Design and analysis of an aging‐aware energy management system for islanded grids using mixed‐integer quadratic programming

The rapid increase of renewable energy sources made coordinated control of the distributed and intermittent generation units a more demanded task. Matching demand and supply is particularly challenging in islanded microgrids. In this study, we have demonstrated a mixed‐integer quadratic programming (MIQP) method to achieve efficient use of sources within an islanded microgrid. A unique objective function involving fuel consumption of diesel generator, degradation in a lithium‐ion battery energy storage system, carbon emissions, load shifting, and curtailment of the renewable sources is constructed, and an optimal operating point is pursued using the MIQP approach. A systematic and extensive methodology for building the objective function is given in a sequential and explicit manner with an emphasis on a novel model‐based battery aging formulation. Performance of the designed system and a sensitivity analysis of resulting battery dispatch, diesel generator usage, and storage aging against a range of optimization parameters are presented by considering real‐world specifications of the Semakau Island, an island in the vicinity of Singapore.     

System-specific static code analyses: a case study in the complex embedded systems domain

In this paper, we are exploring the approach to utilize system-specific static analyses of code with the goal to improve software quality for specific software systems. Specialized analyses, tailored for a particular system, make it possible to take advantage of system/domain knowledge that is not available to more generic analyses. Furthermore, analyses can be selected and/or developed in order to best meet the challenges and specific issues of the system at hand. As a result, such analyses can be used as a complement to more generic code analysis tools because they are likely to have a better impact on (business) concerns such as improving certain software quality attributes and reducing certain classes of failures. We present a case study of a large, industrial embedded system, giving examples of what kinds of analyses could be realized and demonstrate the feasibility of implementing such analyses. We synthesize lessons learned based on our case study and provide recommendations on how to realize system-specific analyses and how to get them adopted by industry.     

Thermodynamic and Experimental Investigations of High-Temperature Refractory Corrosion by Molten Slags

Corrosion mechanisms between MgO refractory substrates and FeNi slags were investigated. The FeNi slags taken into consideration represent a simple synthetically mixed slag with specific oxides and a real slag from a ferroalloy producer. The MgO refractory substrates with the specimens of FeNi slag were heated in a hot-stage microscope at 10 K/min from room temperature to three different temperatures 1573 K, 1723 K, and 1923 K (1300 °C, 1450 °C, and 1650 °C). The experiments were carried out under a controlled gas atmosphere that simulates the relevant process conditions. The corrosion mechanisms of each system were followed by scanning electron microscope analyses. The results obtained showed that slag corrosion dominates, with a pronounced partial dissolution of refractory fines forming Mg-silicates of type forsterite. It was also observed that iron oxide present in the slag diffused into the coarse refractory grains forming magnesiowustite. Finally, the results obtained were compared with those predicted by FACTSAGE software to understand the corrosion mechanisms and draw implications for improving the refractory performance and lifetime.     

Archaeological Arsenical Bronzes and Equilibrium in the As-Cu System

Metallurgical and Materials Transactions B - Understanding the effects of impurities, segregation, undercooling, and solidification velocity is necessary to reconstruct prehistoric As-Cu alloy...     

Selecting creep models using Bayesian methods

The development of creep prediction models has been a field of extensive research and many different models have already been proposed. This paper presents an evaluation method of the prediction quality of creep models for specific experimental data. Within the scope of this paper, the model according to Bockhold and the model according to Heidolf are examined. First, the parameters of the models are identified with respect to existing experimental data. This is done using a sampling based approach of Bayesian updating developed by Ba?ant and Chern. In extension to the method by Ba?ant and Chern, the uncertainty coming from inaccurate measurement data is taken into account in the definition of the likelihood function within the updating algorithm. The more inaccurate the measurements are, the more uncertain the estimated model parameters and model prognoses become. The identification is performed for different short- and long-term creep tests. The intension is not to validate these models intensively, but to evaluate their prognoses for the individually tested creep behavior. The results show that the identifiability of the models?? parameters is different for both models and consequently the models prognoses differ in their uncertainties. Second, the models are evaluated using two different strategies: the stochastic model selection according to MacKay, Beck and Yuen based on the Ockham factor, and a comparison of the uncertainties taking into account parameter and model uncertainties. The results of the evaluation of the creep models differ for various experimental tests. Model Heidolf is more flexible and gives a better fit to the data, however, it fails to predict reliable long-term creep deformations using only short-term measurements compared to model Bockhold. Comparing the evaluation methods, the analysis of uncertainties of the creep prognosis proofs to be more stable than the evaluation using the stochastic model selection.     

Zwitterionic‐Coated “Stealth” Nanoparticles for Biomedical Applications: Recent Advances in Countering Biomolecular Corona Formation and Uptake by the Mononuclear Phagocyte System

Nanoparticles represent highly promising platforms for the development of imaging and therapeutic agents, including those that can either be detected via more than one imaging technique (multi‐modal imaging agents) or used for both diagnosis and therapy (theranostics). A major obstacle to their medical application and translation to the clinic, however, is the fact that many accumulate in the liver and spleen as a result of opsonization and scavenging by the mononuclear phagocyte system. This focused review summarizes recent efforts to develop zwitterionic‐coatings to counter this issue and render nanoparticles more biocompatible. Such coatings have been found to greatly reduce the rate and/or extent of non‐specific adsorption of proteins and lipids to the nanoparticle surface, thereby inhibiting production of the “biomolecular corona” that is proposed to be a universal feature of nanoparticles within a biological environment. Additionally, in vivo studies have demonstrated that larger‐sized nanoparticles with a zwitterionic coating have extended circulatory lifetimes, while those with hydrodynamic diameters of ≤5 nm exhibit small‐molecule‐like pharmacokinetics, remaining sufficiently small to pass through the fenestrae and slit pores during glomerular filtration within the kidneys, and enabling efficient excretion via the urine. The larger particles represent ideal candidates for use as blood pool imaging agents, whilst the small ones provide a highly promising platform for the future development of theranostics with reduced side effect profiles and superior dose delivery and image contrast capabilities.     

Modeling trade-offs in the design of sensor-based event processing infrastructures

Systems for distributed event processing have recently gained increasing attention in a broad range of application domains. This raises the demand for methods to adapt the system design to application-specific needs. Our approach considers (1) trade-offs regarding the hardware infrastructure and (2) trade-offs in the software design. For the underlying model we categorize events along the dimensions of temporal complexity and physical distribution. This yields a categorization of events that drives trade-offs in the infrastructure design. The presented model supports design decisions in dependence on application-specific event properties and design goals.     

Ionic Discotic Liquid Crystals

Ionic discotic liquid crystals are salts of discotic liquid crystals that may display lyotropic and thermotropic mesomorphism. Columnar structures of π-π stacking ionic discotic liquid crystals function not only as anisotropic organic semiconductors, similar to their neutral analogues, but they may also efficiently conduct ions. This combination of electronic and ionic conduction is only one of several unique properties that these materials may display, but their systematic investigation has been limited because of their often complex synthesis, purification, and characterization. However, a comprehensive account of existing reports on ionic discotic liquid crystals is not straightforward, despite their relatively small number, because publications are scattered across different areas of research, such as liquid crystals, ionic liquids, and ionic self-assembly. This review intends to provide a concise but comprehensive overview of the published work on ionic discotic liquid crystals and related compounds and is expected to stimulate further exploration. Highlighted in this review is the mesomorphism of ionic discotic liquid crystals and its dependence on structural changes, which is also the focus of most reported studies. Particular attention was given to the dependence of mesomorphism on the location and types of the charged groups as these are parameters unique to these compounds. Also described are electronic, optical, and other properties of these materials if reported.