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Nonlinear dynamic analysis of shear- and torsion-free rods using isogeometric discretization and outlier removal
Get PDFIn this paper, we present a discrete formulation of nonlinear shear- and torsion-free rods introduced by Gebhardt and Romero (Acta Mechanica 232(10):3825–3847, 2021) that uses isogeometric discretization and robust time integration. Omitting the director as an independent variable field, we reduce the number of degrees of freedom and obtain discrete solutions in multiple copies of the Euclidean space ℝ³, which is larger than the corresponding multiple copies of the manifold ℝ³×S² obtained with standard Hermite finite elements. For implicit time integration, we choose the same integration scheme as Gebhardt and Romero in (2021) that is a hybrid form of the midpoint and the trapezoidal rules. In addition, we apply a recently introduced approach for outlier removal by Hiemstra et al. (Comput Methods Appl Mech Eng 387:114115, 2021) that reduces high-frequency content in the response without affecting the accuracy, ensuring robustness of our nonlinear discrete formulation. We illustrate the efficiency of our nonlinear discrete formulation for static and transient rods under different loading conditions, demonstrating good accuracy in space, time and the frequency domain. Our numerical example coincides with a relevant application case, the simulation of mooring lines
Phenomenological analysis of the electrical behavior of helical gears to identify sensory utilizable effects for condition monitoring approaches
Get PDFIn this contribution the electrical behavior of helical gear contacts is investigated. The investigation is based on impedance measurements obtained on an industrial gearbox test bench. The results are analyzed to identify the qualitative influence of rotation speed, load, rotation direction, load direction and surface alterations. Furthermore, potentials and limitations of utilizing the electrical behavior of helical gear contacts for condition monitoring applications are discussed. The investigations show that the lubrication condition can be qualitatively identified based on the characteristics of the electrical behavior of the gear contact. Important influencing factors for the lubrication film thickness and consequently the impedance of the gear contact can be determined to be rotation speed and load but also rotation and load direction. Surface alterations like damages but also tooth pitch deviations in the region of single digit micrometers can be seen to have a measurable influence on the impedance signal of the gear contact. These effects can potentially be used for condition monitoring approaches. However, the ambiguity of the impedance signal due to the high number of influencing factors remains a limitation of this new measurement method. Another factor for the ambiguity of the impedance signal is the simultaneous contact of multiple teeth which are not distinguishable in the impedance signal. This contribution shows the potentials and limitations for the sensory utilization of the electrical behavior of helical gear contacts and highlights novel research gaps
Accurate Modeling of Thermal Losses in Heating Networks for Efficient Operational Planning
Get PDFIn this paper we present a simplified nonlinear modeling approach for thermal losses in heating pipes that closely approximates the behavior of models with exponential heat loss function throughout the entire operational range. Our approach enables accurate modeling of part-load operation as well as nonlinear modeling without the need to fix the direction of flow. Our approach is suited for use in district heating system models with multiple suppliers at different locations in the grid, where flow directions are not necessarily known beforehand. It can be solved with modern standard optimization algorithms. We compare our model to different common approaches using an illustrative case and discuss model quality
Surgical phase recognition by learning phase transitions
Get PDFAutomatic recognition of surgical phases is an important component for developing an intra-operative context-aware system. Prior work in this area focuses on recognizing short-term tool usage patterns within surgical phases. However, the difference between intra- and inter-phase tool usage patterns has not been investigated for automatic phase recognition. We developed a Recurrent Neural Network (RNN), in particular a state-preserving Long Short Term Memory (LSTM) architecture to utilize the long-term evolution of tool usage within complete surgical procedures. For fully automatic tool presence detection from surgical video frames, a Convolutional Neural Network (CNN) based architecture namely ZIBNet is employed. Our proposed approach outperformed EndoNet by 8.1% on overall precision for phase detection tasks and 12.5% on meanAP for tool recognition tasks
Crack development in an old church building due to clay shrink-swell
Get PDFCracking is a common occurrence in any building. Where they occur in historic
buildings, however, they present a greater concern due to the structure’s cultural significance. A
common reason for cracking is the ground movement beneath foundations as a result of shrinkswell
in clay subsoils. In this paper, we present a shrink-swell case that is causing the progressive
movement and cracking of a centuries-old church, the Massenheim Evangelical Church in Hessen,
Germany. Results of field and laboratory investigations reveal a layer of very highly expansive
clay. The upper part of this layer appears to be within the active zone, and therefore subject
to volume change with seasonal fluctuations in water content. The development of cracks with
time is aligned with the prevailing climatic conditions during the observation period. A possible
mitigation measure is the use of micropiles that bypass that part of the layer that lies within the active
zone
The Authorship of Stephen King’s Books Written Under the Pseudonym “Richard Bachman”: A Stylometric Analysis
Get PDFBetween 1977 and 1984, Stephen King published five novels under the
pseudonym “Richard Bachman”. Reviewers noted similarities between King’s
and Bachman’s writing styles when Thinner (1984) was published, ultimately
leading to King’s unmasking. We investigate, using the Juola protocol, whether
computational techniques can correctly identify King as the author of the Bachman
books out of a selection of contemporary candidate authors – Dean Koontz,
Peter Straub, and Thomas Harris. We also perform a post-hoc analysis of the use
of pop-culture references and brand names in Bachman, King, Koontz, Straub,
and Harris novels, based on comments in reviews of Bachman and King novels.
The references extracted from the Bachman books occurred significantly
more often in King’s texts than in the others’, showing that attentive readers
could have “heard King’s voice” in the Bachman books through what a reviewer
denigratingly called King’s “compulsion to list brand-name products and his
affinity for pop-cult teenage junk”. These results contribute to the vexed issue of
explainability, which is a recurrent challenge in author identification for literary
texts
GPU-Accelerated Solution of Many Small ODE Systems for High-Temperature Component Lifetime Modeling
Get PDFAccurate lifetime prediction of critical components in steam and gas turbines is essential for optimizing maintenance strategies and ensuring safe operation under demanding conditions. Traditional engineering methods, though quick, lack the flexibility and precision required for complex scenarios. Advanced continuum damage mechanics models, such as the Chaboche model, offer greater accuracy but are computationally intensive.
This thesis investigates the potential of GPU acceleration to significantly reduce the computational cost of lifetime estimation using the Chaboche model. By leveraging the parallel processing capabilities of GPUs, the study enables efficient simulation of numerous load cases and parameter configurations, addressing uncertainties inherent in such models. We evaluate the suitability of SUNDIALS, a state-of-the-art ODE solver, for GPU-accelerated simulations, highlighting its limitations. Simpler numerical methods, including the Forward Euler method, are also explored to balance accuracy and computational efficiency. Performance enhancements are achieved by optimizing data types and step sizes, improving the efficiency of both SUNDIALS and the Forward Euler method on GPU platforms.
The results demonstrate substantial computational speedups of 40 to 60 times with GPU-accelerated solvers compared to CPU-based implementations. Additionally, optimizing the simplified Chaboche model with tailored data types and step sizes yields a further 23% performance improvement without compromising accuracy. This research offers key insights into the effective application of GPU acceleration for lifetime prediction, contributing to more efficient and reliable design and maintenance practices for critical components in energy systems
Gradient‐based eigenvalue optimization for electromagnetic cavities with built‐in mode matching
Get PDFShape optimization with respect to eigenvalues of a cavity plays an important role in the design of new resonators or in the optimization of existing ones. This paper proposes a gradient‐based optimization scheme, which is enhanced with closed‐form shape derivatives of the system matrices. Based on these, accurate derivatives of eigenvalues, eigenmodes, and the cost function can be computed with respect to the geometry, which significantly reduces the computational effort of the optimizer. The work is demonstrated by applying it to the 9‐cell TESLA cavity, for which the design parameters of the computational model are considered as optimization variables to match the design criteria for devices in realistic use cases. Since eigenvalues may cross during the shape optimization of a cavity, a new algorithm based on an eigenvalue matching procedure is proposed, to ensure the optimization of the desired mode in order to also enable successful matching along large shape variations
Convergence rate of a penalty method for strongly convex problems with linear constraints
Get PDFWe consider an optimization problem with strongly convex objective and linear inequalities constraints. To be able to deal with a large number of constraints we provide a penalty reformulation of the problem. As penalty functions we use a version of the one-sided Huber losses. The smoothness properties of these functions allow us to choose time-varying penalty parameters in such a way that the incremental procedure with the diminishing step-size converges √ to the exact solution with the rate O(1/√k). To the best of our knowledge, we present the first result on the convergence rate for the penalty-based gradient method, in which the penalty parameters vary with time
Das FuN Screen-Prinzip zur experimentellen Analyse von Nanoporen in E. coli
Get PDFNanopores constitute an important class of biotechnologically relevant proteins. Unlike binders and enzymes, their experimental characterization is limited to high-resolution, yet low throughput biophysical methods. Addressing this technological gap, the functional nanopore (FuN) screen now provides a versatile assay to study and engineer nanopores in Escherichia coli combining quantitative resolution with the ease, scalability, and throughput of cellular assays