The 10 most recently published documents
The use of industrial robots allows the precise manipulation of all components necessary for setting up a large-scale particle image velocimetry (PIV) system. The known internal calibration matrix of the cameras in combination with the actual pose of the industrial robots and the calculated transform from the fiducial markers to camera coordinates allow the precise positioning of the individual PIV components according to the measurement demands. In addition, the complete calibration procedure for generating the external camera matrix and the mapping functions for e.g. dewarping the stereo images can be automatically determined without further user interaction and thus the degree of automation can be extended to nearly 100%. This increased degree of automation expands the applications range of PIV systems, in particular for measurement tasks with severe time constraints.
Manufacturing companies are forced to operate in an increasingly volatile and unpredictabl environment. The number of events that can have a potentially critical impact on a production system‘s economic performance have significantly increased. This forces companies to invest considerably more in flexible and robust production systems capable of withstanding a certain amount of change however unable to quantify the benefits in advance. The satisfactory quantification and assessment of these qualities – Flexibility and Robustness –has not been realized yet. This paper discusses commonality between Flexibility and Robustness and offers a new approach to connect changes in the environment with the elements of a production system and thus quantifying its flexibility and robustness.
This paper presents initial findings from aeroelastic studies conducted on a wing-propeller model, aimed at evaluating the impact of aerodynamic interactions on wing flutter mechanisms and overall aeroelastic performance. Utilizing a frequency domain method, the flutter onset within a specified flight speed range is assessed. Mid-fidelity tools with a time domain approach are then used to account for the complex aerodynamic interaction between the propeller and the wing. Specifically, open-source software DUST and MBDyn are leveraged for this purpose. This investigation covers both windmilling and thrusting conditions of the wing-propeller model. During the trim process, adjustments to the collective pitch of the blades are made to ensure consistency across operational points. Time histories are then analyzed to pinpoint flutter onset, and corresponding frequencies and damping ratios are meticulously identified. The results reveal a marginal destabilizing effect of aerodynamic interaction on flutter speed, approximately 5%. Notably, the thrusting condition demonstrates a greater destabilizing influence compared to windmilling. These comprehensive findings enhance the understanding of the aerodynamic behavior of such systems and offer valuable insights for early design predictions and the development of streamlined models for future endeavors.
This paper deals with the problem of determining the optimal capacity of concentrated solar power (CSP) plants, especially in the context of hybrid solar power plants. This work presents an innovative analytical approach to optimizing the capacity of concentrated solar plants. The proposed method is based on the use of additional non-dimensional parameters, in particular, the design factor and the solar multiple factor. This paper presents a mathematical optimization model that focuses on the capacity of concentrated solar power plants where thermal storage plays a key role in the energy source. The analytical approach provides a more complete understanding of the design process for hybrid power plants. In addition, the use of additional factors and the combination of the proposed method with existing numerical methods allows for more refined optimization, which allows for the more accurate selection of the capacity for specific geographical conditions. Importantly, the proposed method significantly increases the speed of computation compared to that of traditional numerical methods. Finally, the authors present the results of the analysis of the proposed system of equations for calculating the levelized cost of electricity (LCOE) for hybrid solar power plants. The nonlinearity of the LCOE on the main calculation parameters is shown
This paper presents initial findings from aeroelastic studies conducted on a wing-propeller model, aimed at evaluating the impact of aerodynamic interactions on wing flutter mechanisms and overall aeroelastic performance. The flutter onset is assessed using a frequency-domain method. Mid-fidelity tools based on the time-domain approach are then exploited to account for the complex aerodynamic interaction between the propeller and the wing. Specifically, the open-source software DUST and MBDyn are leveraged for this purpose. The investigation covers both windmilling and thrusting conditions. During the trim process, adjustments to the collective pitch of the blades are made to ensure consistency across operational points. Time histories are then analyzed to pinpoint flutter onset, and corresponding frequencies and damping ratios are identified. The results reveal a marginal destabilizing effect of aerodynamic interaction on flutter speed, approximately 5%. Notably, the thrusting condition demonstrates a greater destabilizing influence compared to the windmilling case. These comprehensive findings enhance the understanding of the aerodynamic behavior of such systems and offer valuable insights for early design predictions and the development of streamlined models for future endeavors.
Enhancement of succinic acid production by Actinobacillus succinogenes in an electro-bioreactor
(2024)
This work examines the electrochemically enhanced production of succinic acid using the bacterium Actinobacillus succinogenes. The principal objective is to enhance the metabolic potential of glucose and CO2 utilization via the C4 pathway in order to synthesize succinic acid. We report on the development of an electro-bioreactor system to increase succinic acid production in a power-2-X approach. The use of activated carbon fibers as electrode surfaces and contact areas allows A. succinogenes to self-initiate biofilm formation. The integration of an electrical potential into the system shifts the redox balance from NAD+ to NADH, increasing the efficiency of metabolic processes. Mediators such as neutral red facilitate electron transfer within the system and optimize the redox reactions that are crucial for increased succinic acid production. Furthermore, the role of carbon nanotubes (CNTs) in electron transfer was investigated. The electro-bioreactor system developed here was operated in batch mode for 48 h and showed improvements in succinic acid yield and concentration. In particular, a run with 100 µM neutral red and a voltage of −600 mV achieved a yield of 0.7 gsuccinate·gglucose−1. In the absence of neutral red, a higher yield of 0.72 gsuccinate·gglucose−1 was achieved, which represents an increase of 14% compared to the control. When a potential of −600 mV was used in conjunction with 500 µg∙L−1 CNTs, a 21% increase in succinate concentration was observed after 48 h. An increase of 33% was achieved in the same batch by increasing the stirring speed. These results underscore the potential of the electro-bioreactor system to markedly enhance succinic acid production.
The emergence of automotive-grade LiDARs has given rise to new potential methods to develop novel advanced driver assistance systems (ADAS). However, accurate and reliable parking slot detection (PSD) remains a challenge, especially in the low-light conditions typical of indoor car parks. Existing camera-based approaches struggle with these conditions and require sensor fusion to determine parking slot occupancy. This paper proposes a parking slot detection (PSD) algorithm which utilizes the intensity of a LiDAR point cloud to detect the markings of perpendicular parking slots. LiDAR-based approaches offer robustness in low-light environments and can directly determine occupancy status using 3D information. The proposed PSD algorithm first segments the ground plane from the LiDAR point cloud and detects the main axis along the driving direction using a random sample consensus algorithm (RANSAC). The remaining ground point cloud is filtered by a dynamic Otsu’s threshold, and the markings of parking slots are detected in multiple windows along the driving direction separately. Hypotheses of parking slots are generated between the markings, which are cross-checked with a non-ground point cloud to determine the occupancy status. Test results showed that the proposed algorithm is robust in detecting perpendicular parking slots in well-marked car parks with high precision, low width error, and low variance. The proposed algorithm is designed in such a way that future adoption for parallel parking slots and combination with free-space-based detection approaches is possible. This solution addresses the limitations of camera-based systems and enhances PSD accuracy and reliability in challenging lighting conditions.
Additive Manufacturing (AM) is a topic that is becoming more relevant to many companies globally. With AM's progressive development and use for series production, integrating the technology into existing production structures is becoming an important criterion for businesses. This study qualitatively examines the actual state and different perspectives on the integration of AM in production structures. Seven semi-structured interviews were conducted and analyzed. The interview partners were high-level experts in Additive Manufacturing and production systems from industry and science. Four main themes were identified. Key findings are the far-reaching interrelationships and implications of AM within production structures. Specific AM-related aspects were identified. Those can be used to increase the knowledge and practical application of the technology in the industry and as a foundation for economic considerations.
The fourth industrial revolution is on its way to reshape manufacturing and value creation in a profound way. The underlying technologies like cyber-physical systems (CPS), big data, collaborative robotics, additive manufacturing or artificial intelligence offer huge potentials for the optimization and evolution of production systems. However, many manufacturing companies struggle to implement these technologies. This can only in part be attributed to the lack of skilled personal within these companies or a missing digitalization strategy. Rather, there is a fundamental incompatibility between the way current production systems and companies (Industry 3.0) are structured across multiple dimensions compared to what is necessary for industry 4.0. This is especially true in manufacturing systems and their transition towards flexible, decentralized and autonomous value creation networks. This paper shows across various dimensions these incompatibilities within manufacturing systems, explores their reasons and discusses a different approach to create a foundation for Industry 4.0 in manufacturing companies.