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Characterization of NiTi Shape Memory Damping Elements designed for Automotive Safety Systems
(2014)
Actuator elements made of NiTi shape memory material are more and more known in industry because of their unique properties. Due to the martensitic phase change, they can revert to their original shape by heating when subjected to an appropriate treatment. This thermal shape memory effect (SME) can show a significant shape change combined with a considerable force. Therefore such elements can be used to solve many technical tasks in the field of actuating elements and mechatronics and will play an increasing role in the next years, especially within the automotive technology, energy management, power, and mechanical engineering as well as medical technology. Beside this thermal SME, these materials also show a mechanical SME, characterized by a superelastic plateau with reversible elongations in the range of 8%. This behavior is based on the building of stress-induced martensite of loaded austenite material at constant temperature and facilitates a lot of applications especially in the medical field. Both SMEs are attended by energy dissipation during the martensitic phase change. This paper describes the first results obtained on different actuator and superelastic NiTi wires concerning their use as damping elements in automotive safety systems. In a first step, the damping behavior of small NiTi wires up to 0.5 mm diameter was examined at testing speeds varying between 0.1 and 50 mm/s upon an adapted tensile testing machine. In order to realize higher testing speeds, a drop impact testing machine was designed, which allows testing speeds up to 4000 mm/s. After introducing this new type of testing machine, the first results of vertical-shock tests of superelastic and electrically activated actuator wires are presented. The characterization of these high dynamic phase change parameters represents the basis for new applications for shape memory damping elements, especially in automotive safety systems.
The problem of vessel collisions or near-collision situations on sea, often caused by human error due to incomplete or overwhelming information, is becoming more and more important with rising maritime traffic. Approaches to supply navigators and Vessel Traffic Services with expert knowledge and suggest trajectories for all vessels to avoid collisions, are often aimed at situations where a single planner guides all vessels with perfect information. In contrast, we suggest a two-part procedure which plans trajectories using a specialised A* and negotiates trajectories until a solution is found, which is acceptable for all vessels. The solution obeys collision avoidance rules, includes a dynamic model of all vessels and negotiates trajectories to optimise globally without a global planner and extensive information disclosure. The procedure combines all components necessary to solve a multi-vessel encounter and is tested currently in simulation and on several test beds. The first results show a fast converging optimisation process which after a few negotiation rounds already produce feasible, collision free trajectories.
Codes over quotient rings of Lipschitz integers have recently attracted some attention. This work investigates the performance of Lipschitz integer constellations for transmission over the AWGN channel by means of the constellation figure of merit. A construction of sets of Lipschitz integers that leads to a better constellation figure of merit compared to ordinary Lipschitz integer constellations is presented. In particular, it is demonstrated that the concept of set partitioning can be applied to quotient rings of Lipschitz integers where the number of elements is not a prime number. It is shown that it is always possible to partition such quotient rings into additive subgroups in a manner that the minimum Euclidean distance of each subgroup is strictly larger than in the original set. The resulting signal constellations have a better performance for transmission over an additive white Gaussian noise channel compared to Gaussian integer constellations and to ordinary Lipschitz integer constellations. In addition, we present multilevel code constructions for the new signal constellations.
This paper proposes a pipelined decoder architecture for generalised concatenated (GC) codes. These codes are constructed from inner binary Bose-Chaudhuri-Hocquenghem (BCH) and outer Reed-Solomon codes. The decoding of the component codes is based on hard decision syndrome decoding algorithms. The concatenated code consists of several small BCH codes. This enables a hardware architecture where the decoding of the component codes is pipelined. A hardware implementation of a GC decoder is presented and the cell area, cycle counts as well as the timing constraints are investigated. The results are compared to a decoder for long BCH codes with similar error correction performance. In comparison, the pipelined GC decoder achieves a higher throughput and has lower area consumption.
Bernstein polynomials on a simplex V are considered. The expansion of a given polynomial p into these polynomials provides bounds for range of p over V. Bounds for the range of a rational function over V can easily be obtained from the Bernstein expansions of the numerator and denominator polynomials of this function. In this paper it is shown that these bounds converge monotonically and linearly to the range of the rational function if the degree of the Bernstein expansion is elevated. If V is subdivided then the convergence is quadratic with respect to the maximum of the diameters of the subsimplices.
Sleep is an important aspect in life of every human being. The average sleep duration for an adult is approximately 7 h per day. Sleep is necessary to regenerate physical and psychological state of a human. A bad sleep quality has a major impact on the health status and can lead to different diseases. In this paper an approach will be presented, which uses a long-term monitoring of vital data gathered by a body sensor during the day and the night supported by mobile application connected to an analyzing system, to estimate sleep quality of its user as well as give recommendations to improve it in real-time. Actimetry and historical data will be used to improve the individual recommendations, based on common techniques used in the area of machine learning and big data analysis.