Zur Treffsicherheit neuerer Festigkeitshypothesen für die mehrachsige Schwingbeanspruchung metallischer Werkstoffe

Accuracy by Using newer Criterions of Strength for the Fatigue Behaviour of Metals under Multiaxial Alternating Load The prediction quality and applicability range of five newer developed approaches for determining the fatigue endurance limit of metallic materials under multiaxial loading conditions are tested by an extensive catalogue of present available experimental results. The discussion is limited to various biaxial states of combined normal and torsional alternating stress with synchronous or out-of-phase amplitudes and superimposed mean stresses. The statistical analysis of the deviations between experimental data (results from fatigue tests with probability of survival of P_s = 50%) and calculated values demonstrates significant differences with respect to the accuracy and validity; therefore and in consideration further aspects, a distinct quality rank of the examined computation methods is clearly indicated. As results of the recent examination can be stated, that in relation to the other failure criterions the “Quadratische Versagenshypothese” (QVH) is preferably recommended for a reliable application.     

FAPbI3‐Based Perovskite Solar Cells Employing Hexyl‐Based Ionic Liquid with an Efficiency Over 20% and Excellent Long‐Term Stability

Formamidinium lead triiodide (FAPbI₃)‐based perovskite materials are of interest for photovoltaics in view of their close‐to‐ideal bandgap, allowing absorption of photons over a broad solar spectrum. However, FAPbI₃‐based materials suffer from a notorious phase transition from the photoactive black phase (α‐FAPbI₃) to nonperovskite yellow phase (δ‐FAPbI₃) under ambient conditions. This transition dramatically reduces light absorbtion, thus, degrading the photovoltaic performance and stability of ensuring solar cells. In this study, 1‐hexyl‐3‐methylimidazolium iodide (HMII) ionic liquid (IL) is employed as an additive for the first time in FAPbI₃ perovskite to overcome the above‐mentioned issues. HMII incorporation facilitates the grain coarsening of FAPbI₃ crystal owing to its high‐polarity and high‐boiling point, which yields liquid domains between neighboring grains to reduce the activation energy of the grain‐boundary migration. As a result, the FAPbI₃ active layer exhibits micron‐sized grains with substantially suppressed parasitic traps with an Urbach energy reduced by 2 meV. Hence, the resulting perovskite solar cell achieves an efficiency of 20.6% with notable increase in open circuit voltage (V_OC) of 80 mV compared with HMII‐free cells (17.1%). More importantly, the HMII‐doped FAPbI₃‐based cells show a striking enhancement in shelf‐stability under high humidity and thermal stress, retaining >80% of their initial efficiencies at 60 ± 10% relative humidity and ≈95% at 65 °C.     

Physiological and subjective evaluation of a human-robot object hand-over task

In the context of task sharing between a robot companion and its human partners, the notions of safe and compliant hardware are not enough. It is necessary to guarantee ergonomic robot motions. Therefore, we have developed Human Aware Manipulation Planner (Sisbot et al., 2010), a motion planner specifically designed for human–robot object transfer by explicitly taking into account the legibility, the safety and the physical comfort of robot motions. The main objective of this research was to define precise subjective metrics to assess our planner when a human interacts with a robot in an object hand-over task. A second objective was to obtain quantitative data to evaluate the effect of this interaction. Given the short duration, the “relative ease” of the object hand-over task and its qualitative component, classical behavioral measures based on accuracy or reaction time were unsuitable to compare our gestures. In this perspective, we selected three measurements based on the galvanic skin conductance response, the deltoid muscle activity and the ocular activity. To test our assumptions and validate our planner, an experimental set-up involving Jido, a mobile manipulator robot, and a seated human was proposed. For the purpose of the experiment, we have defined three motions that combine different levels of legibility, safety and physical comfort values. After each robot gesture the participants were asked to rate them on a three dimensional subjective scale. It has appeared that the subjective data were in favor of our reference motion. Eventually the three motions elicited different physiological and ocular responses that could be used to partially discriminate them.     

Classifier ensemble construction with rotation forest to improve medical diagnosis performance of machine learning algorithms

Improving accuracies of machine learning algorithms is vital in designing high performance computer-aided diagnosis (CADx) systems. Researches have shown that a base classifier performance might be enhanced by ensemble classification strategies. In this study, we construct rotation forest (RF) ensemble classifiers of 30 machine learning algorithms to evaluate their classification performances using Parkinson's, diabetes and heart diseases from literature.While making experiments, first the feature dimension of three datasets is reduced using correlation based feature selection (CFS) algorithm. Second, classification performances of 30 machine learning algorithms are calculated for three datasets. Third, 30 classifier ensembles are constructed based on RF algorithm to assess performances of respective classifiers with the same disease data. All the experiments are carried out with leave-one-out validation strategy and the performances of the 60 algorithms are evaluated using three metrics; classification accuracy (ACC), kappa error (KE) and area under the receiver operating characteristic (ROC) curve (AUC).Base classifiers succeeded 72.15%, 77.52% and 84.43% average accuracies for diabetes, heart and Parkinson's datasets, respectively. As for RF classifier ensembles, they produced average accuracies of 74.47%, 80.49% and 87.13% for respective diseases.RF, a newly proposed classifier ensemble algorithm, might be used to improve accuracy of miscellaneous machine learning algorithms to design advanced CADx systems.     

Polyimides from a Novel Monomer 3,6-Bis(dimethylamino)acridine(p-cymene)dichlororuthenium(II) for a Catalytic Application

Tricyclic heteroaraomatic dye-based monomer containing NMe₂ units, 6-bis(dimethylamino)acridine(p-cymene)dichlororuthenium (II), was used to prepare novel polyimides via a one-stage solution polycondensation due to their stability under a variety of oxidative and reductive conditions. The Ru(II) complex monomer was synthesized starting from [RuCl₂(p-cymene)]₂ and 3,6-bis(dimethylamino)acridine. A series of stable polyimides was synthesized from the Ru(II) complex of 3,6-bis(dimethylamino)acridine and various aromatic dianhyrides. The polymers had inherent viscosities ranging from 1.72 to 2.11 dL/g and were soluble in polar solvents. The glass transition temperatures were 192–278 °C, and the 10% weight loss temperatures were above 503–635 °C. Ruthenium-substituted polyimides were tested for catalytic activity in the furan formation reaction of (Z)-3-methylpent-2-en-4-yn-1-ol. The polymeric catalyst was added to (Z)-3-methylpent-2-en-4-yn-l-ol without a solvent and the pure furan was isolated by distillation under reduced pressure. The conversion of the starting, enynol, was determined by gas chromatography (GC).     

Hydropower Optimization for the Lower Seyhan Basin System in Turkey using dynamic programming

Abstract

Dynamic programming with successive approximation has been used in the past for optimizing multi-reservoir water resources systems. In this study, a State Incremental Dynamic Programming (SIDP) model is developed for energy optimization of multi-reservoir systems. A random file access method is used to generate initial and intermediate data and cope with the curse of dimensionality of dynamic programming. The conventional dynamic programming method is used for each single reservoir to find the initial trajectory of the reservoirs. Then, the computer program developed in the study is applied to the multipurpose-multi-reservoir system in lower Seyhan basin, which comprises six reservoirs, some serial and some parallel. Extended historical flows are used to first maximize firm energy in the critical period, and then total energy over the entire period of flow records. The program is run with 50-year long segments (20 flow scenarios) of the synthetic flow data generated by using the hec-4 generalized computer program to account for the stochastic nature of streamflows. A 20% approximate increase in total energy is obtained by using the developed model for the lower seyhan basin system as compared to that calculated previously by conventional methods.     

Hydropower Optimization for the Lower Seyhan System in Turkey using Dynamic Programming

Abstract

Dynamic programming with successive approximation has been used in the past for optimizing multi-reservoir water resources systems. In this study, the State Incremental Dynamic Programming (SIDP) model is developed for energy optimization of multi-reservoir systems. A random file access method is used for reaching initial and intermediate data to cope with the curse of dimensionality of dynamic programming. A conventional dynamic programming method is used for each single reservoir to find the initial trajectory of the reservoirs. Then, the computer program developed in the study is applied to the multipurpose-multi-reservoir system in Lower Seyhan Basin, which has six reservoirs, some of which are serial and some parallel. First, extended historical flows were used to maximize firm energy in the critical period, and then total energy in the total flows. The program was run with 50-year long segments (20 flow scenarios) of the synthetic flow data generated by using the HEC-4 generalized computer program to take into account the stochastic nature of stream flows. An increment of approximately 20 percent in total energy was obtained by using the model for the Lower Seyhan System, as compared to that calculated previously by conventional methods.