bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid adiabatic pulse with asymmetry (HAPY): An asymmetric adiabatic pulse with an application in pulsed arterial spin labeling at 7T
Authors: Chi Didi , Blunck Yasmin , Glarin Rebecca , Davey Catherine E. , Zhang Xianyi , Stäb Daniel , Pfeuffer Josef , Johnston Leigh A. , Jin Jin 
Published: March 2023

PurposeA new class of asymmetric adiabatic radiofrequency (RF) pulses, Hybrid Adiabatic Pulse with asYmmetry (HAPY), is designed to be used as the labeling pulse for Pulsed Arterial Spin labeling (PASL) at 7T to reduce overall specific absorption rate (SAR) while maintaining high labeling efficiency with and inhomogeneities.MethodsRealistic and distributions were extracted from multiple in vivo scans. The proposed class of asymmetric pulses was parameterized and optimized considering these conditions. Simulation and phantoms experiments were performed to compare the optimized pulses with HS‐3, GOIA, and trFOCI pulses. In vivo experiments were conducted to demonstrate the application of HAPY in PICORE PASL at 7T, compared with the GOIA and trFOCI pulses.ResultsHAPYs with different amounts of pulse energy reduction are obtained by the proposed optimization framework. Both simulation and phantom experiments demonstrate that HAPY achieves high labeling efficiency and high selectivity along the critical side despite off‐resonance and low amplitude. In vivo experiments reveal that HAPY is able to generate robust perfusion signal with less overall SAR or shorter pulse repetition time, compared to the GOIA and trFOCI pulses.ConclusionThe HAPY class of pulses, obtained via systematic optimization tailored to the application of PASL at 7T, reduces power deposition without affecting labeling efficiency, which provides a prospect of further exploiting the benefits of ultra‐high field in ASL.
Assessment of motor unit firing by high‐density surface electromyography detects motor neuronal hyperexcitable state in amyotrophic lateral sclerosis
Authors: Noto Yu‐ichi , Kitaoji Takamasa , Watanabe Kohei , Mizuno Toshiki 
Published: March 2023

AbstractIntroduction/AimsIn amyotrophic lateral sclerosis (ALS), the impact of motor neuron dysfunction on the motor unit (MU) firing pattern remains to be elucidated. The aim of this study was to clarify the characteristics of the MU firing rate and its association with clinical factors in ALS patients using high‐density surface electromyography (HDSEMG) and MU decomposition analysis.MethodsNineteen ALS patients and 20 controls prospectively underwent HDSEMG recording of the vastus lateralis muscle during ramp‐up (30% of maximum voluntary contraction) and sustained (10% of maximal voluntary contraction for 60 seconds) contractions on performing isometric knee extension. After decomposition analysis, instantaneous firing rates (IFRs) of individually identified MUs were calculated. Comparison of IFRs and clinical variables between ALS patients and controls and analysis of the correlation between individual mean IFR and clinical variables in ALS patients were performed.ResultsThe number of identified MUs was lower in ALS patients than in controls (P = .017). Mean IFRs of MUs (i.e., mean MU firing rates) were higher in ALS patients than in controls at some force levels on ramp‐up contraction (P < .05) and at 50 to 60 seconds during sustained contraction (9.1 [ALS] vs 8.3 [controls] pulses per second; P = .036). There was no correlation between the clinical parameters and mean IFR of each patient.DiscussionALS patients had a higher MU firing rate during muscle contraction at a low force level. Noninvasive assessment of the MU firing rate by HDSEMG can detect a motor neuronal hyperexcitable state in ALS patients.
Nurses' knowledge, attitude and behaviour on medical adhesive related skin injury in neonatal department: A survey
Authors: Wu Longyan , Deng Shanshan , Yu Lulu , Rong Hui 
Published: March 2023

AbstractAimTo evaluate the status quo of knowledge, attitude and behaviour of neonatal nurses on medical adhesive related skin injury (MARSI).DesignA survey.MethodsWe conducted a survey on the knowledge, attitude and behaviour of neonatal nurses from September 1–30, 2022. The characteristics, knowledge, attitude and behaviour of neonatal nurses were evaluated and analysed.ResultsA total of 116 neonatal nurses were included. Multivariate regression analysis indicated that had accepted MARSI training, education level, year of work experience are the influencing factors of nurses' MARSI knowledge score (all p < 0.05). Had accepted MARSI training, year of work experience are the influencing factors of nurses' MARSI attitude score (all p < 0.05). Had accepted MARSI training, year of work experience are the influencing factors of nurses' MARSI behaviour score (p = 0.015).Patient contributionNeonatal nurses should strengthen their learning and training of MARSI related knowledge, and standardize their protective behaviours to reduce MARSI.
Standardized and validated training to support the charge nurse: Research protocol
Authors: Jubinville Maripier , Longpré Caroline , Tchouaket Nguemeleu Éric 
Published: March 2023

AbstractAimTo develop a standardized training for charge nurses.DesignA developmental research design divided into three parts will be undertaken.Methods(1) A scoping review will be used to develop standardized training focusing on charge nurse skills and sub‐skills; (2) a Delphi review with nurses, managers and researchers will validate the content of the training; content validity will be assessed over sufficient rounds of review to obtain a content validity index of over 0.7 and (3) a cross‐sectional study will pilot test the training with 30 charge nurses.ResultsThis study will describe the development of updated and empirically validated training to be systematically implemented in healthcare institutions and offered to charge nurses when they begin.
Local Refinement in Isogeometric Analysis of Detailed Tire Models
Authors: Israfilova Alina , Garcia Mario A. , Kaliske Michael 
Published: March 2023

AbstractIsogeometric Analysis (IGA) and its unconventional basis functions bring undeniable benefits to the numerical analysis of solid bodies with a complex geometrical shape such as pneumatic tires. This approach erases barriers between the stage of design and the computational environment. Preservation of the exact geometrical description of the real body and the nature of functions at hand allow for higher precision of simulations for different physical phenomena.This contribution is aimed to show further developments in the framework for rolling simulation of tires using IGA. The large support of Non‐Uniform Rational B‐Splines (NURBS) provides continuous variable fields along the contact patch. Truncated hierarchical B‐splines (THB‐splines), implemented into an in‐house Finite Element Analysis (FEA) code, improve the modeling of tires by locally refining the contact zone. Global extraction operators bring the hierarchical concept as close as possible to a standard FEA code structure, flattening the set of nested layers of mesh into a sequence of single‐level elements. Furthermore, an algorithm for the computation of the accelerations at material points based on the relative velocities is adapted. The outlook of this development is the intention to use this algorithm in possible combination with analytical models for the in‐situ estimation of forces and to capture certain mechanical behavior which often are not tracked in experiments or hard and too costly to reproduce.The sampling procedure within the hierarchically nested basis is elaborated with attention to required adjustments for the nested parent‐child layered analytical meshes created via the introduction of the selective global multilevel extraction operators. Numerical simulations of rolling tires at steady‐state using IGA are presented. The evaluation and comparison of the developed framework are done using uniformly refined and locally refined models in IGA as well as classical FEA models.
Deformation analysis of friction welded hybrid structures
Authors: Heppner Eric , Glüge Rainer , Weber Martin , Woschke Elmar 
Published: March 2023

AbstractThe purpose of this paper is to present a framework for modelling the deformation behaviour of friction welded hybrid structures. The constitutive model is developed for large deformations and nonlinear material behaviour. Moreover, to demonstrate the model's applicabilities, it was implemented into a finite element system (ABAQUS). Subsequently, the simulation results were critically evaluated using experimental data.
A parametric study of high velocity impact prediction using the Mie‐Grüneisen equation
Authors: Kalapis Stephan , Kärtner Moritz , Schröder Kai-Uwe 
Published: March 2023

AbstractSpace debris is a serious threat to space travel. Even small fragments are enough to damage or destroy satellites. To protect against space debris, satellites have protective shields, which come in various forms. These shields must be optimized not only for impact protection but also for secondary factors such as weight and size. New shield systems can be tested experimentally with high‐speed guns. This requires a lot of time, energy, and cost. Here, numerical solvers can be used to evaluate these new shield systems. For example, the smoothed‐particle‐hydrodynamics (SPH) method is commonly used to simulate the large deformations resulting from an impact. Special equations of state are used to capture the effects that occur. One such model is the Mie‐Grüneisen equation of state. It is widely used for this application but does not account for the physical effects that can occur at very high speeds. Other, more complex equations of state can cover these physical effects, but they are often not implemented in commercial numerical solvers such as ABAQUS. Here we show that the Mie‐Grüneisen equation of state can lead to quantitatively reasonable results compared to experimental tests of hypervelocity impacts in ranges up to 10 km/s, even though the physical effects are not covered. A parametric study shows that the Mie‐Grüneisen equation of state can be used to predict plate collapse as a function of impactor diameter and velocity for various target thicknesses. Initial designs of new isotropic protective shields for space debris can thus be numerically tested with low effort and cost.
A magneto‐mechanically coupled material model for magnetic sensor investigation
Authors: Dorn Christian , Wulfinghoff Stephan 
Published: March 2023

AbstractWe consider coupled micro‐magneto‐mechanics with the aim to understand the processes which underpin magnetic noise in composite magnetoelectric sensors. We formulate a material model within the generalized standard material framework. This approach ensures thermodynamic consistency. Using our material model, we study the interaction of domain walls with two types of defects: geometrical defects and eigenstrains. We discuss the interaction and underlying effects in detail.
Towards shape optimization of flow channels in profile extrusion dies using reinforcement learning
Authors: Wolff Daniel , Fricke Clemens , Kemmerling Marco , Elgeti Stefanie 
Published: March 2023

AbstractProfile extrusion is a continuous production process for manufacturing plastic profiles from molten polymer. Especially interesting is the design of the die, through which the melt is pressed to impart the desired shape. However, due to an inhomogeneous velocity distribution at the die exit or residual stresses inside the extrudate, the final shape of the manufactured part often deviates from the desired one [1]. To avoid these deviations, we want to optimize the shape of the flow channel inside the die computationally. This has already been investigated in the literature using conventional optimization approaches [2,3].In this work, we investigate the feasibility of Reinforcement Learning (RL) as a learning‐based approach for shape optimization. RL is based on trial‐and‐error interactions of an agent with an environment. For each action, the agent is rewarded and informed about the subsequent state of the environment, which for this application stems from a high‐fidelity Finite Element Method (FEM) simulation.We will introduce a 2D test case as a proof‐of‐concept, in which an RL agent learns to change the geometry of a flow channel by modifying its representation as computational mesh through a spline‐based deformation method known as Free Form Deformation (FFD) [4]. We will show that an agent can be trained to optimize the geometry for different values of the quantity of interest and that the learning behavior is reproducible, which renders the RL‐based approach promising for further research.
Efficient micromagnetic finite element simulations using a perturbed Lagrange multiplier method
Authors: Reichel Maximilian , Schröder Jörg , Xu Bai-Xiang 
Published: March 2023

AbstractHigh performance magnets play an important role in critical issues of modern life such as renewable energy supply, independence of fossile resource and electro mobility. The performance optimization of the established magnetic material system relies mostly on the microstructure control and modification. Here, finite element based in‐silico characterizations, as micromagnetic simulations can be used to predict the magnetization distribution on fine scales. The evolution of the magnetization vectors is described within the framework of the micromagnetic theory by the Landau‐Lifshitz‐Gilbert equation, which requires the numerically challenging preservation of the Euclidean norm of the magnetization vectors. Finite elements have proven to be particularly suitable for an accurate discretization of complex microstructures. However, when introducing the magnetization vectors in terms of a cartesian coordinate system, finite elements do not preserve their unit length a priori. Hence, additional numerical methods have to be considered to fulfill this requirement. This work introduces a perturbed Lagrangian multiplier to penalize all deviations of the magnetization vectors from the Euclidean norm in a suited manner. To reduce the resulting system of equations, an element level based condensation of the Lagrangian multiplier is presented.
On the characterisation of cohesive interfaces by the mode I strain energy release ratio
Authors: Linke Max , Lammering Rolf 
Published: March 2023

AbstractFor the evaluation of the double cantilever beam (DCB) test several approaches are applicable that can provide different results. This ambiguity can significantly affect numerical models which refer to experimentally obtained material parameters. In this work, different approaches for the test evaluation are presented. It is shown that equations derived from the beam theory give reasonable results and good agreement between experiments, numerical and analytical solutions. In this context, DCB tests of glass fibre reinforced polymer substrates with carbon nanotube enriched composites are conducted. A slight negative effect of the latter on the experimental results is found.
An Investigation on Limiting Potentials for Damage Prediction of Viscoelastic Adhesives
Authors: Schumacher Aaron , Matzenmiller Anton 
Published: March 2023

AbstractIn his recent work VOLOKH introduced the energy limiting method as an alternative to continuum damage mechanics developed and envolved by KACHANOV, RABOTNOV, LEMAITRE and many more. In contrast to continuum damage mechanics, the energy limiting method is physically grounded by the process of atomistic debonding and, therefore, motivated on an energy basis. In order to use the energy limiting method within the framework of continuum mechanics, a limiting potential needs to be defined, which can be seen as a macroscopic manifestation of the LENNARD‐JONES bonding potential. The first limiting potential was proposed by VOLOKH and applies an exponential function with one parameter describing the maximum energy that can be absorbed by a material. Consequently, this potential can only capture the onset of damage of different materials, but not the evolution of damage. To overcome this restriction, VOLOKH proposed a generalization applying a Gamma function with two parameters describing the maximum energy and the shape of the damage evolution. Besides this improvement, this generalization has the disadvantages of violating physical plausibility conditions, needing an integration for the evaluation and having coupled parameters, which affect each other. The aim of this contribution is to propose and investigate a collection of analytical limiting potentials satisfying all physical plausibility conditions while having decoupled parameters. Finally, these potentials are used for the damage prediction of thick, viscoelastic adhesives.
Polymorphic Uncertain Structural Analysis: Challenges in Data‐Driven Inelasticity
Authors: Zschocke Selina , Graf Wolfgang , Kaliske Michael 
Published: March 2023

AbstractThis contribution addresses polymorphic uncertainty quantification within structural analysis of reinforced concrete structures composed of heterogeneous concrete and reinforcement (e.g. steel bars or carbon fibres). The macroscopic material behaviour of concrete is strongly dependent on the mesoscopic heterogeneities, which are considered by multiscale modelling. The heterogeneous mesoscopic material behaviour is characterized by representative volume elements (RVE) and the transition of scales is carried out by utilizing numerical homogenization methods.The concept of data‐driven computational mechanics enables material model free finite element analyses directly based on material data sets, overcoming the necessity of assumptions in material modelling. This approach mainly consists in assigning a stress‐strain state, which leads to a minimum of an objective function and fulfils equilibrium as well as compatibility constraints of every integration point. Inelastic material behaviour is taken into account through the definition of local data sets containing only data set states which are consistent with respect to the past local history . The realistic modelling of structures requires the consideration of data uncertainty. Generalized polymorphic uncertainty models are utilized in order to take variability, imprecision, inaccuracy and incompleteness of material data into account by combining aleatoric and epistemic uncertainty models.In this contribution, a computationally efficient approach for the consideration of data sets containing uncertain stress‐strain states within data‐driven analysis based on information reduction measurements is presented. Due to generalization, the approach is applicable to various aleatoric, epistemic and polymorphic uncertainty models. The identification of admissible local data sets for taking inelastic material behaviour into account within data‐driven analysis is realized by an energy based history parametrization which is extended to uncertain data. An approach for the efficient selection of these local data sets is presented and challenges in data‐driven inelasticity, particularly in the use case of polymorphic uncertain analyses of concrete structures, are pointed out.
Reliability‐Based Design Optimization of Laser‐Hardened Traces in a Car Front Bumper Under the Influence of Polymorphic Uncertainties
Authors: Miska Niklas , Balzani Daniel 
Published: March 2023

AbstractIn this contribution, the extended Optimal Uncertainty Quantification framework is integrated within the context of reliability‐based design optimizations (RBDO). By that, all advantages the extended Optimal Uncertainty Quantification framework offers for the polymorphic uncertainty quantification, such as the ability to incorporate exact or bounded moment information on epistemic uncertainties without the requirement of the specification of an underlying probability distribution function, can be utilized in order to identify the mathematically sharpest bounds on probabilities as required in an RBDO‐context. The combined framework is tested by means of a numerical example, in which the production and a simple crash scenario of a car front bumper are investigated. Therein, the optimization objective is the maximization of the dissipated energy during the crash, whilst a predefined failure probability is not exceeded.
Simulation Strategy for Fluid‐Structure Interaction of a Pre‐tensioned Dynamic Seal
Authors: Lankenau Tobias , Graf Matthias , Ottink Kathrin , Ebel Thomas 
Published: March 2023

AbstractAfter their assembly, dynamic seals operate in a highly deformed and, therefore, pre‐tensioned configuration. The geometrically enforced elastic pre‐stress is essential for the sealing effect, which minimises the fluid passing through the seal gap. When moving, a thin film of the fluid is transported through the seal gap to the opposite side of the seal. The mechanics of this fluid film can be described, for instance, using the Reynolds equation for thin‐film flow. However, the Reynolds equation is limited to the thin gap and can hardly be applied outside; the “thin gap assumption” is avoided here. Additionally, the geometry penetration of the undeformed seal leads to a system that cannot be meshed at the start of a coupled fluid‐structure simulation. We provide a method for solving this type of system using COMSOL Multiphysics. In the first step, solid body contact builds up the elastic pretension. In the following step, the solid body contact is incrementally replaced by fluid pressure induced by an increasing rod movement. The developed model is capable of describing the full loss of solid body contact. It can be applied to simulate local fluid backflow in the vicinity of the seal gap.
New data perspective for selective laser melting simulations
Authors: Luberto Luca , de Payrebrune Kristin M. 
Published: March 2023

AbstractIn selective laser melting (SLM), a powdered material is locally melted by a laser and, after cooling, forms a coherent solid structure that enables the production of complex geometries with various materials. The process involves extreme heating and cooling rates and, thus, large temperature gradients, which lead to anisotropic material properties on the macroscopic scale and, in the worst case, reduced mechanical properties. In order to reliably predict the final mechanical component properties, simulations can be performed at different time and length scales. Enormous computational resources are often required to perform such simulations. In order to transform these simulations into suitable surrogate models, the generated data must be compressed and evaluated in a suitable way. This paper shows first preliminary work and a possible new data description of such simulations.
Stabilization of a Multi‐Dimensional System of Hyperbolic Balance Laws – A Case Study
Authors: Thein Ferdinand 
Published: March 2023

AbstractIn a recent work we studied a stabilization problem for a multi‐dimensional system of n hyperbolic partial differential equations. Using a novel Lyapunov function taking into account the multi‐dimensional geometry we show stabilization in L2 for the arising system using a suitable feedback control. The aim of the present work is to show how this approach can be applied to a particular system. Moreover we present numerical results supporting the theoretical results.
Higher Order Asymptotic Expansion Effects in Laser Cutting Modelling
Authors: Vossen Georg , Itner Dominik 
Published: March 2023

AbstractA new model for laser cutting is derived by asymptotic expansion techniques. The model describes the movements of the free boundaries of the melt flow and involves higher order expansion terms arising from impulse and energy balance as well as surface tension phenomena. Its stationary solution is derived and analyzed for stability. The stability is correlated to published numerical and experimental results for the cutting quality.