To reduce the environmental, economical, and safety consequences of ship collisions, it is compulsory that hull structures of all oil tankers arrange for double sides and bottoms. It is clear that double hulls lead to an increase of crash-worthiness and mitigate the possibility of severe damage in ships body and oil spill. Recently, various studies have been conducted to improve the efficiency of double hulls with adding some granular materials into the space between the two walls. In the current research, the collision of double hull vessels filled with energy absorbing granular materials will be studied on both micro and macro scales. For this purpose, the compaction behavior of granulates will be studied at first using DEM. Then considering a representative volume element (RVE) and homogenization technique, the mechanical properties of the particles will be identified for the continuum model. At the next step, since the granular material must be modeled by different methods in different sub-domains (DEM and FEM), a bridging or coupling must be established in the domains interface using, for example, the Arlequin method. At the end, the collision problem in double hull vessels will be simulated and the effects of influencing parameters can be investigated. Project partners: Prof. M. Dosta (TUHH)

The Characteristic Mode Analysis (CMA) – based on the fundamental works of Harrington and Mautz – is a well-known numerical tool for antenna analysis and design. Within the numerical framework of the method of moments (MoM) the characteristic modes are found by the solution of a weighted matrix eigenvalue equation formulated with the MoM system matrix. The resulting current distributions are the eigencurrents and eigenvalues, respectively. The eigenvalues indicate if the corresponding eigencurrents may store primarily magnetic energy, or electric energy, or if they are “at resonance” and may radiate efficiently if excited. The eigencurrents constitute a set of (orthogonal) modes characteristic to the investigated structure (hence the name) and independent of any excitation. In antenna design inspection of the eigencurrents allows to identify e.g. suitable locations for generators and ways to improve radiation efficiency. In EMC analysis, the goals are opposite: analyze a potentially radiating structure and reduce its potential for emission. During the Alexander von Humboldt Fellowship of Prof. Qi Wu at TUHH CMA was applied successfully to antenna design and extended to EMC analysis of digital systems

Particulate processes are the processes in which particles change their physical properties due to several mechanisms happening due to the interactions of the continuous and dispersed phases. Particulate processes are widely used in various fields of engineering such as aerosol, polymerization, chemical engineering, mining engineering, and emulsion processes. The physical properties that change due to different particulate processes are size, mass, porosity, shape etc. A well-known application of processing of particulate materials is the spray fluidized bed granulator (SFBG). SFBG are widely used to produce granular products for solubility control, tablet production, and other special materials in various industries. It has several advantageous features like temperature homogeneity, excellent heat and mass transfer properties, possibility of continuous operation and production of homogeneous granules. The objective of this research is twofold: first is to simulate SFBG process using DEM-CFD approach, second to identify influential parameters and approximate them in the form of aggregation and breakage kernels of the PBE. More specifically, DEM-CFD simulations (substitute for lab scale experiments) will only facilitate to design the mathematical form of the kernels as a function of different micro-properties so that the PBE framework can be used to predict particle size distribution (primary interest for the final product) at low cost. The main problem of the modeling stands for the identification of important parameters that can reasonably be correlated. We wish to find a new kernel structure that makes full use of scaling and splitting opportunities, reducing the problem of identification to some time-independent factor that is either constant or can be reasonably correlated with operating parameters.

The presence of high concentrations of ionic contaminants in groundwater reservoirs pose a serious threat to humans and environment. Amongst, selenium (Se) oxyanions have been recorded in groundwater because of mining, petroleum refining, fossil fuel combustion, and irrigation [2]. In accordance, high Se concentration i.e., 2103 μg/L, 800 μg/L, 2700 μg/L and 4475 μg/L have been found in Soan Sakesar Valley, Pakistan; Atacama Desert, Chile; Martin Creek Reservoir, Texas, USA; and Sirmaur district of Himachal Pradesh, India; respectively [3]. Nevertheless, Se is an essential mineral required by human body however it becomes noxious when found in greater concentrations in drinking water supplies. The oral intake of higher Se concentration (>400 μg/day) may cause serious health problems including reproductive anomalies and developmental abnormalities in foetus, hair loss, body pain, muscle damage, liver and kidney failure, cancer, and even death may occur. Therefore, German drinking water ordinance, World Health Organization (WHO) and U.S. Environmental Protection Agency has set Drinking Water Regulation Limit (DWRL) for Se as 10 μg/L, 40 μg/L and 50 μg/L, respectively [4,5]. To meet stringent Se guidelines and ensure public health safety, an efficient and technoeconomic feasible treatment approach is needed. Amongst, adsorption technology utilizing commercial iron-based adsorbents has shown promising performance for removing contaminants including metal oxyanions from a wide range of water matrices. However, eliminating Se from drinking water is challenging owing to its toxicity, solubility and varying oxidation states. It is commonly found in environment as selenate (Se(VI): HSeO4‾, SeO42-), selenite (Se(IV): H2SeO3, HSeO3‾, SeO32-), selenium (Se(0)) and selenide (Se(-II): H2Se, HSe‾) depending on pH and redox conditions [2]. Previous research [6–8] has shown wide applicability of commercially available iron-based adsorbent i.e., granular ferric hydroxide (GFH) for removal of other oxyanions including arsenic, phosphate, vanadium etc. from water. Therefore, it may be hypothesized that GFH may contain potential in eliminating toxic Se oxyanions from drinking water supplies. In addition, release of iron from poorly crystalline GFH structure into the solution particularly at low redox potential, leading to its higher residual content, has been rarely investigated. Therefore, it will be critical to examine the stability of GFH at long term operations along with its effectiveness in remediating targeted contaminants. In accordance, little is known on how Se oxyanions will behave and react with GFH in aqueous environment. It will therefore be worth exploring the mechanistic insights into the fate, mobility, transformation, and removal behavior of Se species under environmentally relevant conditions. In addition to commercial adsorbents, prior research has focused on utilization of iron-based sorbents for Se remediation from drinking water, however, all these studies only discussed in-depth understanding of batch mode operation [9]. Moreover, there always remains a research gap in utilizing adsorbent material in GEH® adsorbent unit for continuous mode Se treatment from drinking water supplies. Therefore, the planned project aims to address these research gaps and provide practical and sustainable solution to drinking water industries when dealing with toxic Se oxyanions.