TY - JOUR A1 - Hein, Andreas M. A1 - Eubanks, T. Marshall A1 - Lingam, Manasvi A1 - Hibberd, Adam A1 - Fries, Dan A1 - Schneider, Jean A1 - Kervella, Pierre A1 - Kennedy, Robert A1 - Perakis, Nikolaos A1 - Dachwald, Bernd T1 - Interstellar now! Missions to explore nearby interstellar objects JF - Advances in Space Research N2 - The recently discovered first hyperbolic objects passing through the Solar System, 1I/’Oumuamua and 2I/Borisov, have raised the question about near term missions to Interstellar Objects. In situ spacecraft exploration of these objects will allow the direct determination of both their structure and their chemical and isotopic composition, enabling an entirely new way of studying small bodies from outside our solar system. In this paper, we map various Interstellar Object classes to mission types, demonstrating that missions to a range of Interstellar Object classes are feasible, using existing or near-term technology. We describe flyby, rendezvous and sample return missions to interstellar objects, showing various ways to explore these bodies characterizing their surface, dynamics, structure and composition. Their direct exploration will constrain their formation and history, situating them within the dynamical and chemical evolution of the Galaxy. These mission types also provide the opportunity to explore solar system bodies and perform measurements in the far outer solar system. KW - Interstellar objects KW - Trajectories KW - Missions Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.asr.2021.06.052 SN - 0273-1177 VL - 69 IS - 1 SP - 402 EP - 414 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Ulmer, Jessica A1 - Braun, Sebastian A1 - Cheng, Chi-Tsun A1 - Dowey, Steve A1 - Wollert, Jörg T1 - Usage of digital twins for gamification applications in manufacturing T2 - Procedia CIRP N2 - Gamification applications are on the rise in the manufacturing sector to customize working scenarios, offer user-specific feedback, and provide personalized learning offerings. Commonly, different sensors are integrated into work environments to track workers’ actions. Game elements are selected according to the work task and users’ preferences. However, implementing gamified workplaces remains challenging as different data sources must be established, evaluated, and connected. Developers often require information from several areas of the companies to offer meaningful gamification strategies for their employees. Moreover, work environments and the associated support systems are usually not flexible enough to adapt to personal needs. Digital twins are one primary possibility to create a uniform data approach that can provide semantic information to gamification applications. Frequently, several digital twins have to interact with each other to provide information about the workplace, the manufacturing process, and the knowledge of the employees. This research aims to create an overview of existing digital twin approaches for digital support systems and presents a concept to use digital twins for gamified support and training systems. The concept is based upon the Reference Architecture Industry 4.0 (RAMI 4.0) and includes information about the whole life cycle of the assets. It is applied to an existing gamified training system and evaluated in the Industry 4.0 model factory by an example of a handle mounting. KW - Gamification KW - Digital Twin KW - Support System Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.procir.2022.05.044 SN - 2212-8271 N1 - 55th CIRP Conference on Manufacturing Systems VL - 107 SP - 675 EP - 680 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Dannen, Tammo A1 - Schindele, Benedikt A1 - Prümmer, Marcel A1 - Arntz, Kristian A1 - Bergs, Thomas T1 - Methodology for the self-optimizing determination of additive manufacturing process eligibility and optimization potentials in toolmaking T2 - Procedia CIRP N2 - Additive Manufacturing (AM) of metallic workpieces faces a continuously rising technological relevance and market size. Producing complex or highly strained unique workpieces is a significant field of application, making AM highly relevant for tool components. Its successful economic application requires systematic workpiece based decisions and optimizations. Considering geometric and technological requirements as well as the necessary post-processing makes deciding effortful and requires in-depth knowledge. As design is usually adjusted to established manufacturing, associated technological and strategic potentials are often neglected. To embed AM in a future proof industrial environment, software-based self-learning tools are necessary. Integrated into production planning, they enable companies to unlock the potentials of AM efficiently. This paper presents an appropriate methodology for the analysis of process-specific AM-eligibility and optimization potential, added up by concrete optimization proposals. For an integrated workpiece characterization, proven methods are enlarged by tooling-specific figures. The first stage of the approach specifies the model’s initialization. A learning set of tooling components is described using the developed key figure system. Based on this, a set of applicable rules for workpiece-specific result determination is generated through clustering and expert evaluation. Within the following application stage, strategic orientation is quantified and workpieces of interest are described using the developed key figures. Subsequently, the retrieved information is used for automatically generating specific recommendations relying on the generated ruleset of stage one. Finally, actual experiences regarding the recommendations are gathered within stage three. Statistic learning transfers those to the generated ruleset leading to a continuously deepening knowledge base. This process enables a steady improvement in output quality. KW - Additive manufacturing KW - Laser-Powder Bed Fusion KW - L-PBF KW - Binder Jetting KW - Directed Energy Deposition Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.procir.2022.05.188 SN - 2212-8271 N1 - 55th CIRP Conference on Manufacturing Systems VL - 107 SP - 1539 EP - 1544 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Weiss, Christian A1 - Heslenfeld, Jonas A1 - Saewe, Jasmin Kathrin A1 - Bremen, Sebastian A1 - Häfner, Constantin Leon T1 - Investigation on the influence of powder humidity in Laser Powder Bed Fusion (LPBF) T2 - Procedia CIRP N2 - In the Laser Powder Bed Fusion (LPBF) process, parts are built out of metal powder material by exposure of a laser beam. During handling operations of the powder material, several influencing factors can affect the properties of the powder material and therefore directly influence the processability during manufacturing. Contamination by moisture due to handling operations is one of the most critical aspects of powder quality. In order to investigate the influences of powder humidity on LPBF processing, four materials (AlSi10Mg, Ti6Al4V, 316L and IN718) are chosen for this study. The powder material is artificially humidified, subsequently characterized, manufactured into cubic samples in a miniaturized process chamber and analyzed for their relative density. The results indicate that the processability and reproducibility of parts made of AlSi10Mg and Ti6Al4V are susceptible to humidity, while IN718 and 316L are barely influenced. KW - LPBF KW - Additive Manufacturing KW - Powder Material KW - Humidity Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.procir.2022.08.102 SN - 2212-8271 N1 - Teil der Sonderausgabe: 12th CIRP Conference on Photonic Technologies [LANE 2022] VL - 111 SP - 115 EP - 120 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Monakhova, Yulia A1 - Diehl, Bernd W.K. T1 - Nuclear magnetic resonance spectroscopy as an elegant tool for a complete quality control of crude heparin material JF - Journal of Pharmaceutical and Biomedical Analysis N2 - Nuclear magnetic resonance (NMR) spectrometric methods for the quantitative analysis of pure heparin in crude heparin is proposed. For quantification, a two-step routine was developed using a USP heparin reference sample for calibration and benzoic acid as an internal standard. The method was successfully validated for its accuracy, reproducibility, and precision. The methodology was used to analyze 20 authentic porcine heparinoid samples having heparin content between 4.25 w/w % and 64.4 w/w %. The characterization of crude heparin products was further extended to a simultaneous analysis of these common ions: sodium, calcium, acetate and chloride. A significant, linear dependence was found between anticoagulant activity and assayed heparin content for thirteen heparinoids samples, for which reference data were available. A Diffused-ordered NMR experiment (DOSY) can be used for qualitative analysis of specific glycosaminoglycans (GAGs) in heparinoid matrices and, potentially, for quantitative prediction of molecular weight of GAGs. NMR spectrometry therefore represents a unique analytical method suitable for the simultaneous quantitative control of organic and inorganic composition of crude heparin samples (especially heparin content) as well as an estimation of other physical and quality parameters (molecular weight, animal origin and activity). KW - NMR spectroscopy KW - Heparin KW - Crude heparin KW - USP KW - Ions Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.jpba.2022.114915 SN - 0731-7085 VL - 219 IS - Article number: 114915 PB - Elsevier CY - New York, NY ER - TY - JOUR A1 - Pourshahidi, Ali Mohammad A1 - Engelmann, Ulrich M. A1 - Offenhäusser, Andreas A1 - Krause, Hans-Joachim T1 - Resolving ambiguities in core size determination of magnetic nanoparticles from magnetic frequency mixing data JF - Journal of Magnetism and Magnetic Materials N2 - Frequency mixing magnetic detection (FMMD) has been widely utilized as a measurement technique in magnetic immunoassays. It can also be used for the characterization and distinction (also known as “colourization”) of different types of magnetic nanoparticles (MNPs) based on their core sizes. In a previous work, it was shown that the large particles contribute most of the FMMD signal. This leads to ambiguities in core size determination from fitting since the contribution of the small-sized particles is almost undetectable among the strong responses from the large ones. In this work, we report on how this ambiguity can be overcome by modelling the signal intensity using the Langevin model in thermodynamic equilibrium including a lognormal core size distribution fL(dc,d0,σ) fitted to experimentally measured FMMD data of immobilized MNPs. For each given median diameter d0, an ambiguous amount of best-fitting pairs of parameters distribution width σ and number of particles Np with R2 > 0.99 are extracted. By determining the samples’ total iron mass, mFe, with inductively coupled plasma optical emission spectrometry (ICP-OES), we are then able to identify the one specific best-fitting pair (σ, Np) one uniquely. With this additional externally measured parameter, we resolved the ambiguity in core size distribution and determined the parameters (d0, σ, Np) directly from FMMD measurements, allowing precise MNPs sample characterization. Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.jmmm.2022.169969 SN - 0304-8853 VL - 563 IS - In progress, Art. No. 169969 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Engelmann, Ulrich M. A1 - Pourshahidi, Mohammad Ali A1 - Shalaby, Ahmed A1 - Krause, Hans-Joachim T1 - Probing particle size dependency of frequency mixing magnetic detection with dynamic relaxation simulation JF - Journal of Magnetism and Magnetic Materials N2 - Biomedical applications of magnetic nanoparticles (MNP) fundamentally rely on the particles’ magnetic relaxation as a response to an alternating magnetic field. The magnetic relaxation complexly depends on the interplay of MNP magnetic and physical properties with the applied field parameters. It is commonly accepted that particle core size is a major contributor to signal generation in all the above applications, however, most MNP samples comprise broad distribution spanning nm and more. Therefore, precise knowledge of the exact contribution of individual core sizes to signal generation is desired for optimal MNP design generally for each application. Specifically, we present a magnetic relaxation simulation-driven analysis of experimental frequency mixing magnetic detection (FMMD) for biosensing to quantify the contributions of individual core size fractions towards signal generation. Applying our method to two different experimental MNP systems, we found the most dominant contributions from approx. 20 nm sized particles in the two independent MNP systems. Additional comparison between freely suspended and immobilized MNP also reveals insight in the MNP microstructure, allowing to use FMMD for MNP characterization, as well as to further fine-tune its applicability in biosensing. Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.jmmm.2022.169965 SN - 0304-8853 VL - 563 IS - In progress, Art. No. 169965 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Haeger, Gerrit A1 - Bongaerts, Johannes A1 - Siegert, Petra T1 - A convenient ninhydrin assay in 96-well format for amino acid-releasing enzymes using an air-stable reagent JF - Analytical Biochemistry N2 - An improved and convenient ninhydrin assay for aminoacylase activity measurements was developed using the commercial EZ Nin™ reagent. Alternative reagents from literature were also evaluated and compared. The addition of DMSO to the reagent enhanced the solubility of Ruhemann's purple (RP). Furthermore, we found that the use of a basic, aqueous buffer enhances stability of RP. An acidic protocol for the quantification of lysine was developed by addition of glacial acetic acid. The assay allows for parallel processing in a 96-well format with measurements microtiter plates. Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.ab.2022.114819 SN - 1096-0309 IS - 624 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Kahmann, Stephanie L. A1 - Rausch, Valentin A1 - Plümer, Jonathan A1 - Müller, Lars P. A1 - Pieper, Martin A1 - Wegmann, Kilian T1 - The automized fracture edge detection and generation of three-dimensional fracture probability heat maps JF - Medical Engineering & Physics N2 - With proven impact of statistical fracture analysis on fracture classifications, it is desirable to minimize the manual work and to maximize repeatability of this approach. We address this with an algorithm that reduces the manual effort to segmentation, fragment identification and reduction. The fracture edge detection and heat map generation are performed automatically. With the same input, the algorithm always delivers the same output. The tool transforms one intact template consecutively onto each fractured specimen by linear least square optimization, detects the fragment edges in the template and then superimposes them to generate a fracture probability heat map. We hypothesized that the algorithm runs faster than the manual evaluation and with low (< 5 mm) deviation. We tested the hypothesis in 10 fractured proximal humeri and found that it performs with good accuracy (2.5 mm ± 2.4 mm averaged Euclidean distance) and speed (23 times faster). When applied to a distal humerus, a tibia plateau, and a scaphoid fracture, the run times were low (1–2 min), and the detected edges correct by visual judgement. In the geometrically complex acetabulum, at a run time of 78 min some outliers were considered acceptable. An automatically generated fracture probability heat map based on 50 proximal humerus fractures matches the areas of high risk of fracture reported in medical literature. Such automation of the fracture analysis method is advantageous and could be extended to reduce the manual effort even further. KW - Fracture classification KW - Shoulder KW - Probability distribution mapping KW - Morphing KW - Imaging Y1 - 2022 SN - 1350-4533 VL - 2022 IS - 110 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Schwager, Christian A1 - Flesch, Robert A1 - Schwarzbözl, Peter A1 - Herrmann, Ulf A1 - Teixeira Boura, Cristiano José T1 - Advanced two phase flow model for transient molten salt receiver system simulation JF - Solar Energy N2 - In order to realistically predict and optimize the actual performance of a concentrating solar power (CSP) plant sophisticated simulation models and methods are required. This paper presents a detailed dynamic simulation model for a Molten Salt Solar Tower (MST) system, which is capable of simulating transient operation including detailed startup and shutdown procedures including drainage and refill. For appropriate representation of the transient behavior of the receiver as well as replication of local bulk and surface temperatures a discretized receiver model based on a novel homogeneous two-phase (2P) flow modelling approach is implemented in Modelica Dymola®. This allows for reasonable representation of the very different hydraulic and thermal properties of molten salt versus air as well as the transition between both. This dynamic 2P receiver model is embedded in a comprehensive one-dimensional model of a commercial scale MST system and coupled with a transient receiver flux density distribution from raytracing based heliostat field simulation. This enables for detailed process prediction with reasonable computational effort, while providing data such as local salt film and wall temperatures, realistic control behavior as well as net performance of the overall system. Besides a model description, this paper presents some results of a validation as well as the simulation of a complete startup procedure. Finally, a study on numerical simulation performance and grid dependencies is presented and discussed. KW - Molten salt solar tower KW - Molten salt receiver system KW - Dynamic simulation KW - Two-phase modelling KW - Transient flux distribution Y1 - 2022 U6 - http://dx.doi.org/10.1016/j.solener.2021.12.065 SN - 0038-092X (print) SN - 1471-1257 (online) VL - 232 SP - 362 EP - 375 PB - Elsevier CY - Amsterdam ER -