Multicomponent Working Fluids in Organic Rankine Cycle Evaporators

Organic Rankine cycles are a promising technology to convert waste heat energy into usable mechanical or electric power, giving them the potential to reduce fossil fuel emissions generated by traditional energy generation. The heat exchangers of these devices are of particular interest, as maximizing energy extraction from these free heat sources will increase net electrical power output. For this project I created a model to predict the effects of mixture working fluids on the evaporator performance of an organic Rankine cycle generator for a wide range of waste heat source temperatures. This model combines empirically derived heat exchanger performance parameters with the Lemmon and Jacobsen equations of state for mixtures of refrigerants to calculate the overall heat transfer coefficient (the UA value) for the specified entry conditions, allowing for outlet temperatures and net heat transfer to be predicted. Data was collected on a 10”x20” x 40 plate flat plate heat exchanger using cool and warm water at various flow rates. Additional data was provided by Ener-G-Rotors from their refrigerant test bed. Parameters that can be varied within the model are the mass flow rates and inlet temperatures of the heat source and refrigerant, as well as the composition of the refrigerant working fluid. This variability will assist in future system adaptations to new waste heat conditions that could be utilized by organic Rankine cycle technology

REDUCING THE COGNITIVE LOAD OF DECISION-MAKERS IN EMERGENCY MANAGEMENT THROUGH AUGMENTED REALITY

Decision processes in emergency management are particularly complex. Operations managers have to make decisions under time pressure while the situation at hand changes continuously. As wrong decisions in emergencies often have drastic effects, operations managers try to receive information from various sources such as the emergency control centre, their operation forces, databases, electronic location maps and drones. However, previous research has shown that humans have only limited information processing capabilities, and once these are exceeded, task performance decreases. Augmented Reality (AR) offers entire new possibilities to visualise information. Previous research on the relationship between the use of AR for information visualisation and the experienced cognitive load yielded contradictory results. By using the design science approach, we therefore aim to develop an AR decision support system. In a comparative eye-tracking study, we plan to examine how different types of AR information visualisation affect the experienced cognitive load of operations managers and thus decision-making. In this research-in-progress paper, we present the results of expert interviews with six operations managers who described three AR use cases in emergency management and five requirements for an AR decision support system

The Potential of Augmented Reality for Improving Occupational First Aid

Accidents at work can happen at any time, but employees often do not feel prepared for such situations and therefore provide inadequate first aid. Using the Design Science approach, we developed a concept for an Augmented Reality(AR) application which uses voice assistance and visual AR overlays to support occupational first aiders with instructions in accident situations. The concept was implemented in the form of a video prototype and evaluated through interviews. The evaluation revealed that the application would enable employees without first aid training to apply first aid measures quickly and correctly; thus, reducing the probability of serious consequential injuries and costs in connection with occupational accidents

Towards predictive part quality and predictive maintenance in industrial machining - a data-driven approach

Programs such as Industry 4.0 and Internet of Things contain the promise of intelligent production with smart services . In fact, great advances have already been made in sensor technology and machine connectivity. Production plants continuously generate and communicate large amounts of data and have become cyber-physical systems . However, the task of gaining knowledge from these large amounts of data is still challenging. Data generated by numerical control (NC) and programmable logic controllers (NC) comes in a raw format that doesn’t allow the application of analytical methods directly. Extensive preprocessing and feature engineering has to be applied to structure this data for further analysis. An important application is the timely detection of deviations in the production process which allows immediate reactions and adjustments of production parameters or indicates the necessity of a predictive maintenance action. In our research, we aimed at the identification of special deviant behavior of a grinding machine based on NC data. One finding wast the distinguishing the warm-up program from regular production and the other to recognize imprecise identification of the grinding process window. Both tasks could be solved with extensive preprocessing of the raw data, appropriate feature extraction and feature reduction, and the subsequent application of a clustering algorithm

A Social Network Approach for Investigating Social Influences on Effective Use: Demonstration in Virtual Reality Collaboration

Merely using new collaboration technologies does not necessarily result in the desired benefits, which is why it is important to understand what constitutes effective use behavior. In information systems research, the affordance network approach has been developed as a methodological approach to investigate effective use behavior. The approach has already been applied to understand the effective use of electronic medical record systems and fitness wearables; however, it neglects how social influences foster or hinder effective use behavior in collaborative settings. Therefore, we supplemented the affordance network approach for collaborative contexts by using social network methods. We demonstrate our approach based on two university courses in which students carried out group work within the collaborative VR application Spatial. Thereby, we contribute a methodological approach that enables researchers to identify influential users who encourage their team members to actualize affordances leading to goal achievement

The Adoption of social media analytics for crisis management – Challenges and Opportunities

We live in a time when anyone can change from a passive bystander to an active communicator during a crisis. This makes user-generated content a potentially valuable source of information for emergency management agencies. However, at present, agencies still hesitate to use social media during crises. This research seeks to identify the challenges emergency management agencies face in using social media analytics within their organisations. We conducted a systematic literature review and interviewed ten emergency management professionals across six expert interview sessions. Afterwards, we used the Technology-Organization-Environment Framework to conceptualise our findings. Our study reveals fruitful opportunities for the continuous collaboration of both information systems research and emergency management agencies. Accordingly, information systems research can support emergency management agencies in using social media data for efficient crisis management by enhancing awareness of the benefits of social media analytics and helping to overcome organisational and technological challenges

Towards Routinely Using Virtual Reality in Higher Education

Virtual reality promises to be a tool that can improve higher education. Immersive virtual environments offer the chance to enrich courses with experiential learning experiences. The technological possibilities evolve rapidly and more and more researchers report on adopting virtual reality for learning – albeit such work often has a more or less experimental character. However, the base of knowledge on using virtual reality in higher education is growing; educators who want to employ virtual reality to amend courses, to extend the curriculum with experiential learning, or who want to offer new content enabled through virtual reality, find increasingly rich advice. With this article, we contribute to this advice by providing insights from three research cases. Although these were experimental, their embedding into a larger project enables us to propose recommendations for educators. The ultimate aim of our work is the routine use of virtual reality in higher education

Credibility of Cyber Threat Communication on Twitter – Expert Evaluation of Indicators for Automated Credibility Assessment

Computer Emergency Response Teams (CERTs) are experts responsible for managing cybersecurity incidents. To identify cyber threats, they consider a wide range of sources from official vulnerability databases to public sources such as Twitter, which has an active cybersecurity community. Due to the high number of topic-related tweets per day, credibility assessment represents an immense effort in the daily work of CERTs. Although approaches for automated credibility assessment have already been developed in previous research, these mainly take peripheral cues into account, although users with domain expertise and a high level of personal involvement also assess content-related cues. We therefore conducted interviews with CERT members to re-evaluate known indicators for automated credibility assessment from an expert perspective. In doing so, we contribute valuable insights to the development of automated approaches for credibility assessment targeting users with high domain knowledge and personal involvement

Life without complex I: proteome analyses of an Arabidopsis mutant lacking the mitochondrial NADH dehydrogenase complex

The mitochondrial NADH dehydrogenase complex (complex I) is of particular importance for the respiratory chain in mitochondria. It is the major electron entry site for the mitochondrial electron transport chain (mETC) and therefore of great significance for mitochondrial ATP generation. We recently described an Arabidopsis thaliana double-mutant lacking the genes encoding the carbonic anhydrases CA1 and CA2, which both form part of a plant-specific 'carbonic anhydrase domain' of mitochondrial complex I. The mutant lacks complex I completely. Here we report extended analyses for systematically characterizing the proteome of the ca1ca2 mutant. Using various proteomic tools, we show that lack of complex I causes reorganization of the cellular respiration system. Reduced electron entry into the respiratory chain at the first segment of the mETC leads to induction of complexes II and IV as well as alternative oxidase. Increased electron entry at later segments of the mETC requires an increase in oxidation of organic substrates. This is reflected by higher abundance of proteins involved in glycolysis, the tricarboxylic acid cycle and branched-chain amino acid catabolism. Proteins involved in the light reaction of photosynthesis, the Calvin cycle, tetrapyrrole biosynthesis, and photorespiration are clearly reduced, contributing to the significant delay in growth and development of the double-mutant. Finally, enzymes involved in defense against reactive oxygen species and stress symptoms are much induced. These together with previously reported insights into the function of plant complex I, which were obtained by analysing other complex I mutants, are integrated in order to comprehensively describe 'life without complex I'.DFG/1186/Br1829/10–