelectric generators, the temperature difference in automotive systems is not constant, and this imposes a set of specific requirements on the TEG system components. In particular, the behavior of the TEGs and interface materials used to link the heat flow from the heat source through the TEG to the heat sink must be examined. Due to the usage patterns of automobiles, the TEG will be subject to cyclic thermal loads, which leads to module degradation. Additionally, the automotive TEG will be exposed to an inhomogeneous temperature distribution, leading to inhomogeneous mechanical loads and reduced system efficiency. Therefore, a characterization rig is required to allow determination of the electrical, thermal, and mechanical properties of such high-temperature TEG systems. This paper describes a measurement setup using controlled adjustment of cold-side and warm-side temperatures as well as controlled feed-in of electrical power for evaluation of TEGs for application in vehicles with combustion engines. The temperature profile in the setup can be varied to simulate any vehicle usage pattern, such as the European standard driving cycle, allowing the power yield of the TEGs to be evaluated for the chosen cycle. The spatially resolved temperature distribution of a TEG system can be examined by thermal imaging. Hotspots or cracks on thermocouples of the TEGs and the thermal resistance of thermal interface materials can also be examined using this technology. The construction of the setup is briefly explained, followed by detailed discussion of the experimental results.     

SVM-based validation of motor unit potential trains extracted by EMG signal decomposition

Motor unit potential trains (MUPTs) extracted via electromyographic (EMG) signal decomposition can aid in the diagnosis of neuromuscular disorders and the study of the neural control of movement, but only if they are valid. In this paper, support vector machine (SVM)-based supervised classifiers are proposed to estimate the validity of extracted MUPTs. The classifiers use either the MU firing pattern or the MUP shape consistency of an MUPT, or both, to estimate its validity. The developed classifiers estimate the class label of an MUPT (i.e., valid/invalid) and a degree of support for the decision being made. A single SVM that estimates the validity of a given MUPT using extracted MU firing pattern and MUP shape features was investigated. In addition, the effectiveness of multiclassifier techniques which estimate the overall validity of a train by fusing the MU firing pattern and MUP shape validity of a given MUPT, determined separately by two distinct SVMs, was also investigated. Training based only on simulated data showed robust classification performance of the several multiclassifier methods when tested using both simulated and real test data. Of the methods studied, the multiclassifier constructed using trainable logistic regression to aggregate base classifier outputs had the best performance. Assuming 12.7% of extracted MUPTs are on average invalid, the estimated accuracy for this method in correctly categorizing MUPTs extracted during decomposition was 99.4% and 98.8% for simulated and real data, respectively.     

UNICORE 6 — Recent and Future Advancements

UNICORE is a European Grid Technology with more than 10 years of history. Originating from the Supercomputing domain, the latest version UNICORE 6 has turned into a general-purpose Grid technology that follows established standards and offers a rich set of features to its users. The paper starts with an architectural insight into UNICORE 6, highlighting the workflow features, standards and the different clients. Next, the current state of advancement is presented by describing recent developments. The paper closes with an outlook on future planned developments.     

The Effects of Petroleum Coke Properties on Carbon Anode Quality

Comprehensive bench-scale testing of the effects of calcined coke on the properties ofprebaked anodes for aluminum smelting cells has revealed correlations between coke and anode properties. Extensive measurements of the physical properties of coke as well as impurities, determinations of performance-indicative anode properties, and correlation by regression analyses provided statistically significant relationships which can generally be explained in terms of reasonable chemical and physical interactions.     

A Hybrid Decoupled Power Flow Method for Balanced Power Distribution Systems

This paper proposes a hybrid decoupled power flow method for balanced power distribution systems with distributed generation sources.The method formulates the power flow equations in active power and reactive power decoupled form with polar coordinates.Second-order terms are included in the active power mismatch iteration,and constant Jacobian and Hessian matrices are used.A hybrid direct and indirect solution technique is used to achieve efficiency and robustness of the algorithm.Active power correction is solved by means of a sparse lower triangular and upper triangular(LU) decomposition algorithm with partial pivoting,and the reactive power correction is solved by means of restarted generalized minimal residual algorithm with an incomplete LU pre-conditioner.Typical distribution generation models and distribution load models are included.The impact of zero-impedance branches is explicitly modeled through reconfiguring of the adjacent branches with impedances.Numerical examples on a sample distribution system with widespread photovoltaic installations are given to demonstrate the effectiveness of the proposed method.     

2.5D Quantitative Millimeter Wave Imaging of a Hidden Object on a Simplified Human Body Model Using Value Picking Regularization

In this contribution, the authors provide a proof of principle for quantitative imaging of concealed objects on the human body using millimeter waves. A two-and-a-half-dimensional (2.5D) quantitative millimeter wave imaging algorithm is applied to reconstruct a hidden dielectric object on a clothed simplified human body model. At millimeter wave frequencies, the incident field is typically a fully three-dimensional (3D) Gaussian beam, illuminating only a limited spot on the body. Due to the large dimensions of the human body in terms of wavelengths, a 3D discretization is hardly feasible. Therefore, it is assumed that the electromagnetic properties of the body do not significantly change within the illuminated spot, along the longitudinal direction of a person. Hence, only the cross-section of a human body model is discretized. This 2.5D assumption however is still not sufficient to reduce the forward problem to a feasible size. Therefore, a priori knowledge on the illumination and on the scattering properties of the clothed human body is used to deduce a simplified model to describe the cross-section of the clothed human abdomen. The complex permittivity profile of a small dielectric object, hidden underneath clothing and representing some type of explosive, is reconstructed. The complex permittivity profiles of all other scatterers are assumed to be known. The presented quantitative inverse scattering algorithm is based on a Newton-type optimization, combined with an approximate line search and regularized by applying Stepwise Relaxed Value Picking regularization. The input data of the quantitative inverse scattering problem are synthetic scattering data since the authors are not aware of any amplitude and phase measurement data for concealed weapon detection yet made available to the inversion community at these high frequencies.     

A two-stage capacitive-feedback differencing amplifier for temporal contrast IR sensors

This article presents a small-area, ultra low-power, low-mismatch differencing transient amplifier for ROIC pixels of micro-bolometer based temporal contrast IR sensors. The two-stage capacitive-feedback amplifier works in the sub-threshold domain, has a voltage gain of 46 dB, a 3 dB bandwidth of about 10 kHz and consumes 85 nW of static power. The amplifier circuit has been fabricated in a 0.35 μm standard CMOS process and consumes less than 2000 μm² of silicon area, enabling a square pixel size of 50 × 50 μm for the IR sensor array.     

Autonomic Self‐Repairing Glassy Materials

A new process that enables glassy materials to self‐repair from mechanical damage is presented in this paper. Contrary to intrinsic self‐healing, which involves overheating to enable crack healing by glass softening, this process is based on an extrinsic effect produced by vanadium boride (VB) particles dispersed within the glass matrix. Self‐repair is obtained through the oxidation of VB particles, and thus without the need to increase the operating temperature. The VB healing agent is selected for its capacity to oxidize at a lower temperature than the softening point of the glass. Thermogravimetric analyses indeed show that VB oxidation is rapid and occurs below the glass transition temperature. Solid‐state nuclear magnetic resonance spectroscopy indicates that VB is oxidized into V₂O₅ and B₂O₃, which enable the local formation of glass. The autonomic self‐healing effect is demonstrated by an in situ experiment visualized using an environmental scanning electron microscope. It is shown that a crack could be healed by the VB oxidation products.     

New Alternatives to the Estimation Problem in Hardware-Software Codesign of Complex Embedded Systems: The H.261 Video Co-dec Case Study

As Codesign problems become larger and more realistic, the required time to estimate their solutions turns into an important bottleneck. This paper presents a new approach to improve the traditional estimation techniques, in order to avoid this drawback. The presented method has been successfully tested on a large experimental benchmark, attaining quality levels close to those provided by the Synopsys Behavioral Compiler. Finally, a case study based on the standard H.261 video co-dec is described, proving the convenience of the technique on real-life situations. The obtained results show a significant improvement in the process time, while keeping the good precision and fidelity levels that the traditional estimation models usually offer.