• Environmental Challenges and Opportunities in Marine Engine Heavy Fuel Oil Combustion

      Abdul Jameel, Abdul Gani; Alkhateeb, Abdulrahman; Telalovic, Selvedin; Elbaz, Ayman M.; Roberts, William L.; Sarathy, Mani (Multi-Target Drug Design Using Chem-Bioinformatic Approaches, Springer New York, 2019-01-16) [Book Chapter]
      Heavy fuel oil (HFO) has been used as fuel to propel marine engines for over half a century. HFO combustion results in the release of particulate matter like smoke, cenospheres, and ash, and the high sulfur content in HFO results in sulfur dioxide emissions. The use of HFO has resulted in deleterious effects on the environment and on human health. As a result, the International Maritime Organization (IMO) has placed a complete ban on its use on ships in the Antarctic waters to preserve the ecosystem from harm; by 2020, this regulation could be extended to the rest of the world. In the present work, the environmental challenges associated with HFO combustion in the form of gaseous emissions like CO, CO, SO, and NO were analyzed using TGA-FTIR technique. Particulate emission like cenosphere formation during HFO combustion was also studied by employing HFO droplet combustion experiments. The influence of asphaltenes, which are notorious for negatively impacting HFO combustion and are responsible for cenosphere formation, was also studied. Strategies like desulfurization, asphaltene removal, and gasification were proposed to help reduce the environmental impact of ships powered by HFO.
    • TopSpin: TOPic Discovery via Sparse Principal Component INterference

      Takáč, Martin; Ahipaşaoğlu, Selin Damla; Cheung, Ngai-Man; Richtarik, Peter (Brain-Inspired Intelligence and Visual Perception, Springer Singapore, 2019-02-14) [Book Chapter]
      We propose a novel topic discovery algorithm for unlabeled images based on the bag-of-words (BoW) framework. We first extract a dictionary of visual words and subsequently for each image compute a visual word occurrence histogram. We view these histograms as rows of a large matrix from which we extract sparse principal components (PCs). Each PC identifies a sparse combination of visual words which co-occur frequently in some images but seldom appear in others. Each sparse PC corresponds to a topic, and images whose interference with the PC is high belong to that topic, revealing the common parts possessed by the images. We propose to solve the associated sparse PCA problems using an Alternating Maximization (AM) method, which we modify for the purpose of efficiently extracting multiple PCs in a deflation scheme. Our approach attacks the maximization problem in SPCA directly and is scalable to high-dimensional data. Experiments on automatic topic discovery and category prediction demonstrate encouraging performance of our approach. Our SPCA solver is publicly available.
    • Scalability of a parallel monolithic multilevel solver for poroelasticity

      Nägel, Arne; Wittum, Gabriel (Springer, 2019) [Book Chapter]
      This study investigates a solver for the quasi-static Biot model for soil con- solidation. The scheme consists of an extrapolation scheme in time, com- plemented by a scalable monolithic multigrid method for solving the linear systems resulting after spatial discretisation. The key ingredient for the later is a fixed-stress inexact Uzawa smoother that has been suggested and anal- ysed using local Fourier analysis before [8]. The work at hand investigates the parallel properties of the resulting multigrid solver. For a 3D benchmark problem with roughly 400 million degrees of freedom, scalability is demon- strated in a preliminary study on HazelHen. The presented solver framework should be seen as a prototype, and can be extended and generalized, e.g., to non-linear problems easily.
    • Massively Parallel Multigrid for the Simulation of Skin Permeation on Anisotropic Tetrakaidecahedral Cell Geometries

      Reiter, Sebastian; Nägel, Arne; Vogel, Andreas; Wittum, Gabriel (Springer, 2018-02-17) [Book Chapter]
      Numerical simulation based on mathematical models is an important pillar for enhancing the understanding of permeation processes in the skin. To adequately resolve the complex geometrical structure of the skin, special models based on tetrakaidecahedral cells have been suggested. While these models preserve many of the desirable properties of the underlying geometry, they impose challenges regarding mesh generation and solver robustness. To improve robustness of the used multigrid solver, we propose a new mesh and hierarchy structure with good aspect ratios and angle conditions. Furthermore, we show how those meshes can be used in scalable massively parallel multigrid based computations of permeation processes in the skin.
    • Towards the Implementation of a New Multigrid Solver in the DNS Code FS3D for Simulations of Shear-Thinning Jet Break-Up at Higher Reynolds Numbers

      Ertl, Moritz; Reutzsch, Jonathan; Nägel, Arne; Wittum, Gabriel; Weigand, Bernhard (Springer, 2018-02-17) [Book Chapter]
      Liquid jet break-up appears in many technical applications, as well as in nature. It consists of complex physical processes, which happen on very small scales in space and time. This makes them hard to capture by experimental methods; and therefore a prime subject for numerical investigations. The state-of-the-art approach combines the Volume of Fluid (VOF) method with Direct Numerical Simulations (DNS) as employed in the ITLR in-house code Free Surface 3D (FS3D). The simulation of these jets is dependent on very fine grids, with most of the computational costs incurred by solving the Pressure Poisson Equation. In order to simulate larger computational domains, we tried to improve the performance of FS3D by the implementation of a new multigrid solver. For this we selected the solver contained in the UG4 package developed by the Goethe Center for Scientific Computing at the University of Frankfurt. We will show simulations of the primary break-up of shear-thinning liquid jets and explain why larger computational domains are necessary. Results are preliminary. We demonstrate that the implementation of UG4 into FS3D provides a noticeable increase in weak scaling performance, while the change in strong scaling is yet detrimental. We will then discuss ways to further improve these results.
    • Numerical modelling of buckling phenomenon in carbon nanotubes filled with ZnS

      Cachim, Paulo; Monteiro, Andre O.; Da Costa, Pedro M. F. J.; Holec, David (Functionalized Engineering Materials and Their Applications, Taylor and Francis, 2018-09-03) [Book Chapter]
    • Scalable Cardiac Electro-Mechanical Solvers and Reentry Dynamics

      Franzone, P. Colli; Pavarino, L. F.; Scacchi, S.; Zampini, Stefano (Domain Decomposition Methods in Science and Engineering XXIV, Springer International Publishing, 2019-01-04) [Book Chapter]
      We present a scalable solver for the three-dimensional cardiac electro-mechanical coupling (EMC) model, which represents, currently, the most complete mathematical description of the interplay between the electrical and mechanical phenomena occurring during a heartbeat. The most computational demanding parts of the EMC model are: the electrical current flow model of the cardiac tissue, called Bidomain model, consisting of two non-linear partial differential equations of reaction-diffusion type; the quasi-static finite elasticity model for the deformation of the cardiac tissue. Our finite element parallel solver is based on: Block Jacobi and Multilevel Additive Schwarz preconditioners for the solution of the linear systems deriving from the discretization of the Bidomain equations; Newton-Krylov-Algebraic-Multigrid or Newton-Krylov-BDDC algorithms for the solution of the non-linear algebraic system deriving from the discretization of the finite elasticity equations. Three-dimensional numerical test on two linux clusters show the effectiveness and scalability of the EMC solver in simulating both physiological and pathological cardiac dynamics.
    • Balancing Domain Decomposition by Constraints Algorithms for Curl-Conforming Spaces of Arbitrary Order

      Zampini, Stefano; Vassilevski, Panayot; Dobrev, Veselin; Kolev, Tzanio (Domain Decomposition Methods in Science and Engineering XXIV, Springer International Publishing, 2019-01-04) [Book Chapter]
      We construct Balancing Domain Decomposition by Constraints methods for the linear systems arising from arbitrary order, finite element discretizations of the H(curl) model problem in three-dimensions. Numerical results confirm that the proposed algorithm is quasi-optimal in the coarse-to-fine mesh ratio, and poly-logarithmic in the polynomial order of the curl-conforming discretization space. Additional numerical experiments, including higher-order geometries, upscaled finite elements, and adaptive coarse spaces, prove the robustness of our algorithm. A scalable three-level extension is presented, and it is validated with large scale experiments using up to 16,384 subdomains and almost a billion of degrees of freedom.
    • Perovskite Single Crystals: Synthesis, Properties and Devices

      Zhumekenov, Ayan A.; Saidaminov, Makhsud I.; Bakr, Osman (World Scientific Handbook of Organic Optoelectronic Devices, World Scientific, 2018-06-27) [Book Chapter]
    • Energy-Efficient 5G Networks Using Joint Energy Harvesting and Scheduling

      Alsharoa, Ahmad; Celik, Abdulkadir; Kamal, Ahmed E. (5G Networks: Fundamental Requirements, Enabling Technologies, and Operations Management, John Wiley & Sons, Inc., 2018-09-16) [Book Chapter]
      This chapter considers a downlink energy harvesting heterogeneous networks (EHHetNet) system where each base station (BS) is equipped to harvest from wireless and renewable sources. It presents the EH HetNets system model and gives the problem formulation based on the knowledge level of the RE generation, aiming to minimize the networks energy consumption during the B time slots. The formulated binary linear programming (BLP) optimization problems are considered as NP-hard problem due to the existence of the binary variables; hence, propose a metaheuristic algorithm, namely, binary particle swarm optimization (BPSO). The performances of the proposed BPSO algorithm is compared to those of the well-know genetic algorithm (GA). The chapter provides the selected numerical results to evaluate the performance of the EH HetNets systems. Selected BSs transmit their messages periodically every Tbsec.
    • Spatial extremes

      Davison, Anthony C.; Huser, Raphaël (CRC Press, 2019) [Book Chapter]
    • Numerical recipies for landslide spatial prediction by using R-INLA: A step-by-step tutorial

      Lombardo, Luigi; Opitz, Thomas; Huser, Raphaël (Elsevier, 2019) [Book Chapter]
      The geomorphological community typically assesses the landslide susceptibility at the catch- ment or larger scales through spatial predictive models. However, the spatial information is conveyed only through the geographical distribution of the covariates. Spatial dependence, which allows capturing similarities at neighboring sites that are not directly explained by covariate information, is typically not accounted for in the landslides literature, whilst such spatial models have become commonplace in the geostatistical literature. Here we explain step by step how to rigorously model and predict activations of debris flow based on an adequate statistical model by using the R-INLA library from the statistical software R in the context of a real multiple landslide event. This chapter follows the analysis of Lombardo et al. (2018a) with a few modifications; it is written in a tutorial style to provide the geomor- phological community with a hands-on guide to replicate similar analyses in R. While our focus here is on implementation and computing, more details about the underlying statistical theory, modeling and estimation can be found in Lombardo et al. (2018a). Our modeling approach deviates fundamentally from the commonly-used regression models fitted to binary presence/absence data. Specifically, we use a Bayesian hierarchical Cox point process model to describe landslide counts at high resolution (i.e., at the pixel level), while capturing spatial dependence through a latent spatial effect defined at lower resolution over slope units. Our point process modeling approach allows us to derive the distribution of aggregated landslide counts for any areas of interest. Crucially, the latent spatial effect represents the unexplained but spatially structured component in the data when the linear or nonlinear effects of covariates are removed. Thus, in the case of sparse raingauge or seismic networks, we suggest using the latent spatial effect to uncover the trigger distribution over space. In particular, for landslides triggered by extreme precipitation, the meteorological stress can play a dominant role with respect to the covariates that are typically introduced in predictive models; therefore, accounting for the trigger in modeling may dramatically improve the performance of landslide prediction.
    • An Adjoint-Based Approach for a Class of Nonlinear Fokker-Planck Equations and Related Systems

      Festa, Adriano; Gomes, Diogo A.; Machado Velho, Roberto (PDE Models for Multi-Agent Phenomena, Springer International Publishing, 2018-12-22) [Book Chapter]
      Here, we introduce a numerical approach for a class of Fokker-Planck (FP) equations. These equations are the adjoint of the linearization of Hamilton-Jacobi (HJ) equations. Using this structure, we show how to transfer properties of schemes for HJ equations to FP equations. Hence, we get numerical schemes with desirable features such as positivity and mass-preservation. We illustrate this approach in examples that include mean-field games and a crowd motion model.
    • Increasing Salinity Tolerance of Crops

      Alqahtani, Mashael; Roy, Stuart J.; Tester, Mark A. (Encyclopedia of Sustainability Science and Technology, Springer New York, 2018-12-18) [Book Chapter]
    • Compact CPV—Sustainable Approach for Efficient Solar Energy Capture with Hybrid Concentrated Photovoltaic Thermal (CPVT) System and Hydrogen Production

      Burhan, Muhammad; Shahzad, Muhammad Wakil; Ng, Kim Choon (The Energy Mix for Sustaining Our Future, Springer International Publishing, 2018-12-29) [Book Chapter]
      Solar energy being intermittent in nature can provide a sustainable, steady, and high-density energy source when converted into electrolytic hydrogen. However, in the current photovoltaic market trend with 99% conventional single junction PV panels, this cannot be achieved efficiently and economically. The advent of the multi-junction solar cells (MJCs), with cell efficiency exceeding 46%, has yet to receive widespread acceptance in the current PV market in form of concentrated photovoltaic (CPV) system, because of its system design complexity, limiting its application scope and customers. The objective of this paper is to develop a low-cost compact CPV system that will not only eliminate its application and installation-related restrictions but it is also introducing a highly efficient and sustainable photovoltaic system for common consumer, to convert intermittent sunlight into green hydrogen. The developed CPV system negates the common conviction by showing two times more power output than the flat plate PV, in the tropical region. In addition, sunlight to hydrogen conversion efficiency of 18% is recorded for CPV, which is two times higher than alone electricity production efficiency of flat plate PV. As concentrated photovoltaic (CPV) system can operate at ×1000 concentration ratio, therefore, such high concentration ratio requires heat dissipation from the cell area to maintain optimum temperature. With such heat recovery, the hybrid CPVT system has shown solar energy conversion efficiency of 71%.
    • Chapter 14: Automated Mining of Disease-Specific Protein Interaction Networks Based on Biomedical Literature

      Chowdhary, Rajesh; Jankovic, Boris R.; Stankowski, Rachel V.; Archer, John A.C.; Zhang, Xiangliang; Gao, Xin; Bajic, Vladimir B. (Science, Engineering, and Biology InformaticsBiological Data Mining and Its Applications in Healthcare, WORLD SCIENTIFIC, 2013-12-17) [Book Chapter]
    • Virus-Mediated Genome Editing in Plants Using the CRISPR/Cas9 System

      Mahas, Ahmed; Ali, Zahir; Tashkandi, Manal; Mahfouz, Magdy M. (Plant Genome Editing with CRISPR Systems, Springer New York, 2019-01-04) [Protocol]
      Targeted modification of plant genomes is a powerful strategy for investigating and engineering cellular systems, paving the way for the discovery and development of important, novel agricultural traits. Cas9, an RNA-guided DNA endonuclease from the type II adaptive immune CRISPR system of the prokaryote Streptococcus pyogenes, has gained widespread popularity as a genome-editing tool for use in a wide array of cells and organisms, including model and crop plants. Effective genome engineering requires the delivery of the Cas9 protein and guide RNAs into target cells. However, in planta genome modification faces many hurdles, including the difficulty in efficiently delivering genome engineering reagents to the desired tissues. We recently developed a Tobacco rattle virus (TRV)-mediated genome engineering system for Nicotiana benthamiana. Using this platform, genome engineering reagents can be delivered into all plant parts in a simple, efficient manner, facilitating the recovery of progeny plants with the desired genomic modifications, thus bypassing the need for transformation and tissue culture. This platform expands the utility of the CRISPR/Cas9 system for in planta, targeted genome modification. Here, we provide a detailed protocol explaining the methodologies used to develop and implement TRV-mediated genome engineering in N. benthamiana. The protocol described here can be extended to any other plant species susceptible to systemic infection by TRV. However, this approach is not limited to vectors derived from TRV, as other RNA viruses could be used to develop similar delivery platforms.
    • Crustal and Upper-Mantle Structure Beneath Saudi Arabia from Receiver Functions and Surface Wave Analysis

      Mai, Paul Martin; Julià, Jordi; Tang, Zheng (Geological Setting, Palaeoenvironment and Archaeology of the Red Sea, Springer International Publishing, 2018-12-05) [Book Chapter]
      Using receiver-functions and surface-wave dispersion curves, we study the crustal and upper-mantle structure of Saudi Arabia. Our results reveal first-order differences in crustal thickness between the Arabian Shield in the west and the Arabian Platform in the east. Moho depths generally increase eastward, while crustal thickness varies strongly in the west over the volcanic regions and near the Red Sea. Localized zones of increased P-wave speed in the west may indicate solidified magmatic intrusions within the area of recent volcanism. Our receiver-function analysis for deep converted phases reveals that the transition zone thickness between the 410 km and the 660 km discontinuities is not anomalously thinned, refuting the hypothesis of a small localized mantle plume as the origin for the volcanic activity in western Saudi Arabia. Our results suggest that the volcanism in western Arabia may be due to the lithospheric mantle being heated from below by lateral flow from the Afar and (possibly) Jordan plumes. This triggers localized melts that ascend adiabatically through the lithosphere as magma diapirs. Recent xenolith measurements that provide information on temperatures and depths of melting are overall consistent with this hypothesis. However, further dedicated localized tomographic studies are needed to decipher the details of the origin of the volcanism and its relation to the overall geodynamics of the region.
    • Physicochemical Dynamics, Microbial Community Patterns, and Reef Growth in Coral Reefs of the Central Red Sea

      Roik, Anna Krystyna; Ziegler, Maren; Voolstra, Christian R. (Oceanographic and Biological Aspects of the Red Sea, Springer International Publishing, 2018-12-06) [Book Chapter]
      Coral reefs in the Red Sea belong to the most diverse and productive reef ecosystems worldwide, although they are exposed to strong seasonal variability, high temperature, and high salinity. These factors are considered stressful for coral reef biota and challenge reef growth in other oceans, but coral reefs in the Red Sea thrive despite these challenges. In the central Red Sea high temperatures, high salinities, and low dissolved oxygen on the one hand reflect conditions that are predicted for ‘future oceans’ under global warming. On the other hand, alkalinity and other carbonate chemistry parameters are considered favourable for coral growth. In coral reefs of the central Red Sea, temperature and salinity follow a seasonal cycle, while chlorophyll and inorganic nutrients mostly vary spatially, and dissolved oxygen and pH fluctuate on the scale of hours to days. Within these strong environmental gradients micro- and macroscopic reef communities are dynamic and demonstrate plasticity and acclimatisation potential. Epilithic biofilm communities of bacteria and algae, crucial for the recruitment of reef-builders, undergo seasonal community shifts that are mainly driven by changes in temperature, salinity, and dissolved oxygen. These variables are predicted to change with the progression of global environmental change and suggest an immediate effect of climate change on the microbial community composition of biofilms. Corals are so-called holobionts and associate with a variety of microbial organisms that fulfill important functions in coral health and productivity. For instance, coral-associated bacterial communities are more specific and less diverse than those of marine biofilms, and in many coral species in the central Red Sea they are dominated by bacteria from the genus Endozoicomonas. Generally, coral microbiomes align with ecological differences between reef sites. They are similar at sites where these corals are abundant and successful. Coral microbiomes reveal a measurable footprint of anthropogenic influence at polluted sites. Coral-associated communities of endosymbiotic dinoflagellates in central Red Sea corals are dominated by Symbiodinium from clade C. Some corals harbour the same specific symbiont with a high physiological plasticity throughout their distribution range, while others maintain a more flexible association with varying symbionts of high physiological specificity over depths, seasons, or reef locations. The coral-Symbiodinium endosymbiosis drives calcification of the coral skeleton, which is a key process that provides maintenance and formation of the reef framework. Calcification rates and reef growth are not higher than in other coral reef regions, despite the beneficial carbonate chemistry in the central Red Sea. This may be related to the comparatively high temperatures, as indicated by reduced summer calcification and long-term slowing of growth rates that correlate with ocean warming trends. Indeed, thermal limits of abundant coral species in the central Red Sea may have been exceeded, as evidenced by repeated mass bleaching events during previous years. Recent comprehensive baseline data from central Red Sea reefs allow for insight into coral reef functioning and for quantification of the impacts of environmental change in the region.
    • Seagrass Distribution, Composition and Abundance Along the Saudi Arabian Coast of Red Sea

      Qurban, Mohammad Ali B.; Karuppasamy, Manikandan; Krishnakumar, Periyadan K.; Garcias Bonet, Neus; Duarte, Carlos M. (Oceanographic and Biological Aspects of the Red Sea, Springer International Publishing, 2018-12-06) [Book Chapter]
      Seagrasses rank among the most productive ecosystems with important implications in climate change mitigation. Tropical and subtropical seas hold the largest seagrass species richness. A total of 12 different seagrass species have been reported from the Red Sea. However, there is little information on seagrass diversity and distribution along the Saudi Arabian coast of the Red Sea. This study aims to capture: (i) the distribution and composition of seagrasses from 18°N to 28°N latitudes on a broader scale, and (ii) the species composition, distribution and abundance of seagrasses by detailed investigations at three locations along the Saudi Arabian coast: Sharma, Umluj and Jazan, representing the northern, central and southern Red Sea. The most commonly observed seagrass species along the Red Sea were Halodule uninervis (17 observations), Thalassia hemprichii (13 observations) and Halophila stipulacea (11 observations). Halophila stipulacea was the most dominant species at each of the three locations studied in more detail. Syringodium isoetifolium and Thalassodendron ciliatum were found only at Umluj, while H. ovalis and T. hemprichii were found only at Jazan. H. uninervis was observed at both Umluj and Jazan. Shoot lengths of H. stipulacea and H. uninervis showed significant differences among the three locations. The average above-ground biomass of seagrasses differed significantly among locations (analysis <0.05; multiple tests), with the highest biomass for Halophila stipulacea recorded at Jazan (81 ± 24 gDW m−2) and an average biomass for T. ciliatum of 74 ± 16 gDW m−2 at Umluj. The species T. ciliatum was the only taxa that exhibited significant differences (p < 0.05) in the abundance of seagrasses among the three locations. This work contributes further to our understanding of the distribution and diversity of seagrasses in the Red Sea, confirming a high seagrass richness with at least ten different species along the Saudi Arabian coast of the Red Sea.