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The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps’ characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer’s point of view, keeping in mind the economically important trade-off between investment and operation costs.
Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.
Nacre-mimetic nanocomposites based on high fractions of synthetic high-aspect-ratio nanoclays in combination with polymers are continuously pushing boundaries for advanced material properties, such as high barrier against oxygen, extraordinary mechanical behavior, fire shielding, and glass-like transparency. Additionally, they provide interesting model systems to study polymers under nanoconfinement due to the well-defined layered nanocomposite arrangement. Although the general behavior in terms of forming such layered nanocomposite materials using evaporative self-assembly and controlling the nanoclay gallery spacing by the nanoclay/polymer ratio is understood, some combinations of polymer matrices and nanoclay reinforcement do not comply with the established models. Here, we demonstrate a thorough characterization and analysis of such an unusual polymer/nanoclay pair that falls outside of the general behavior. Poly(ethylene oxide) (PEO) and sodium fluorohectorite form nacre-mimetic, lamellar nanocomposites that are completely transparent and show high mechanical stiffness and high gas barrier, but there is only limited expansion of the nanoclay gallery spacing when adding increasing amounts of polymer. This behavior is maintained for molecular weights of PEO varied over four orders of magnitude and can be traced back to depletion forces. By careful investigation via X-ray diffraction and proton low-resolution solid-state NMR, we are able to quantify the amount of mobile and immobilized polymer species in between the nanoclay galleries and around proposed tactoid stacks embedded in a PEO matrix. We further elucidate the unusual confined polymer dynamics, indicating a relevant role of specific surface interactions.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
As part of the transnational research project EDITOR, a parabolic trough collector system (PTC) with concrete thermal energy storage (C-TES) was installed and commissioned in Limassol, Cyprus. The system is located on the premises of the beverage manufacturer KEAN Soft Drinks Ltd. and its function is to supply process steam for the factory's pasteurisation process [1]. Depending on the factory's seasonally varying capacity for beverage production, the solar system delivers between 5 and 25 % of the total steam demand. In combination with the C-TES, the solar plant can supply process steam on demand before sunrise or after sunset. Furthermore, the C-TES compensates the PTC during the day in fluctuating weather conditions. The parabolic trough collector as well as the control and oil handling unit is designed and manufactured by Protarget AG, Germany. The C-TES is designed and produced by CADE Soluciones de Ingeniería, S.L., Spain. In the focus of this paper is the description of the operational experience with the PTC, C-TES and boiler during the commissioning and operation phase. Additionally, innovative optimisation measures are presented.
Modeling and upscaling of a pilot bayonettube reactor for indirect solar mixed methane reforming
(2020)
A 16.77 kW thermal power bayonet-tube reactor for the mixed reforming of methane using solar energy has been designed and modeled. A test bench for the experimental tests has been installed at the Synlight facility in Juelich, Germany and has just been commissioned. This paper presents the solar-heated reactor design for a combined steam and dry reforming as well as a scaled-up process simulation of a solar reforming plant for methanol production. Solar power towers are capable of providing large amounts of heat to drive high-endothermic reactions, and their integration with thermochemical processes shows a promising future. In the designed bayonet-tube reactor, the conventional burner arrangement for the combustion of natural gas has been substituted by a continuous 930 °C hot air stream, provided by means of a solar heated air receiver, a ceramic thermal storage and an auxiliary firing system. Inside the solar-heated reactor, the heat is transferred by means of convective mechanism mainly; instead of radiation mechanism as typically prevailing in fossil-based industrial reforming processes. A scaled-up solar reforming plant of 50.5 MWth was designed and simulated in Dymola® and AspenPlus®. In comparison to a fossil-based industrial reforming process of the same thermal capacity, a solar reforming plant with thermal storage promises a reduction up to 57 % of annual natural gas consumption in regions with annual DNI-value of 2349 kWh/m2. The benchmark solar reforming plant contributes to a CO2 avoidance of approx. 79 kilotons per year. This facility can produce a nominal output of 734.4 t of synthesis gas and out of this 530 t of methanol a day.
Game-based learning is a promising approach to anti-phishing education, as it fosters motivation and can help reduce the perceived difficulty of the educational material. Over the years, several prototypes for game-based applications have been proposed, that follow different approaches in content selection, presentation, and game mechanics. In this paper, a literature and product review of existing learning games is presented. Based on research papers and accessible applications, an in-depth analysis was conducted, encompassing target groups, educational contexts, learning goals based on Bloom’s Revised Taxonomy, and learning content. As a result of this review, we created the publications on games (POG) data set for the domain of anti-phishing education. While there are games that can convey factual and conceptual knowledge, we find that most games are either unavailable, fail to convey procedural knowledge or lack technical depth. Thus, we identify potential areas of improvement for games suitable for end-users in informal learning contexts.
Biocomposite Materials Based on Carbonized Rice Husk in Biomedicine and Environmental Applications
(2020)
This chapter describes the prospects for biomedical and environmental engineering applications of heterogeneous materials based on nanostructured carbonized rice husk. Efforts in engineering enzymology are focused on the following directions: development and optimization of immobilization methods leading to novel biotechnological and biomedical applications; construction of biocomposite materials based on individual enzymes, multi-enzyme complexes and whole cells, targeted on realization of specific industrial processes. Molecular biological and biochemical studies on cell adhesion focus predominantly on identification, isolation and structural analysis of attachment-responsible biological molecules and their genetic determinants. The chapter provides a short overview of applications of the biocomposite materials based of nanostructured carbonized adsorbents. It emphasizes that further studies and better understanding of the interactions between CNS and microbial cells are necessary. The future use of living cells as biocatalysts, especially in the environmental field, needs more systematic investigations of the microbial adsorption phenomenon.