Refine
Year of publication
Document Type
- Article (149) (remove)
Has Fulltext
- yes (149)
Keywords
- Risikomanagement (5)
- Erneuerbare Energien (4)
- Digitaler Zwilling (3)
- HIV (3)
- Heterogeneous Catalysis (3)
- Katastrophenmanagement (3)
- Katastrophenrisiko (3)
- Klimaänderung (3)
- Lyrik (3)
- Optimization (3)
Faculty
- Angewandte Naturwissenschaften (F11) (29)
- Fakultät 12 / Institut für Technologie und Ressourcenmanagement in den Tropen und Subtropen (21)
- Fakultät 09 / Institut für Rettungsingenieurwesen und Gefahrenabwehr (11)
- Fakultät 10 / Institut Allgemeiner Maschinenbau (11)
- Fakultät 03 / Institut für Translation und Mehrsprachige Kommunikation (8)
- Fakultät 09 / Institut für Produktentwicklung und Konstruktionstechnik (8)
- Fakultät 07 / Institut für Nachrichtentechnik (7)
- Fakultät 09 / Institut Anlagen und Verfahrenstechnik (7)
- Fakultät 09 / Cologne Institute for Renewable Energy (6)
- Fakultät 03 / Institut für Informationswissenschaft (4)
Stable recombinant mammalian cells are of growing importance in pharmaceutical biotechnology production scenarios for biologics such as monoclonal antibodies, growth and blood factors, cytokines and subunit vaccines. However, the establishment of recombinant producer cells using classical stable transfection of plasmid DNA is hampered by low stable gene transfer efficiencies. Consequently, subsequent selection of transgenic cells and the screening of clonal cell populations are time- and thus cost-intensive. To overcome these limitations, expression cassettes were embedded into transposon-derived donor vectors. Upon the co-transfection with transposase-encoding constructs, elevated vector copy numbers stably integrated into the genomes of the host cells are readily achieved facilitating under stringent selection pressure the establishment of cell pools characterized by sustained and high-yield recombinant protein production. Here, we discuss some aspects of transposon vector technologies, which render these vectors promising candidates for their further utilization in the production of biologics.
This paper introduces CAAI, a novel cognitive architecture for artificial intelligence in cyber-physical production systems. The goal of the architecture is to reduce the implementation effort for the usage of artificial intelligence algorithms. The core of the CAAI is a cognitive module that processes the user’s declarative goals, selects suitable models and algorithms, and creates a configuration for the execution of a processing pipeline on a big data platform. Constant observation and evaluation against performance criteria assess the performance of pipelines for many and different use cases. Based on these evaluations, the pipelines are automatically adapted if necessary. The modular design with well-defined interfaces enables the reusability and extensibility of pipeline components. A big data platform implements this modular design supported by technologies such as Docker, Kubernetes, and Kafka for virtualization and orchestration of the individual components and their communication. The implementation of the architecture is evaluated using a real-world use case. The prototypic implementation is accessible on GitHub and contains a demonstration.
Editorial
(2020)
Reducing the carbon emissions from hotels on non-interconnected islands (NII) is essential in the context of a low carbon future for the Mediterranean region. Maritime tourism is the major source of income for Greece and many other countries in the region, as well as hot-temperate and tropical regions worldwide. Like many NIIs, Rhodes attracts a high influx of tourists every summer, doubling the island’s energy demand and, given the high proportion of fossil fuels in the Rhodian energy supply, increasing carbon emissions. Using the theoretical framework ‘FINE’, this paper presents the optimisation of a medium-sized hotel’s energy system with the aim of reducing both cost and carbon emissions. By introducing a Photovoltaic (PV) net metering system, it was found that the carbon emissions associated with an NII hotel’s energy system could be reduced by 31% at an optimised cost. It is suggested that large-scale deployment of PV or alternative renewable energy sources (RES) in NII hotels could significantly reduce carbon emissions associated with the accommodation sector in Greece and help mitigate climate change.
Steer-by-wire systems represent a key technology for highly automated and autonomous driving. In this context, robust steering control is a fundamental precondition for automated vehicle lateral control. However, there is a need for improvement due to degrees of freedom, signal delays, and nonlinear characteristics of the plant which are unconsidered in the design models for the design of current steering controls. To be able to design an extremely robust steering control, suitable optimal models of a steer-by-wire system are required. Therefore, this paper presents an innovative nonlinear detail model of a steer-by-wire system. The detail model represents all characteristics of a real steer-by-wire system. In the context of a dominance analysis of the detail model, all dominant characteristics of a steer-by-wire system, including parameter dependencies, are identified. Through model reduction, a reduced model of the steer-by-wire system is then developed that can be used for a subsequent robust control design. Furthermore, this paper compares the steer-by-wire system with a conventional electromechanical power steering and shows similarities as well as differences.
Positive Impact of Red Soil on Albedo and the Annual Yield of Bifacial Photovoltaic Systems in Ghana
(2023)
The annual yield of bifacial photovoltaic systems is highly dependent on the albedo of the underlying soil. There are currently no published data about the albedo of red soil in western Africa. In this study, the impact of the albedo of red soil in Ghana on the energy yield of bifacial photovoltaic systems is analysed. A bifacial photovoltaic simulation model is created by combining the optical view factor matrix with an electrical output simulation. For an exact simulation, the albedo of red soil at three different locations in Ghana is measured for the first time. The average albedo of every red soil is clearly determined, as well as the measurement span including instrumentation uncertainty; values between 0.175 and 0.335 were measured. Considering these data, a state-of-the-art bifacial photovoltaic system with an average of 19.8% efficient modules in northern Ghana can achieve an annual energy yield of 508.8 kWh/m2 and a bifacial gain of up to 18.3% in comparison with monofacial photovoltaic panels. To summarise, red soil in two out of three locations in Ghana shows higher albedo values than most natural ground surfaces and therefore positively impacts the annual yield of bifacial photovoltaic systems.
Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data
(2023)
The transition towards climate neutrality will result in an increase in electrical vehicles, as well as other electric loads, leading to higher loads on electrical distribution grids. This paper presents an optimisation algorithm that enables the integration of more loads into distribution grid infrastructure using information from smart meters and/or smart meter gateways. To achieve this, a mathematical programming formulation was developed and implemented. The algorithm determines the optimal charging schedule for all electric vehicles connected to the distribution grid, taking into account various criteria to avoid violating physical grid limitations and ensuring non-discriminatory charging of all electric vehicles on the grid while also optimising grid operation. Additionally, the expandability of the infrastructure and fail-safe operation are considered through the decentralisation of all components. Various scenarios are modelled and evaluated in a simulation environment. The results demonstrate that the developed optimisation algorithm allows for higher transformer loads compared to a P(U) control approach, without causing grid overload as observed in scenarios without optimisation or P(U) control.
Abstract
Even though researchers are increasingly acknowledging the dark side of customer participation (i.e., behavioral customer engagement), particularly in professional services with high cognitive demands that cause customer participation stress (i.e., negative psychological state resulting from the customer's overextension by required customer participation efforts), insights on how firms can effectively mitigate customer participation stress remains limited. Building on transactional stress theory, we investigate whether customers can effectively cope with the expected cognitive demands of professional services. Moreover, by introducing an adapted coping construct (i.e., coping support), we examine whether employees can provide coping support to help decrease customer participation stress. The findings of a time‐lagged field study with customers of a large German bank (N = 117) suggest that customer coping before the encounter cannot mitigate the effect of anticipated cognitive demands on customer participation stress. Instead, the results of both the field study and a follow‐up experimental study (N = 218) show that a certain set of employee coping support during service encounters is crucial. While focusing on action coping support is not ideal in situations with high cognitive demands, firms should advise their professional service employees to offer emotional coping support to attenuate the unfavorable effect of cognitive demands on customer participation stress.
To date, the establishment of high-titer stable viral packaging cells (VPCs) at large scale for gene therapeutic applications is very time- and cost-intensive. Here we report the establishment of three human suspension 293-F-derived ecotropic MLV-based VPCs. The classic stable transfection of an EGFP-expressing transfer vector resulted in a polyclonal VPC pool that facilitated cultivation in shake flasks of 100 mL volumes and yielded high functional titers of more than 1 × 106 transducing units/mL (TU/mL). When the transfer vector was flanked by transposon terminal inverted repeats (TIRs) and upon co-transfection of a plasmid encoding for the transposase, productivities could be slightly elevated to more than 3 × 106 TU/mL. In contrast and using mRNA encoding for the transposase, as a proof of concept, productivities were drastically improved by more than ten-fold exceeding 5 × 107 TU/mL. In addition, these VPC pools were generated within only 3 weeks. The production volume was successfully scaled up to 500 mL employing a stirred-tank bioreactor (STR). We anticipate that the stable transposition of transfer vectors employing transposase transcripts will be of utility for the future establishment of high-yield VPCs producing pseudotype vector particles with a broader host tropism on a large scale.
Austria is committed to the net-zero climate goal along with the European Union. This requires all sectors to be decarbonized. Hereby, hydrogen plays a vital role as stated in the national hydrogen strategy. A report commissioned by the Austrian government predicts a minimum hydrogen demand of 16 TWh per year in Austria in 2040. Besides hydrogen imports, domestic production can ensure supply. Hence, this study analyses the levelized cost of hydrogen for an off-grid production plant including a proton exchange membrane electrolyzer, wind power and solar photovoltaics in Austria. In the first step, the capacity factors of the renewable electricity sources are determined by conducting a geographic information system analysis. Secondly, the levelized cost of electricity for wind power and solarphotovoltaics plants in Austria is calculated. Thirdly, the most cost-efficient portfolio of wind power and solar photovoltaics plants is determined using electricity generation profiles with a 10-min granularity. The modelled system variants differ among location, capacity factors of the renewable electricity sources and the full load hours of the electrolyzer. Finally, selected variables are tested for their sensitivities. With the applied model, the hydrogen production cost for decentralized production plants can be calculated for any specific location. The levelized cost of hydrogen estimates range from 3.08 EUR/kg to 13.12 EUR/kg of hydrogen, whereas it was found that the costs are most sensitive to the capacity factors of the renewable electricity sources and the full load hours of the electrolyzer. The novelty of the paper stems from the model applied that calculates the levelized cost of renewable hydrogen in an off-grid hydrogen production system. The model finds a cost-efficient portfolio of directly coupled wind power and solar photovoltaics systems for 80 different variants in an Austria-specific context.