Vorarlberg University of Applied Sciences
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Analytical estimation of maximum amplitude during passage through resonance of a flexible rotor
Full text linkA rotor is a critical component in our modern-day lives and its applications range from heavy-duty industry to transportation and domestic applications. There are two different types of rotors. Rigid rotors operate below their critical speed and flexible rotors operate above at least one of its critical speeds. Flexible rotors possess critical speeds that may lead to large vibration amplitudes during run-up. The maximum radial displacement during passage through resonance is defined by the stiffness, mass and damping of the rotor and its bearings as well as the acceleration of the run-up characteristic. Higher resonance in flexible rotors is caused by low stiffness, rotordynamic and gyroscopic effects, limited damping, shaft support interactions and unbalance acting as an excitation source near critical speeds. The higher the acceleration, the lower the maximum displacement becomes. The underlying equations of motion of a Jeffcott rotor cannot be solved in closed form. An analytical approximation is derived for the maximum radial amplitude during passage through resonance. The derived formula is bench-marked against the exact numerical solution of a specific example. The error percentage between numerical values and analytical values from the derived expression lies below 7.1% for varying angular acceleration and below 13% for varying shaft stiffness, confirming the usefulness of the formula for a first design
Inclusion of carbon pricing into stress testing for the Austrian banking sector
No full textThis paper introduces two approaches for integrating climate-related financial risksinto bank stress testing by translating carbon price projections into parameters forassessing climate risk. The first approach employs a linear model to translate sector-level probability of default changes, derived from external models, to the busi-ness unit level. The second approach directly incorporates the carbon price andemission intensity at the level of the economic category. It captures the interactionbetween carbon pricing, specific emissions profiles for NACE Rev.2 categories,and default risk, allowing for the estimation of vulnerabilities within bank port-folios and providing a basis for ESG considerations. Furthermore, we introduce a’sigmoid’ scenario for carbon price development, bridging the gap between orderlyand disorderly transitions as well as facilitating the exploration of non-linear carbonprice dynamics using economic parameters. Applying these approaches to a sampleportfolio reveals differences in probability of default estimates, underscoring thesignificance of methodological choice
Modellbasierte Optimierung thermischer Quartierspeicher
Full text linkQuartierlösungen spielen eine wichtige Rolle in der Wärmewende, da sie es ermöglichen, Energiesysteme zu konsolidieren und durch größere, effizientere Anlagen sowohl Kosten als auch Energieverbräuche zu reduzieren, während Eigenverbräuche erhöht werden. Laut ver-schiedener Quellen stellen auch modellbasierte Regelungsansätze mit Mixed-Integer Linear Programming einen vielversprechenden Ansatz zur weiteren Optimierung der Steuerung ähnlicher Anlagen dar. Bisher wurde jedoch noch kein Quartiersystem mit einem zentralen Wärmepumpen-Heizsystem gemeinsam mit dezentraler Brauchwasseraufbereitung und ei-ner PV-Anlage modelliert und optimiert. In dieser Arbeit wird zuerst ein reales Quartier model-liert, wobei sowohl reale Messdaten als auch ergänzende synthetische Daten zur Modellbil-dung eingesetzt werden. Zur Erhöhung der Modellgenauigkeit wird ein dynamisches Wärme-pumpenmodell eingeführt, das mithilfe der CoolProp-Bibliothek in Python den Kältekreis durchrechnet, um die Leistungsdaten dynamisch zu berechnen. Das Systemmodell wird mit dem MILP-Solver Gurobi über den gesamten Zeitraum eines Jahres optimiert und anschlie-ßend mit einem mit Hysterese betriebenen System verglichen. Hierbei stellt sich heraus, dass durch die optimierte Steuerung der gesamte Energieverbrauch um 3,74 % reduziert werden konnte, wobei eine Kostenersparnis von 20,81 % erzielt wurde.Neighborhood solutions play a significant role in the energy transition, as they enable the consolidation of energy systems, reducing both costs and energy consumption through larg-er and more efficient systems, while increasing self-consumption. According to various sources, model-based control approaches using Mixed-Integer Linear Programming (MILP) offer a promising method for further optimizing the operation of similar systems. However, to date, no neighborhood system combining a centralized heat pump heating system with de-centralized domestic hot water preparation and a photovoltaic (PV) system has been mod-eled and optimized. In this study, a real neighborhood is first modeled using both real meas-urement data and complementary synthetic data for model development. To improve model accuracy, a dynamic heat pump model is introduced, which uses the CoolProp library in Py-thon to simulate the refrigeration cycle, thereby calculating dynamic coefficients of perfor-mance (COPs) and outputs. The system model is optimized using the MILP solver Gurobi over an entire year and compared to a reference system operated with hysteresis control. The results show that the optimized control reduced total energy consumption by 3,74% and achieved cost savings of 20.81%
Leadership strategies for sustaining team well-being and performance in high-pressure automotive projects
Full text linkThis thesis explores how leadership strategies sustain team well-being and performance in high-pressure project environments within the scope of the multinational automotive industry in Austria and Germany. Under the circumstances of rising competition in the region, supply chain volatility, and increased pressure for efficiency, automotive project teams are today subjected to intense conditions that affect psychological resilience and project success. This paper employs a qualitative case study approach to investigate leadership behaviors and other factors that effectively regulate stress, enhance motivation, and maintain team unity in a dynamic project setting. We conducted thirty semi-structured interviews with leaders and teams from fifteen automotive firms. The analytic approach was Braun and Clarke’s thematic analysis, which was used to study how leadership presence, emotion regulation, communication, and informal team processes build resilience and performance. The findings from the research indicated that emotional presence, early stress detection, individual support, and trust construction of adaptive leadership could help in balancing performance and well-being in high-pressure environments. Team members, on the other side, draw attention to peer support, personal coping strategies, and perceived fairness in leadership behavior to manage pressure effectively. The thesis introduces the PRESSURE Framework as well, consisting of 6 Adaptive Leadership dimensions: Presence, Relational Awareness, Early Detection, Self-Regulation, Support Design, and Uninterrupted Recovery Environment. These dimensions offer actionable guidance for project and functional leaders aiming to transform pressure into a sustainable driver of performance. The research contributes to the understanding of stress-sensitive leadership and calls for a shift from purely technical project leadership to emotionally intelligent, context-aware practices that promote human-centered project success
How virtual collaboration tools influence remote work employees` satisfaction
Full text linkThis study investigates how synchronous and asynchronous digital communication tools affect job satisfaction among remote workers, considering the mediating roles of communication satisfaction, trust, emotional support, and work-life balance. Based on a quantitative, cross-sectional survey of 142 remote employees across 24 countries, findings show that asynchronous communication is positively associated with key psychosocial outcomes and job satisfaction. In contrast, synchronous communication demonstrated no significant positive effects. Gender and age differences were non-significant, while respondents from the DACH region reported higher synchronous tool use than those from Iran. These results highlight the advantages of asynchronous tools in promoting autonomy and mitigating digital fatigue in remote work
Herausforderungen und Chancen einer grenzüberschreitenden ESG-Berichterstattung
No full textIn den letzten Jahren ist die Bedeutung von Sozial- und Governance-Kriterien (ESG) für Wirtschaft, Gesellschaft und Unternehmen enorm gestiegen, da sie die Nachhaltigkeitsleistung reflektieren und das Vertrauen von Investoren, Kunden und der Öffentlichkeit stärken. Dabei spielt ESG-Reporting von Unternehmen eine wichtige Rolle, welches im Jahr 2024 erstmals für viele Unternehmen in der EU und der Schweiz verpflichtend wird. Für ein effektives ESG-Reporting werden qualitativ hochwertige Daten benötigt, deren Sammlung und Austausch oft grenzüberschreitend erfolgt. Dies stellt Unternehmen vor einige Herausforderungen, wie den gesetzlichen Regelungen, der Interoperabilität zwischen Informationssystemen oder der Bereitstellung notwendiger Ressourcen zu entsprechen. Zur Bewältigung dieser Herausforderungen präsentieren wir ein Framework, das auf fünf Dimensionen basiert: Wertschöpfung, Vertrauen, Sicherheit, Kultur sowie Recht und Aufsichtsstrukturen. Es bietet konkrete Anleitungen für einen erfolgreichen grenzüberschreitenden Datenaustausch, indem es den Nutzen von ESG-Daten über das Reporting hinaus betont, die Bedeutung eines einheitlichen Datenstandards für Qualität und Konsistenz hervorhebt und die Rolle des Gesetzgebers bei der Verringerung von Unsicherheiten durch klare Vorgaben unterstreicht. Dieses Framework unterstützt Unternehmen dabei, den gesetzlichen Anforderungen zu entsprechen und ihre Nachhaltigkeitsleistung effektiv zu verbessern
Towards sustainable IoT: space efficiency and serialization speed of data exchange formats
No full textThis study presents a comparison of data exchange formats in terms of space efficiency, serialization speed and usage complexity. A total of 27 data format variants were considered and divided into the categories binary, textual, schema-driven and schema-less. Further, 8 use cases were defined that represent data potentially transferred in IoT applications. In terms of space efficiency, Avro outperformed the other formats in all use cases. Cap'n Proto (packed) generally proved to be faster than the other formats when performing the serialization step. In addition, binary formats performed better than textual formats in terms of space efficiency and serialization speed. The same applies to schema-driven formats, which tend to be more efficient than schema-less formats in terms of both space efficiency and serialization speed. No clear correlations were found between usage complexity and the performance aspects investigated, further justifying the need for a comprehensive collation of data format characteristics that allows for informed decisions in the context of sustainable IoT use cases implementations
