52221 research outputs found

    Optimum filter-based analysis for the characterization of a high-resolution magnetic microcalorimeter towards the DELight experiment

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    Ultra-sensitive cryogenic calorimeters have become a favored technology with widespread application where eV-scale energy resolutions are needed. In this article, we characterize the performance of an X-ray magnetic microcalorimeter (MMC) using a Fe-55 source. Employing an optimum filter-based amplitude estimation and energy reconstruction, we demonstrate that an unprecedented FWHM resolution of ΔEFWHM=(1.25±0.17(stat)0.07+0.05(syst))eVΔE_{FWHM}=(1.25±0.17(stat)^{+0.05}_{−0.07}(syst))eV can be achieved. We also derive the best possible resolution and discuss limiting factors affecting the measurement. The analysis pipeline for the MMC data developed in this paper is furthermore an important step for the realization of the proposed superfluid helium-based experiment DELight, which will search for direct interaction of dark matter with masses below 100 MeV/c2^2

    Some remarks on load modeling in nonlinear structural analysis–Statics with large deformations–Consistent treatment of follower load effects and load control

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    Load modeling in nonlinear statics, particularly incorporating large deformations differs significantly from the treatment in linear analysis. As in structural dynamics masses in a gravity field generate the loading, their location, and their modifications within the deformation process must be considered in a nonlinear simulation. A specific view besides loading by masses is on gas and fluid interaction with structures. In addition, load control using specifically designed algorithms is evaluated with respect to realistic applications. Within the load modeling an unavoidable, however side aspect, is the general discussion about the so-called follower forces and non-conservative loading. As an example of real-world applications, the specifics of inflated rubber dams are presented

    Vision through Obstacles—3D Geometric Reconstruction and Evaluation of Neural Radiance Fields (NeRFs)

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    In this contribution we evaluate the 3D geometry reconstructed by Neural Radiance Fields (NeRFs) of an object’s occluded parts behind obstacles through a point cloud comparison in 3D space against traditional Multi-View Stereo (MVS), addressing the accuracy and completeness. The key challenge lies in recovering the underlying geometry, completing the occluded parts of the object and investigating if NeRFs can compete against traditional MVS for scenarios where the latter falls short. In addition, we introduce a new “obSTaclE, occLusion and visibiLity constrAints” dataset named STELLA concerning transparent and non-transparent obstacles in real-world scenarios since there is no existing dataset dedicated to this problem setting to date. Considering that the density field represents the 3D geometry of NeRFs and is solely position-dependent, we propose an effective approach for extracting the geometry in the form of a point cloud. We voxelize the whole density field and apply a 3D density-gradient based Canny edge detection filter to better represent the object’s geometric features. The qualitative and quantitative results demonstrate NeRFs’ ability to capture geometric details of the occluded parts in all scenarios, thus outperforming in completeness, as our voxel-based point cloud extraction approach achieves point coverage up to 93%. However, MVS remains a more accurate image-based 3D reconstruction method, deviating from the ground truth 2.26 mm and 3.36 mm for each obstacle scenario respectively

    GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system

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    A geospatial data processing tool, GEO4PALM, has been developed to generate geospatial static input for the Parallelized Large-Eddy Simulation (PALM) model system. PALM is a community-driven large-eddy simulation model for atmospheric and environmental research. Throughout PALM\u27s 20-year development, research interests have been increasing in its application to realistic conditions, especially for urban areas. For such applications, geospatial static input is essential. Although abundant geospatial data are accessible worldwide, geospatial data availability and quality are highly variable and inconsistent. Currently, the geospatial static input generation tools in the PALM community heavily rely on users for data acquisition and pre-processing. New PALM users face large obstacles, including significant time commitments, to gain the knowledge needed to be able to pre-process geospatial data for PALM. Expertise beyond atmospheric and environmental research is frequently needed to understand the data sets required by PALM. Here, we present GEO4PALM, which is a free and open-source tool. GEO4PALM helps users generate PALM static input files with a simple, homogenised, and standardised process. GEO4PALM is compatible with geospatial data obtained from any source, provided that the data sets comply with standard geo-information formats. Users can either provide existing geospatial data sets or use the embedded data interfaces to download geo-information data from free online sources for any global geographic area of interest. All online data sets incorporated in GEO4PALM are globally available, with several data sets having the finest resolution of 1 m. In addition, GEO4PALM provides a graphical user interface (GUI) for PALM domain configuration and visualisation. Two application examples demonstrate successful PALM simulations driven by geospatial input generated by GEO4PALM using different geospatial data sources for Berlin, Germany, and Ōtautahi / Christchurch, New Zealand. GEO4PALM provides an easy and efficient way for PALM users to configure and conduct PALM simulations for applications and investigations such as urban heat island effects, air pollution dispersion, renewable energy resourcing, and weather-related hazard forecasting. The wide applicability of GEO4PALM makes PALM more accessible to a wider user base in the scientific community

    Temperature, humidity, and ionisation effect of iodine oxoacid nucleation

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    Iodine oxoacids are recognised for their significant contribution to the formation of new particles in marine and polar atmospheres. Nevertheless, to incorporate the iodine oxoacid nucleation mechanism into global simulations, it is essential to comprehend how this mechanism varies under various atmospheric conditions. In this study, we combined measurements from the CLOUD (Cosmic Leaving OUtdoor Droplets) chamber at CERN and simulations with a kinetic model to investigate the impact of temperature, ionisation, and humidity on iodine oxoacid nucleation. Our findings reveal that ion-induced particle formation rates remain largely unaffected by changes in temperature. However, neutral particle formation rates experience a significant increase when the temperature drops from +10 °C to −10 °C. Running the kinetic model with varying ionisation rates demonstrates that the particle formation rate only increases with a higher ionisation rate when the iodic acid concentration exceeds 1.5 × 107^7 cm3^{−3} , a concentration rarely reached in pristine marine atmospheres. Consequently, our simulations suggest that, despite higher ionisation rates, the charged cluster nucleation pathway of iodic acid is unlikely to be enhanced in the upper troposphere by higher ionisation rates. Instead, the neutral nucleation channel is likely to be the dominant channel in that region. Notably, the iodine oxoacid nucleation mechanism remains unaffected by changes in relative humidity from 2% to 80%. However, under unrealistically dry conditions (below 0.008% RH at +10 °C), iodine oxides (I2_2O4_4 and I2_2O5_5) significantly enhance formation rates. Therefore, we conclude that iodine oxoacid nucleation is the dominant nucleation mechanism for iodine nucleation in the marine and polar boundary layer atmosphere

    Broadband Circuits for High-Speed Short Reach Optical Transceivers

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    The DataHubCommunity – fosteringFAIR and sustainable research data management across our research field

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    The DataHub of the Research Field Earth and Environment is a joint initiative of all centers of the Helmholtz Association participating in the research program \u27Changing Earth’. Within the DataHub, data management tools are developed and made available, and data products are offered in thematic viewers. The continuous and long-term development process of these solutions is the DataHub\u27s task. The here published poster has been presented during the General Assembly of the Program "Changing Earth - Sustaining our Future" (May 15-16, 2023) in Karlsruhe

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