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Rotordynamics of a Single-Stage Brush Seal in Isolation:The Effects of Variable Stiffness and Back Plate Geometry
Get PDFBrush seals control leakage around rotating components from areas of high to low pressure inside turbomachinery. They are known to contribute to the overall stability of gas turbines, therefore their dynamic behavior is of particular importance to engine designers. Despite this, limited research exists in the literature on the rotordynamic behavior of brush seals. This paper aims to experimentally characterize the leakage and rotordynamic performance of two seals with different bristle diameters tested with both conventional and pressure-relieved back plates with a slight interference. A dynamic test facility was utilized to study the dynamic characteristics of an isolated seal with changes in excitation frequency, rotational speed, and pressure drop. Seal leakage increased with bristle diameter and with the use of the pressure-relieved back plate but reduced with increasing rotational speed for all tests. The direct dynamic coefficients were shown to increase with pressure difference. The back plate geometry influenced the change in stiffness coefficient with rotational speed. The larger bristle diameter resulted in a stiffer seal, however, the damping coefficient reduced with the reduction in packing density. The insight provided by these results will help inform engine manufacturers on the suitability of implementing brush seals in future gas turbine designs
Multi-Template Molecularly Imprinted Polymeric Electrochemical Biosensors
Get PDFDual- or multi-template molecularly imprinted polymers have been an attractive research field for many years as they allow simultaneous detection of more than one target with high selectivity and sensitivity by creating template-specific recognition sites for multiple targets on the same functional monomer. Dual/multi-template molecular imprinting techniques have been applied to identify, extract, and detect many targets, from heavy metal ions to viruses, by different methods, such as high-performance liquid chromatography (HPLC), liquid chromatography–mass spectrometry (LC-MS), and piezoelectric, optical, and electrochemical methods. This article focuses on electrochemical sensors based on dual/multi-template molecularly imprinted polymers detecting a wide range of targets by electrochemical methods. Furthermore, this work highlights the use of these sensors for point-of-care applications, their commercialization and their integration with microfluidic systems
Generative Modeling of Lévy Area for High Order SDE Simulation
Get PDFIt is well known that when numerically simulating solutions_to stochastic differential equations (SDEs), achieving a strong convergence rate better than (Formula presented) (where h is the step-size) usually requires the use of certain iterated integrals of Brownian motion, commonly referred to as its ``Lévy areas,̎ However, these stochastic integrals are difficult to simulate due to their non-Gaussian nature. and for a d-dimensional Brownian motion with d > 2, no fast almost-exact sampling algorithm is known. In this paper, we propose LévyGAN, a deep-learning-based model for generating approximate samples of Lévy area conditional on a Brownian increment. Due to our ``bridge-flipping̎ operation, the output samples match all joint and conditional odd moments exactly. Our generator employs a tailored graph neural network (GNN)-inspired architecture, which enforces the correct dependency structure between the output distribution and the conditioning variable. Furthermore, we incorporate a mathematically principled characteristic-function-based discriminator. Lastly, we introduce a novel training mechanism, termed ``Chen-training,̎ which circumvents the need for expensive-to-generate training data-sets. This new training procedure is underpinned by our two main theoretical results. For four-dimensional Brownian motion, we show that LévyGAN exhibits state-of-the-art performance across several metrics which measure both the joint and marginal distributions. We conclude with a numerical experiment on the log-Heston model, a popular SDE in mathematical finance, demonstrating that a high-quality synthetic Lévy area can lead to high order weak convergence and variance reduction when using multilevel Monte Carlo (MLMC).</p
Structure of alkali magnesium, zinc, and calcium metasilicate glasses
Get PDFThe structure of the metasilicate composition glasses (A2O)x(XO)0.50−x(SiO2)0.50, with A = Na or K, X = Mg, Zn, or Ca, and x = 0.25 or 0.33, was investigated by combining neutron and high-energy x-ray diffraction with Raman scattering and 29Si and 25Mg magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy. The latter employed the rotor-assisted population transfer approach for signal enhancement. The diffraction results show a substantial population of four-coordinated X2+ cations in the majority of the magnesium- and zinc-bearing glasses. Based on the average degree of polymerization of the silicate networks obtained from the solid-state 29Si NMR results, and supported by the findings from Raman spectroscopy, no compelling evidence could be found for a network-forming role for the four-coordinated Mg2+ and Zn2+ species. The relationship between the Mg–O coordination numbers measured by diffraction and the mean isotropic chemical shifts found from 25Mg MAS NMR spectroscopy is considered for a variety of silicate glasses. A clear correlation between these parameters could not be found
Higher Education Reform in Roman Catholic Ecclesiastical Institutions:Responses from French Institutions to Quality Management Imperatives
Get PDFThis study aims to observe and explain how Roman Catholic higher education institutions in France are adapting to the Holy See’s modernization agenda through quality assurance (QA). Using a mixed-method research design, the study aims to unearth differences in policy implementation, and to understand these differences through the lens of organizational ambidexterity. In particular, it will look at managerial actions influencing the level of adaptation to change of the institutions. The findings of this research in-progress will contribute to the under-researched area of ecclesiastical higher education, and to the organizational ambidexterity literature in a non-business environment. Understanding the factors influencing QA implementation will benefit practitioners but also policy-makers working on future regulations across the globe
Zero-shot CLIP Class Forgetting via Text-image Space Adaptation
Get PDFEfficient class forgetting has attracted significant interest due to the high computational cost of retraining models from scratch whenever classes need to be forgotten. This need arises from data privacy regulations, the necessity to remove outdated information, and the possibility to enhance model robustness and security. In this paper we address class forgetting in vision-language CLIP model. Modern class forgetting methods for CLIP have demonstrated that zero-shot forgetting is achievable by generating synthetic data and fine-tuning both visual and textual encoders with a regularization loss. Our approach shows that class forgetting in CLIP can be accomplished in a zero-shot manner without any visual data by adapting the shared vision-text space of CLIP, thereby making the class forgetting process more efficient. Our method delivers superior results, demonstrating strong performance and complete class removal, regardless of the visual encoder used in CLIP. Furthermore, we explore what exactly is being targeted by the class forgetting algorithm discovering some interesting properties of CLIP features. Full implementation can be found here.</p
Higher Education Reform in Roman Catholic Ecclesiastical Institutions:Responses from French Institutions to Quality Management Imperatives
Get PDFThis study aims to observe and explain how Roman Catholic higher education institutions in France are adapting to the Holy See’s modernization agenda through quality assurance (QA). Using a mixed-method research design, the study aims to unearth differences in policy implementation, and to understand these differences through the lens of organizational ambidexterity. In particular, it will look at managerial actions influencing the level of adaptation to change of the institutions. The findings of this research in-progress will contribute to the under-researched area of ecclesiastical higher education, and to the organizational ambidexterity literature in a non-business environment. Understanding the factors influencing QA implementation will benefit practitioners but also policy-makers working on future regulations across the globe
ChemEngML/MP_FO_ML: MP_FO Scripts
No full textAI-assisted Prediction & Optimization of Micropollutants Removal with Forward Osmosis Membranes — this repo provides the curated dataset (642 experiments across 17 commercial/lab-fabricated FO membranes and 102 micropollutants, with standardized chemical, membrane, and process descriptors in Dataset.csv) plus the Python scripts used to train, tune, and interpret the GBR and ANN models for water flux and rejection-rate prediction
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