Prospective Life Cycle Assessment of Biological Methanation in a Trickle-Bed Pilot Plant and a Potential Scale-Up

The fluctuating nature of renewable energies results in the need for sustainable storage technologies to defossilize the energy system without other negative consequences for humans and the environment. In this study, a pilot-scale trickle-bed reactor for biological methanation and various scale-up scenarios for 2024 and 2050 were investigated using life cycle assessment. A best- and worst-case scenario for technology development until 2050 was evolved using cross-consistency analysis and a morphological field, based on which the data for the ecological models were determined. The results show that the plant scale-up has a very positive effect on the ecological consequences of methanation. In the best-case scenario, the values are a factor of 23–780 lower than those of the actual plant today. A hot-spot analysis showed that electrolysis operation has an especially large impact on total emissions. The final Monte Carlo simulation shows that the technology is likely to achieve a low global warming potential with a median of 104.0 kg CO2-eq/MWh CH4 and thus can contribute to decarbonization

QCEDA: Using Quantum Computers for EDA

The field of Electronic Design Automation (EDA) is crucial for microelectronics, but the increasing complexity of Integrated Circuits (ICs) poses challenges for conventional EDA: Corresponding problems are often NP-hard and are therefore in general solved by heuristics, not guaranteeing optimal solutions. Quantum computers may offer better solutions due to their potential for optimization through entanglement, superposition, and interference. Most of the works in the area of EDA and quantum computers focus on how to use EDA for building quantum circuits. However, almost no research focuses on exploiting quantum computers for solving EDA problems. Therefore, this paper investigates the feasibility and potential of quantum computing for a typical EDA optimization problem broken down to the Min-k-Union problem. The problem is mathematically transformed into a Quadratic Unconstrained Binary Optimization (QUBO) problem, which was successfully solved on an IBM quantum computer and a D-Wave quantum annealer

Compliant Robotic Arm based on a Tensegrity Structure with x-shaped Members

The use of intrinsically compliant tensegrity structures in manipulation systems is an attractive research topic. In this paper a 3D compliant robotic arm based on a stacked tensegrity structure consisting of x-shaped rigid members is considered. The rigid members are interconnected by a net of prestressed, tensioned members with pronounced intrinsic elasticity and by inelastic tensioned members. The system's motion is achieved by length-change of the inelastic tensioned members. The operating principle of the system is discussed with the help of kinematic considerations and verified by experiments

Theoretical Investigations on a Dynamic Hand Orthosis Based on a Prestressed Compliant Structure with Respect to Stiffness and Wrist-Forces

Many currently available dynamic hand orthoses use articulated connections that have one degree of freedom, such as hinge joints. These orthoses are therefore only able to replicate the multiaxial range of motion of the human hand to a limited extent. A possible solution for replecating the multiaxial movements of the hand is the use of pre-stressed compliant structures as a basis for the orthoses. After a brief description of this concept, the two main first steps by the development, the so called form-finding and the wrist-joint force characterization by hand movements are explained with theoretical analysis based on the static Finite Element Method. The influence of the orthosis parameters, global stiffness and geometric dimensions as well as the influence of the wrist-joint position relative to the orthosis are discussed. Finally, the next planned development steps towards to the first prototype are outlined

„Analog Discovery 2“ mobiles Praktikum OTH Regensburg

Allen Studierenden wird zu Beginn des zweiten Semesters ein elektronisches Experimentierset mit einem Analog Discovery als „mobiles Praktikum“ für die gesamte Dauer des Studiums ausgeliehen. Im Rahmen der Lehrinnovationsprofessur (LIP) wird Material für möglichst viele verschiedene Module des Studiengangs entwickelt, um Fachwissen praktisch erfahrbar zu machen und gleichzeitig die Module inhaltlich zu verknüpfen

Analyzing the Impact of Redaction on Document Classification Performance of Deep CNN Models

Many companies are facing growing data archives leading to an increasing focus on the automated classification of documents in corporate processes. Due to data protection guidelines, development with clear data is often difficult. One way to overcome this difficulty is to desensitize documents using document redaction. The following study, therefore, examines the impact of redaction on the document classification performance of a deep CNN model by analyzing how the classifica- tion performance deteriorates when the model is trained on unredacted documents and evaluated on redacted data (unredacted model) or trained on redacted data and applied to unredacted documents (redacted model). For the former condition, a loss in accuracy of 2.56%P was found and a loss of 2.08%P for the latter. We were also able to show that the loss in performance differed greatly between document classes and was influenced by their proportion of redacted area (unredacted model: r=0.31; redacted model: r=0.87). For the model trained with redacted and evaluated on unredacted data, we also determined that the decrease in classification accu- racy was affected by the intra-class variability of the redacted area (r=0.74). From these results, recommendations for dealing with redacted data in document classification systems are derived

Vom Boden zur Wand - Stand der Technik und zukünftige Entwicklungen

Lehm selbst ist ein Baustoff mit zahlreichen Vorteilen (diffusionsoffen, wiederverwendbar, hohe Verfügbarkeit, geringe graue Emissionen, guter Schallschutz und hohe Dauerhaftigkeit bei fachgerechtem Einsatz), aber auch Grenzen in der Anwendbarkeit, die sich aus Schwund, begrenzter Lastaufnahme und hoher Wärmeleitfähigkeit (und damit geringer Wärmedämmwirkung) ergeben. Aus Lehm und damit aus Boden Wandbaustoff zu fertigen, funktioniert sowohl im Bereich des Trockenausbaus (Lehmbauplatten, Lehmputz) als auch des tragendes Mauerwerks sehr gut und gewinnt durch die kürzlich eingeführten Normen an neuem Aufschwung. Die tragende Stampflehmbauweise mit lokal ausgehobenem Material ist bedingt durch den hohen handwerklichen Aufwand bei gleichzeitigem Fachkräftemangel und erforderlichen Zustimmung im Einzelfall oder vorhabensbezogener Bauartgenehmigung kosten- und zeitintensiv. Dabei bringt sie bauphysikalisch und ökologisch häufig signifikante Vorteile im Vergleich zu konventionellen Bauweisen mit sich. Dieser Beitrag stellt daher anhand einer ausführlichen Literaturrecherche und eigenen Versuchen den Stand der Technik industrieller Lehmbaustoffe dar. Fokus des Beitrags liegt auf Möglichkeiten, die Stampflehmbauweise zu neuer und wirtschaftlicher Leistungsfähigkeit zu bringen

Preparation methodology for the microstructural characterization of diffusion layers in a titanium/steel composite

Hot pressing of titanium and carbon steel leads to the formation of a diffusion layer at the interface. Depending on the carbon content of the steel used, it either exclusively contains TiC or additional other phases. In the case of steel with a medium carbon concentration (0.67 wt.% C), a pure TiC layer forms. A preparation methodology was developed to make statements about functional and microstructural properties of the respective layers such as layer thickness, porosity, or grain size. However, apart from the diffusion layer’s microstructure, it also reveals the microstructure of the two base substrates. A comparison based on electron backscatter diffraction (EBSD) examinations yields similar results in terms of microstructure. A micrograph analysis based on the new preparation methodology also allows confirming the element distribution measurement by glow discharge optical emission spectroscopy (GDOES). The methodology therefore provides a way of quickly and reliably controlling the layer formation during the hot pressing process of titanium and carbon steel.Beim Heißpressen von Titan und Kohlenstoffstahl entsteht an der Grenzfläche eine Diffusionsschicht, welche abhängig vom Kohlenstoffgehalt des verwendeten Stahls entweder ausschließlich TiC oder zusätzliche andere Phasen enthält. Im Fall eines Stahls mit mittlerer Kohlenstoffkonzentration (0,67 wt.-% C) bildet sich eine reine TiC-Schicht. Um eine Aussage über die funktionalen und mikrostrukturellen Eigenschaften, wie Schichtdicke, Porosität oder Korngröße, entsprechender Schichten treffen zu können, wurde eine Präparationsmethodik entwickelt. Hierbei wird jedoch nicht nur das Gefüge der Diffusionsschicht, sondern auch das der beiden Grundsubstrate entwickelt. Ein Vergleich mit Elektronenrückstreubeugungs-Untersuchungen (EBSD) liefert hinsichtlich der Mikrostruktur vergleichbare Ergebnisse. Auch die Messung der Elementverteilung durch Glimmentladungsspektroskopie (GDOES) kann durch eine Schliffbildanalyse unter Anwendung der neuen Präparationsmethodik belegt werden. Die Methodik stellt also eine Möglichkeit zur schnellen und sicheren Kontrolle der Schichtbildung beim Heißpressen von Titan und Kohlenstoffstahl dar

Towards View-based Development of Quantum Software

Quantum computing is an interdisciplinary field that relies on the expertise of many different stakeholders. The views of various stakeholders on the subject of quantum computing may differ, thereby complicating communication. To address this, we propose a view-based quantum development approach based on a Single Underlying Model (SUM) and a supporting quantumIntegrated Development Environment (IDE). We highlight emerging challenges for future research

Hype or Heuristic? Quantum Reinforcement Learning for Join Order Optimisation

Identifying optimal join orders (JOs) stands out as a key challenge in database research and engineering. Owing to the large search space, established classical methods rely on approximations and heuristics. Recent efforts have successfully explored reinforcement learning (RL) for JO. Likewise, quantum versions of RL have received considerable scientific attention. Yet, it is an open question if they can achieve sustainable, overall practical advantages with improved quantum processors. In this paper, we present a novel approach that uses quantum reinforcement learning (QRL) for JO based on a hybrid variational quantum ansatz. It is able to handle general bushy join trees instead of resorting to simpler left-deep variants as compared to approaches based on quantum(-inspired) optimisation, yet requires multiple orders of magnitudes fewer qubits, which is a scarce resource even for post-NISQ systems. Despite moderate circuit depth, the ansatz exceeds current NISQ capabilities, which requires an evaluation by numerical simulations. While QRL may not significantly outperform classical approaches in solving the JO problem with respect to result quality (albeit we see parity), we find a drastic reduction in required trainable parameters. This benefits practically relevant aspects ranging from shorter training times compared to classical RL, less involved classical optimisation passes, or better use of available training data, and fits data-stream and low-latency processing scenarios. Our comprehensive evaluation and careful discussion delivers a balanced perspective on possible practical quantum advantage, provides insights for future systemic approaches, and allows for quantitatively assessing trade-offs of quantum approaches for one of the most crucial problems of database management systems