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Performance of a low-cost optical particle counter (Alphasense OPC-N3) in estimating size-resolved dust emission flux using eddy covariance
No full textThe recent development of low-cost optical particle counters (OPCs) presents new opportunities for improving spatial coverage of particle concentration in the atmosphere as they are more affordable, compact, and energy efficient than traditional OPCs. In particular, these OPCs could improve our ability to quantify dust emissions in complex environments during aeolian soil erosion. The high-frequency sampling capacity (1 Hz) of some sensors may make them suitable for estimating dust emissions using the eddy-covariance method. Here, the capability of the low-cost OPC-N3 from Alphasense to estimate size-resolved dust flux using the eddy-covariance method is evaluated. During the Jordan Wind erosion And Dust Investigation (J-WADI) experiment, we tested one OPC-N3 against two traditional reference OPCs, the Promo and Fidas, from Palas GmbH. The N3 and Promo OPCs were located in close proximity to a sonic anemometer, enabling the correlation of dust concentration and vertical velocity fluctuations for estimating dust fluxes. Despite the high-temperature and dusty wind conditions of the campaign, the N3 monitored the dynamics and magnitude of dust concentration with reasonable precision. The turbulence characteristics of the dust concentration fluctuations measured by the N3, including variance, skewness, kurtosis, and energy spectrum, were similar to those from the Promo. However, the N3 flow rate exhibited variations under these outdoor conditions that affected the concentration of fine dust particles, and certain particles around 1 µm appeared to be misclassified in the upper size bin. After correcting the N3 dust concentration to address these discrepancies and after calibrating it against a reference OPC, the N3 accurately estimated the dust emission flux, with differences of less than 30 % compared to the reference OPC. Our results confirm the potential of low-cost OPCs for dust erosion research. Nonetheless, further evaluation of low-cost OPCs is still needed across different environments and weather conditions
Performance of a low-cost optical particle counter (Alphasense OPC-N3) in estimating size-resolved dust emission flux using eddy covariance
No full textThe recent development of low-cost optical particle counters (OPCs) presents new opportunities for improving spatial coverage of particle concentration in the atmosphere as they are more affordable, compact, and energy efficient than traditional OPCs. In particular, these OPCs could improve our ability to quantify dust emissions in complex environments during aeolian soil erosion. The high-frequency sampling capacity (1 Hz) of some sensors may make them suitable for estimating dust emissions using the eddy-covariance method. Here, the capability of the low-cost OPC-N3 from Alphasense to estimate size-resolved dust flux using the eddy-covariance method is evaluated. During the Jordan Wind erosion And Dust Investigation (J-WADI) experiment, we tested one OPC-N3 against two traditional reference OPCs, the Promo and Fidas, from Palas GmbH. The N3 and Promo OPCs were located in close proximity to a sonic anemometer, enabling the correlation of dust concentration and vertical velocity fluctuations for estimating dust fluxes. Despite the high-temperature and dusty wind conditions of the campaign, the N3 monitored the dynamics and magnitude of dust concentration with reasonable precision. The turbulence characteristics of the dust concentration fluctuations measured by the N3, including variance, skewness, kurtosis, and energy spectrum, were similar to those from the Promo. However, the N3 flow rate exhibited variations under these outdoor conditions that affected the concentration of fine dust particles, and certain particles around 1 µm appeared to be misclassified in the upper size bin. After correcting the N3 dust concentration to address these discrepancies and after calibrating it against a reference OPC, the N3 accurately estimated the dust emission flux, with differences of less than 30 % compared to the reference OPC. Our results confirm the potential of low-cost OPCs for dust erosion research. Nonetheless, further evaluation of low-cost OPCs is still needed across different environments and weather conditions
Potentiale und Herausforderungen der modellbasierten Zustandsüberwachung von Servopressen
No full textInvestigation on THz response of dielectric substrates for integration and packaging of direct THz detectors
No full textWithin this work, we investigated the response of dielectric materials used in high-frequency laminates, such as Rogers laminates and quartz substrates. A free-space, frequency-domain, non-destructive technique using a continuous-wave THz source was employed in these experiments to provide insights into the material parameters from the experimental results with a focus on the losses induced by these materials in the THz domain (0.02 to 2.5 THz). We extracted the material parameters from the experimental results. The results on the broadband response of materials provide valuable insights for designing novel frequency-selective passive components, which can be used for packaging and integration of THz detectors
Tailored 3D lattice microstructures for enhanced functionality in blood‐gas exchange
No full textCurrent membrane oxygenators for extracorporeal life support (ECLS) are facing their limits regarding gas exchange efficiency and long‐term stability. One aspect adding to these limitations is inhomogeneous blood flow distribution inside the oxygenator's membrane structure. Triply periodic minimal surface (TPMS) lattice structures are proposed to provide increased mass transfer efficiency and local adaptability introducing heterogeneous properties. However, the adaptation of these structures for blood flow, as in ECLS, is challenging as a hemocompatible flow distribution must be established. In this study, this study proposes a novel method for the smooth, multi‐scale modification of TPMS lattice structures creating a tailored flow distribution suited for blood‐gas exchange. It implements this method into an automatic structure optimization within an oxygenator. After manufacturing prototypes, it experimentally evaluate the 3D flow distribution using time‐resolved, contrast enhanced computed tomography comparing the optimized structure to reference geometries. The TPMS structure modification provides a significant change in flow distribution, improving homogeneity by up to 12%. The approach to creating tailored 3D TPMS lattice structures can be directly transferred to various other applications in the field of heat and mass transfer to enhance functionality, e.g., for heat exchangers or membrane contactors
Fluid distribution in artificially manufactured porous mixed-wetting materials as a model for gas diffusion electrodes
No full textHaftung 4.0 – Die Auswirkungen der digitalen Revolution und der Einführung von Smart Products auf die Haftung des Herstellers : eine Analyse der Herstellerhaftung im Bereich der Produkt- und Produzentenhaftung
No full textAn Automated Test Setup to Expose Electronic Components to Repeatable Temperature Shocks Using LN2 Cooling
No full textThis paper presents an approach for the automated stress testing of significant samples of electronic components through the exposure to temperature shocks. The temperature shock is applied by cooling the electronic components mounted on printed circuit boards (PCBs) in liquid nitrogen and heating them using hot air. Using this method, the components experience a temperature delta of more than 300 K at a range from−196 ◦C to 120 ◦C. The test setup is fully automated and can pick up the device under test (DUT) automatically from a magazine. The DUTs are monitored constantly by a data acquisition system during testing. The setup allows the components to be tested under bias and can deliver a current of up to 30 A to the DUT. The presented test setup can be used to conduct accelerated stress testing experiments on a significant sample of electronic components to uncover otherwise difficult to induce degradation mechanisms
Privacy Preservation for Cloud-Edge-Collaborative Energy Management System Using Post-Quantum Homomorphic Encryption
No full textCloud-based energy management systems (EMS) in smart grids face privacy challenges, as existing methods based on traditional homomorphic encryption support limited operations and are vulnerable to quantum attacks. We propose a privacy preservation method for smart grid energy management system, leveraging edge-assisted computing and ring learning with errors (RLWE) homomorphic encryption. Our approach enables both addition and multiplication operations on encrypted smart grid data while defending against quantum threats. We demonstrate the method’s security under the RLWE hardness assumption and validate its effectiveness through an experimental platform simulating smart grid environments. This work addresses computational limitations in current privacy-preserving techniques, enhancing data security for evolving smart grid technologies
Localizing and Mitigating Errors in Long-form Question Answering
No full textLong-form question answering (LFQA) aims to provide thorough and in-depth answers to complex questions, enhancing comprehension. However, such detailed responses are prone to hallucinations and factual inconsistencies, challenging their faithful evaluation. This work introduces HaluQuestQA, the first hallucination dataset with localized error annotations for human-written and model-generated LFQA answers. HaluQuestQA comprises 698 QA pairs with 1.8k span-level error annotations for five different error types by expert annotators, along with preference judgments. Using our collected data, we thoroughly analyze the shortcomings of long-form answers and find that they lack comprehensiveness and provide unhelpful references. We train an automatic feedback model on this dataset that predicts error spans with incomplete information and provides associated explanations. Finally, we propose a prompt-based approach, Error-informed refinement, that uses signals from the learned feedback model to refine generated answers, which we show reduces errors and improves answer quality across multiple models. Furthermore, humans find answers generated by our approach comprehensive and highly prefer them (84%) over the baseline answers