bluuebunny/crossref_metadata_2025 huggingface dataset:
A positive effect of egg consumption on macular pigment and healthy vision: a systematic review and meta‐analysis of clinical trials
Authors: Khalighi Sikaroudi Masoumeh , Saraf‐Bank Sahar , Clayton Zachary S , Soltani Sepideh
Published: January 2021

Increasing macular pigment optical density (MPOD) as a result of increased macular concentration of lutein and zeaxanthin may reduce the risk of age‐related macular degeneration (AMD). The aim of the present study was to determine whether the consumption of eggs, a rich source of dietary lutein and zeaxanthin, influences MPOD and serum lutein. In this systematic review and meta‐analysis we searched PubMed, Scopus, and ISI Web of Science up to July 2020, for relevant randomized clinical trials. Using a random‐effects model, pooled weighted mean differences, and standard deviations (SDs) for each outcome were obtained. The quality of the eligible studies was assessed by the Cochrane Collaboration's tool. A meta‐analysis of five trials (296 participants) revealed that egg consumption significantly increased MPOD (weighted mean differences (WMD): +0.037; 95% CI: 0.004, 0.069; P = 0.027) and serum lutein (WMD: +0.150 μmol L̂‐1; 95% CI: 0.037, 0.263; P = 0.009). Subgroup analyses showed that egg consumption: (a) had a larger effect on MPOD in studies with a parallel design; and (b) increased serum lutein to a greater extent in a healthy population. We did not detect any heterogeneity between studies. Daily egg consumption has beneficial effects on MPOD and serum lutein is inversely associated with reduced AMD progression. Further clinical trials are required to confirm the results of this study. © 2021 Society of Chemical Industry
Characterization of free, conjugated, and bound phenolics in early and late ripening kiwifruit cultivars
Authors: Gao Yuan , Ping Hua , Li Bingru , Li Yang , Zhao Fang , Ma Zhihong
Published: January 2021

BACKGROUND

Kiwifruit (Actinidia) has long been called the ‘king of fruits’ because of its unique flavor and the wide range of bioactive compounds which contains ascorbic acid, phenolics and minerals. These bioactivities are influenced by species and cultivar. However, to date few studies are concerned with the effect of ripening time on fruit quality. Here, early and late ripening kiwifruits were investigated to determine their content of ascorbic acid, organic acid, and phenolic compounds.

RESULTS

Early ripening cultivars contained higher quinic acid and malic acid, while citric acid were found in large amounts in late ripening kiwifruits. Most of the early ripening cultivars contained higher free phenolic fractions than the late ripening fruits, mainly due to the high levels of epicatechin. However, conjugated phenolics, mainly including caffeic and 2,3,4‐trihydroxybenzoic acid, achieved higher levels in the late ripening cultivars. Free phenolics were higher than conjugated phenolics in the early ripening cultivars. Principal component analysis revealed some key compounds that differentiated the kiwifruits, and all the kiwifruits were divided into two subgroups as early and late ripening cultivars.

CONCLUSION

Ripening time had a great impact on the accumulation of bioactive compounds. The early ripening cultivars, compared to the late ripening ones, were characterized by higher levels of free neochlorogenic acid and epicatechin, while the late ripening kiwifruits contained higher amounts of conjugated phenolics. Results from this study provide further insights into the health‐promoting phenolic compounds in kiwifruit, and also provide good evidence to aid consumer selection. © 2021 Society of Chemical Industry
Dispersive liquid‐liquid microextraction based on a new hydrophobic deep eutectic solvent for the determination of phenolic compounds in environmental water samples
Authors: Hu Xizhou , Zhang Luyun , Xia Hong , Peng Maoming , Zhou Youxiang , Xu Zhimin , Peng Xitian
Published: January 2021

Dispersive liquid‐liquid microextraction has garnered increasing attention in sample preparation due to its rapid and efficient extraction process. In this study, a new terpineol‐based hydrophobic deep eutectic solvent was firstly synthesized by mixing α‐terpineol with 1‐octanoic acid, and then applied to analysis of phenols from water samples by dispersive liquid‐liquid microextraction combined with high‐performance liquid chromatography and diode array detection. Infrared spectroscopy indicated that hydrogen bonding was responsible for the formation of deep eutectic solvent between α‐terpineol and 1‐octanoic acid. After optimization of several parameters, such as the type and volume of deep eutectic solvent and the disperser, pH and ionic strength of sample solution, the developed method exhibited excellent extraction performance to the phenols with the enrichment factors from 27 to 32. Good linearity was acquired ranging from 5 to 5000 μg/L, and detection of limits of the proposed method for the phenols ranged from 0.15 to 0.38 μg/L. The recoveries measured by spiked samples at three concentration levels ranged from 81.6 to 99.3%, and precision was found with intra‐ and inter‐day relative standard deviations less than 8.7 and 9.2%, respectively. Finally, the proposed method was successfully applied to the determination of the phenols in environmental water samples.
Predictive Value of Delphian Lymph Node Metastasis in the Thyroid Cancer
Authors: Kim Do Hyun , Kim Sung Won , Hwang Se Hwan
Published: January 2021

Objective/Hypothesis

To evaluate the diagnostic accuracy of Delphian lymph node (DLN) metastasis for the prediction of central lymph node (CLN) metastasis and lateral lymph node (LLN) metastasis.

Methods

Two authors independently reviewed the six databases (Cochrane database, Embase, Google Scholar, PubMed, SCOPUS, and Web of Science). Four parameters were extracted from each study: true positive, true negative, false positive, and false negative. The quality of the methodology was evaluated using the Quality Assessment of Diagnostic Accuracy Studies ver. 2 tool.

Results

The diagnostic odds ratio of DLN in CLN metastasis was 8.859 (95% confidence interval [CI], 4.419; 16.578). The area under the summary receiver operating characteristic curve was 0.748. The diagnostic odds ratio of DLN in LLN metastasis was 7.61 (95% CI, 4.48; 12.94). The area under the summary receiver operating characteristic curve was 0.837. DLN metastasis was moderately predictive of CLN metastasis (sensitivity = 32%, specificity = 95%), LLN metastasis (sensitivity = 52%, specificity = 89%), and contralateral CLN metastasis (sensitivity = 46%, specificity = 85%). DLN metastasis had statistically significant correlation with specific clinicopathological characteristics, including younger age (< 45 years old), bilaterality, capsule invasion, extrathyroidal extension, lymphovascular invasion, male sex, multifocality, and tumor size (> 1 cm).

Conclusions

The higher specificities of DLN pathology may help predict central and lateral compartment involvement in patients with thyroid cancer.

Level of Evidence

NA Laryngoscope, 131:1990–1996, 2021
Effects of conservation agriculture on physicochemical soil health in 20 maize‐based trials in different agro‐ecological regions across Mexico
Authors: Fonteyne Simon , Burgueño Juan , Albarrán Contreras Blanca Aide , Andrio Enríquez Enrique , Castillo Villaseñor Luis , Enyanche Velázquez Fabian , Escobedo Cruz Helios , Espidio Balbuena Juan , Espinosa Solorio Avelino , Garcia Meza Paul , González Galindo Fidelia , González Regalado Jessica , Govaerts Bram , López Durante Juan Diego , López Ramírez Antonio , Martínez Gamiño Miguel Angel , Martínez Hernández Fermín , Mora Gutiérrez Manuel , Nieves Navarro Arturo Ismael , Noriega González Luis Alberto , Núñez Peñaloza Omar , Osorio Alcalá Leodegario , de la Piedra Constantino Rubén , Ponce Lira Brenda , Rivas Jacobo Isac Carlos , Saldivia Tejeda Abel , Tapia Moo Carlos Augusto , Tapia Naranjo Alfredo , Uribe Guerrero Miguel Angel , Vilchis Ramos Rodolfo , Villa Alcántara Jonatán , Verhulst Nele
Published: January 2021

Maize (Zea mays L.) is Mexico's primary staple food, but the Country's degrading soils and climate variability limit its productivity. Conservation agriculture (CA), a management technique that combines minimal tillage, permanent soil cover, and crop diversification, could reduce soil degradation and help improve soil health. There is however a lack of information about the effects of CA on soil health in the diverse agroecological conditions in Mexico. This study reports results of a field trial network established to adapt CA to Mexico's diverse cropping systems and local conditions. Physicochemical soil health, also referred to as soil quality, was studied in 20 trials in agro‐ecologies ranging from handplanted traditional systems to intensive irrigated systems, initiated between 1991 and 2016. Soil in CA was compared to the local conventional practice (CP), which commonly involves tillage, residue removal, and continuous maize production. Across the sites, organic matter and nitrates were higher in the top (0–5 cm) layer of soil and soil aggregate stability was greater under CA than under CPs. For other soil health parameters, such as nutrient content, pH or penetration resistance, the effects of management varied widely across sites and soil types and most were determined more by local soil type than by management. CA increased maize yields at most sites and on average by 0.85 ± 1.80 t ha−1. Given the significant variation across agro‐ecologies, local adaptive trials are important to assess the effects of CA on soil health and fit the practice to local conditions.
A roadmap to operationalize and evaluate impact in a learning health system
Authors: Allen Claire , Coleman Katie , Mettert Kayne , Lewis Cara , Westbrook Emily , Lozano Paula
Published: January 2021

Background

Many health systems invest in initiatives to accelerate translation of knowledge into practice. However, organizations lack guidance on how to develop and operationalize such Learning Health System (LHS) programs and evaluate their impact. Kaiser Permanente Washington (KPWA) launched our LHS program in June 2017 and developed a logic model as a foundation to evaluate the program's impact.

Objective

To develop a roadmap for organizations that want to establish an LHS program, understand how LHS core components relate to one another when operationalized in practice, and evaluate and improve their progress.

Methods

We conducted a narrative review on LHS models, key model components, and measurement approaches.

Results

The KPWA LHS Logic Model provides a broad set of constructs relevant to LHS programs, depicts their relationship to LHS operations, harmonizes terms across models, and offers measurable operationalizations of each construct to guide other health systems. The model identifies essential LHS inputs, provides transparency into LHS activities, and defines key outcomes to evaluate LHS processes and impact. We provide reflections on the most helpful components of the model and identify areas that need further improvement using illustrative examples from deployment of the LHS model during the COVID‐19 pandemic.

Conclusion

The KPWA LHS Logic Model is a starting point for future LHS implementation research and a practical guide for healthcare organizations that are building, operationalizing, and evaluating LHS initiatives.
Evolutionary psychology in marketing: Deep, debated, but fancier with fieldwork
Authors: Otterbring Tobias
Published: January 2021

This guest editorial starts with an introduction of evolutionary psychology (EP) in the marketing domain and delineates some of the building blocks of EP, both generally and when applied to consumer research. While EP is a debated discipline among marketing scholars, with some praising its presence and others perceiving it as patriarchal, politically incorrect, and problematic, a central tenet of this metaframework is a focus on deep‐rooted, ultimate explanations for human behavior. Marketing scholars have traditionally focused on proximate “how” and “what” questions, which are indeed important to address. However, unlike such proximate questions, EP strives to capture the ultimate “why” reasons behind our purchases and product preferences in terms of which adaptive functions they may have in giving us an evolutionary advantage. Having highlighted and exemplified this proximate‐ultimate distinction, I then present each state‐of‐the‐art paper included in this special issue. All special issue articles use a variety of EP arguments and theories to elucidate several consumption‐relevant phenomena with implications for marketing theory and practice. In closing, I provide a set of suggestions for future EP‐based consumer research, meant to make this field flourish further.
Analysis of environmental organic matters by Ultrahigh‐Resolution mass spectrometry—A review on the development of analytical methods
Authors: Kim Sungjune , Kim Donghwi , Jung Maeng‐Joon , Kim Sunghwan
Published: January 2021

Owing to the increasing environmental and climate changes globally, there is an increasing interest in the molecular‐level understanding of environmental organic compound mixtures, that is, the pursuit of complete and detailed knowledge of the chemical compositions and related chemical reactions. Environmental organic molecule mixtures, including those in air, soil, rivers, and oceans, have extremely complex and heterogeneous chemical compositions. For their analyses, ultrahigh‐resolution and sub‐ppb level mass accuracy, achievable using Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR MS), are important. FT‐ICR MS has been successfully used to analyze complex environmental organic molecule mixtures such as natural, soil, particulate, and dissolved organic matter. Despite its success, many limitations still need to be overcome. Sample preparation, ionization, structural identification, chromatographic separation, and data interpretation are some key areas that have been the focus of numerous studies. This review describes key developments in analytical techniques in these areas to aid researchers seeking to start or continue investigations for the molecular‐level understanding of environmental organic compound mixtures.
Scattering and propagation characteristics of SH wave in reduced Cosserat isotropic layered structure at irregular boundaries
Authors: Chaki Mriganka Shekhar , Singh Abhishek Kumar
Published: January 2021

In the present paper, scattering phenomena has been studied when propagating SH wave incident on the irregular upper boundary of a linear‐reduced Cosserat isotropic layer/half‐space configuration. Algebraic expression for dispersion equation of scattering SH wave has been deduced analytically. Expressions of displacement component and microrotational components for reflected wave have been obtained for three distinct types of irregularity, i.e., rectangular, parabolic and triangular notch‐shaped irregularity. The effect of distinct irregularity parameters on displacement and microrotational fields of reflected wave has been analysed numerically and graphically. The deduced microrotational fields due to scattering and reflection phenomena in irregular layered structure with microrotations serve as highlights of the present work which may find their application in seismic prediction, acoustic engineering and civil engineering.
How does policy innovation diffuse among Chinese local governments? A qualitative comparative analysis of River Chief Innovation
Authors: Zhang Yunxiang , Wang Shichen
Published: January 2021

It is well‐documented that interlocal learning and competition could drive policy innovation diffusion. However, their interconnection in non‐western regimes as China is less explored. Utilizing the method of qualitative comparative analysis on the case of River Chief Innovation, this article intends to explore the multiple conjunctural causation of Chinese policy diffusion and the impacts of central recognition. Our findings suggest that interlocal learning and tournament could intimately stimulate Chinese policy diffusion through different combinations. Different governments would adopt innovation for various reasons in a continuum of diffusion mechanisms, involving the technical learning, the championship‐induced learning, the mandate‐induced learning, and the innovation tournament. Hence, despite the ongoing centralization under Xi, space for local spontaneous learning remains. We also find that central recognition could activate the interlocal tournament and extend the diffusion continuum to the tournament side. Therefore, it facilitates policy diffusion toward governments that lack learning motivations and promotes the local implementation of central preferences.
An energy‐momentum space‐time discretization of a constrained micropolar continuum for 3D fiber‐reinforced composites
Authors: Groß Michael , Dietzsch Julian , Röbiger Chris
Published: January 2021

In 2D fiber‐reinforced composites, single fibers with a diameter in the range of micrometers are embedded in a matrix material. 3D fiber‐reinforced composites consist of fiber bundles (rovings) with diameters of millimeters. Therefore, 3D fiber‐reinforced composites require an extended material modelling, because a fiber bundle has to be considered as a beam‐like structure with curvature‐twist (twisting and bending) stiffness. By means of an extended continuum formulation, we modell a micro inertia and a curvature‐twist stiffness. We introduce these secondary effects by means of independent drilling degrees of freedom. The resulting constrained micropolar continuum is derived by a mixed principle of virtual power. In the discrete setting, this variational principle generates a mixed B‐bar method and an energy‐momentum scheme. We show transient numerical examples, which demonstrate the effect of micro inertia as well as the twisting and bending stiffness of the fiber bundles.
Asymptotics of Rounding Algorithms for Integer Control Problems in the Presence of Convexified Pointwise Mixed Constraints
Authors: Manns Paul
Published: January 2021

The analysis of computationally cheap algorithms to approximate the infimum of optimal control problems with discrete‐valued controls has been improved in recent literature. The overall method is often referred to as combinatorial integral approximation decomposition and the algorithms are often referred to as rounding algorithms.

The studied algorithms have in common that they seek to minimize or at least bound a quantity called integrated control deviation. The algorithms operate on a grid (often called rounding grid) and the integrated control deviation vanishes when the grid constant of the grid on tends to zero. Assuming a suitable spatial coherence property of the grid refinement implies weak∗ convergence of the computed controls in L∞.

When the integer optimal control problem features additional pointwise mixed state‐control constraints, the aforementioned rounding algorithms cannot be applied directly. There exist examples for which the observed infeasibility of the constraint after applying the algorithms does not vanish in an L∞‐sense when the grid constant is driven to zero. While modifications of the algorithms exist that resolve this problem, the asymptotics of the infeasibility without those modifications have not been analyzed so far. This work closes this gap in the existing literature and we show that the infeasibility vanishes in a pointwise almost everywhere sense.
Numerical study on shape functions for optimal exploitation of the acoustic black hole effect
Authors: Rothe Sebastian , Dorn Matthias , Langer Sabine Christine
Published: January 2021

The acoustic black hole (ABH) effect offers a great possibility to damp a whole construction in a very efficient way. The main idea of this approach is to weaken thin structures locally to concentrate the structure‐borne sound energy in this area. Therefor material is removed in a certain region, which is referred to as an ABH. This measure leads to a focusing of acoustically critical bending waves. By applying a damping measure, e.g. constraint‐layer damping, within the ABH, the structure is globally damped by a local measure.

The shape function of an ABH is a major issue for optimizing the efficiency of damping. The material diminution, equivalent to the reduction of the mechanical impedance, has to be smooth in order to avoid reflection of bending waves. In literature, a power function with a higher order than two is recommended. Focusing the structure‐borne sound works better by increasing the order. The limit case is infinite order which is a sharp step transition. This is equivalent to an impedance step which is well known to lead to a high portion of reflection and therefor reducing the efficiency of the ABH area. There must be an optimum between these two limits, quadratic and infinite order, in an acoustical sense.

In this paper, numerical studies are carried out to determine the optimal order for a power function approach as shape function of an ABH. For this purpose, a beam is used as a generic structure. In addition, alternative function approaches are investigated and compared.
The integrated control deviation of mixed‐integer optimal control problems with vanishing constraints
Authors: Bestehorn Felix , Kirches Christian
Published: January 2021

Mixed‐integer optimal control problems (MIOCPs) are often solved using a decomposition approach, consisting of solving a partial outer convexified relaxed problem and using a rounding scheme to obtain a discrete‐valued control. We show that even in the presence of Vanishing Constraints (VCs) a binary control with linearly bounded integrated control deviation exists, if the grid is equidistant. We note that this control can be computed efficiently and that the bound is tight.
Reduction of the vibration amplitude with variable excitation frequency
Authors: Simader Victoria , Holl Helmut J.
Published: January 2021

In many dynamic systems large vibration amplitudes occur if the operation frequency is near the resonance frequency. Also during the resonance passage large amplitudes result. In order to reduce the amplitude of the oscillation a suitable excitation can be applied. The force driven single degree of freedom harmonic oscillator is used to analyse the reaction of the dynamic system to a variable excitation frequency. The analysis starts with a mathematical transformation of the excitation signal in order to identify the influence of the different excitation parameters. It is shown that for specific parameters the natural frequency of the system can be eliminated from the excitation signal. In both cases, the operation near the resonance frequency and the passage through resonance, suitable numerical values, correlations between the parameters and functions can be found to reduce the resulting vibration amplitude of the system.
Investigation of heterogeneous fracture aperture distributions in a hydro mechanical setting using hybrid‐dimensional interface elements
Authors: Schmidt Patrick , Steeb Holger
Published: January 2021

In the community of porous and fractured geomaterials properties regarding underground fluid storage and matter are of high interest. Investigations on fluid‐filled fractures require strong hydro mechanical coupling of fracture and porous domain to reproduce deformation triggered, non‐local phenomena such as the Noordbergum effect. Special numerical treatment is necessary to solve the tightly coupled system consisting of high aspect ratio fractures and a surrounding porous matrix, since other approaches such as Direct Numerical Simulations fail due to technical issues (number of Degrees of Freedom (DoF)). Once heterogeneous initial aperture distributions are of interest coarse grained continuum approaches (Biot's poroelasticity theory) facing technical limitations since explicit meshing of the fracture geometry is required. This work uses hybrid‐dimensional interface elements in a fully coupled implicit formulation to investigate its capacities regarding heterogeneous fracture surfaces in three dimensions.
Simultaneous determination of Bingham material parameters using a ball probe concrete rheometer
Authors: Gerland Florian , Schomberg Thomas , Wetzel Alexander , Middendorf Bernhard , Wünsch Olaf
Published: January 2021

A new evaluation method allowing direct determination of the Bingham parameters from ball probe rheometers. A non‐linear relationship between the direct measured variables and the material parameters is revealed through numerical parameter studies. The method was validated on two devices of the ball probe type with different dimensions. Comparison with other methods showed good agreement. It is pointed out how the evaluation method can be transferred to devices having other dimensions by performing a limited number of straightforward calibration experiments. This work closes the gap between established ball probe rheometer evaluations and objective material parameters. Objective material parameters can be extracted from every ball probe rheometer. Even existing data can be converted.
Nonlinear System Identification of a Furuta Pendulum Using Machine Learning Techniques
Authors: Rückwald Tobias , Drücker Svenja , Dücker Daniel-André , Seifried Robert
Published: January 2021

Usually, dynamical systems can be described by differential equations. An accurate model is essential when designing and optimizing a controller. However, not every system can be modeled easily by physical models due to highly nonlinear behavior, such as friction or backlash. Then, a data based approach, such as machine learning, might be helpful. The focus in this work is set on modeling dynamical systems using neural networks and deep learning, which are growing subjects in research and industry to identify nonlinear dynamics.
Size Effects in Computational Homogenization of Polymer Nano‐Composites
Authors: Kumar Paras , Mergheim Julia
Published: January 2021

Nano‐particles, as compared to micro‐sized inclusions, result in a much better improvement to the mechanical properties of otherwise brittle polymers. Standard first‐order computational homogenization lacks the length scale necessary to capture this size effect. In this work, a computational homogenization scheme enhanced with interface energetics is considered and its applicability to polymer nano‐composites with different types of filler particles is assessed through systematic numerical experimentation. The study reveals that the method performs quantitatively much better in the case of softer inclusions as compared to the case where the inclusions are much stiffer than the matrix material, which happens in the case of silica nano‐particles.
Automatic differentiation of strain‐energy functions in the context of user‐defined materials for the FEM
Authors: Hillgärtner Markus , Guo Theron , Itskov Mikhail
Published: January 2021

In order to implement material models as user‐defined material subroutines into implicit finite element method (FEM) codes, a stress tensor and a fourth‐order tangent tensor are required. In the context of hyperelasticity, these tensors can be obtained as the first and second derivative of the strain‐energy function. Manual formulation and implementation of these derivatives can be tedious and error‐prone.

In this contribution, we discuss automatic differentiation (AD) as an easy‐to‐use alternative to express derivatives for the FEM [1] in an efficient way and without extensive manual implementation [2]. AD is applied to automatically obtain a user‐defined material subroutine for an implicit analysis based on source code of the strain‐energy. The approach is validated by utilizing a hyperelastic anisotropic model of arterial layers [3] in ABAQUS. Additionally, a pseudo‐elastic model of the Mullins effect in filled rubber [4] is implemented to evaluate the applicability of the discussed approach for inelastic behaviors which require internal variables.
Jump conditions in phase‐field modeling of interface fracture
Authors: Hansen-Dörr Arne Claus , Brummund Jörg , Kästner Markus
Published: January 2021

In this contribution, a variational framework for diffuse modeling of cracks in heterogeneous media is analyzed. A static order parameter smoothly bridges the discontinuity at material interfaces, while an evolving phase‐field captures the regularized crack. The key novelty is the combination of a strain energy split with a partial rank‐I relaxation in the vicinity of the diffuse interface. The former is necessary to account for physically meaningful crack kinematics like crack closure, the latter ensures the mechanical jump conditions throughout the diffuse region. The model is applied to crack propagation, where a significant influence on crack branching is observed, that underlines the necessity of a reasonable homogenization scheme for the diffuse interface region.
Linear stability of the flow in a cavity driven at yaw
Authors: des Boscs Pierre-Emmanuel , Kuhlmann Hendrik C.
Published: January 2021

The linear stability boundary of the flow in a square cavity driven by a tangentially moving lid having a non‐zero spanwise velocity is investigated by means of finite elements. For intermediate yaw angles, the linear stability boundary is lower than for the classical lid‐driven cavity. Consistent with results for bounded Couette flow the basic flow in the cavity is stabilized as the lid motion turns in spanwise direction.
Efficient identification of random fields coupling Bayesian inference and PGD reduced order model for damage localization
Authors: Robens-Radermacher A. , Held F. , Coelho Lima I. , Titscher T. , Unger J. F.
Published: January 2021

One of the main challenges regarding our civil infrastructure is the efficient operation over their complete design lifetime while complying with standards and safety regulations. Thus, costs for maintenance or replacements must be optimized while still ensuring specified safety levels. This requires an accurate estimate of the current state as well as a prognosis for the remaining useful life. Currently, this is often done by regular manual or visual inspections within constant intervals. However, the critical sections are often not directly accessible or impossible to be instrumented at all. Model‐based approaches can be used where a digital twin of the structure is set up. For these approaches, a key challenge is the calibration and validation of the numerical model based on uncertain measurement data.

The aim of this contribution is to increase the efficiency of model updating by using the advantage of model reduction (Proper Generalized Decomposition, PGD) and applying the derived method for efficient model identification of a random stiffness field of a real bridge.
An efficient semi‐analytical solution of the Reynolds equation
Authors: Pfeil Simon , Gravenkamp Hauke , Duvigneau Fabian , Woschke Elmar
Published: January 2021

A numerically efficient, semi‐analytical solution of the Reynolds equation for hydrodynamic journal bearings is developed based on the Scaled Boundary Finite Element Method. The pressure field is discretized along the circumferential coordinate of the lubrication gap, while an analytical formulation is used in the axial direction. A system of inhomogeneous ordinary differential equations is obtained, which is solved under consideration of the boundary conditions. The solution is verified, and its numerical efficiency is investigated in comparison to an FEM solution.
Deep Learning for Classification of Compton Camera Data in the Reconstruction of Proton Beams in Cancer Treatment
Authors: Basalyga Jonathan N. , Barajas Carlos A. , Gobbert Matthias K. , Maggi Paul , Polf Jerimy
Published: January 2021

Real‐time imaging has potential to greatly increase the effectiveness of proton beam therapy in cancer treatment. One promising method of real‐time imaging is the use of a Compton camera to detect prompt gamma rays, which are emitted by the beam, in order to reconstruct their origin. However, because of limitations in the Compton camera's ability to detect prompt gammas, the data are often ambiguous, making reconstructions based on them unusable for practical purposes. Deep learning's ability to detect subtleties in data that traditional models do not use make it one possible candidate for the improvement of classification of Compton camera data. We show that a suitably designed neural network can reduce false detections and misorderings of interactions, thereby improving reconstruction quality.
Characterization of the objective function landscape using a modified Dijkstra algorithm
Authors: Weiser Stephan , Wulf Hans , Ihlemann Jörn
Published: January 2021

A decisive disadvantage of high dimensional optimization problems is the large number of parameters which make the identification process difficult. Many of this are reflected in the mathematical properties of the objective function used for parameter identification. Ideally, the objective function has a simple, paraboloid‐like form with a single minimum whose location corresponds to the desired parameter set. Instead, unfavorable “landscape forms” occur, for example “bumpy” areas with several local minima. In literature, the dominant methods are attempt to simplify high‐dimensional functions, or to research new, mostly stochastic optimization methods. This article examines a way to obtain information about the landscape of the objective function underlying an optimization problem. A path search algorithm based on the Dijkstra algorithm is presented. The purpose of the algorithm is to find the approximately deepest path between two local minima, which allows to obtain information about the characteristics of the objective function. It is tested on the Himmelblau and Rastrigin function and allows to examine the landscape between two local minima with respect to their topographic characteristics.
Time‐separated stochastic mechanics for simulating the visco‐elastic response of construction parts
Authors: Junker Philipp , Nagel Jan
Published: January 2021

In a series of papers, we investigated the problem of efficiently analyzing visco‐elastic materials with stochastic material properties. The related evolution equation could be solved analytically which allowed for a stochastic series expansion around the mean for the internal variable. This, in turn, gave access to analytical expressions for the stochastic stress and reaction force in a finite element setting such that expectation and variation could be expressed in terms of simple formulas. Consequently, our analysis separated the stochastic properties of the material from any boundary problem and any loads, i.e., the stochastic behavior was separated from all time‐dependent conditions such that we referred our method as time‐separated stochastic mechanics. Numerical results of our formulas were in excellent agreement to representative Monte‐Carlo (MC) simulations. This holds true for both material point computations as well as finite element simulations. Particularly for finite element simulations, the time consumption for our approach is smaller by orders of magnitude.

In this contribution, we recall the basic aspects of our works and present a brief overview. After presenting the key idea of the TSM, we recall the numerical treatment and present several examples which we compare to Monte‐Carlo results. Our results show a similar quality as the reference solution but at a computational effort that is orders of magnitude smaller.
Comparison of Model Predictive and Graph Algebraic Approaches to Distributed Formation Control
Authors: Ebel Henrik , Eberhard Peter
Published: January 2021

Motivated by the advantages that networked control may bring for the performance and flexibility of distributed robotic systems, this contribution considers two very distinct approaches to formation control. One approach, which is more prevalent in literature, is based on results from algebraic graph theory. The other approach draws from distributed model predictive control, allowing the explicit consideration of constraints and resulting in a controller that is rather simple to tune to the application's priorities by adjusting cost function weights and constraint bounds. Interesting observations from the comparison include differences in the conservativeness and performance of the control schemes with increasing numbers of cooperating robots. Experiments with custom‐built hardware robots demonstrate the practical applicability of the schemes.
Investigating different friction models for the stick‐slip effect with nodal contact
Authors: Akar Özge , Willner Kai
Published: January 2021

Friction is an indispensable phenomenon since it appears in many natural phenomena as well as in industrial applications. Especially the so‐called stick‐slip‐effect in dynamic applications can cause undesirable effects like noise and wear. Hence, it is of great importance to investigate and understand friction in detail in order to avoid those phenomena with negative consequences. The goal of this investigation is to observe a three‐dimensional wire‐like beam clamped on one side and free on the other, that is excited at one node with a constant force. Thereby friction is induced to the system and the stick‐slip‐effect occurs. The Fast Nonlinear Analysis Algorithm is used to solve the nonlinear equation computationally. First, dry friction is simulated varying the number of sliders in the Iwan model and applying different friction distribution models. Viscous and Stribeck friction are included afterwards. The obtained results are compared with respect to the simulation time.
Water management of frost‐resistant plant tissues as a consequence of extracellular ice formation
Authors: Eurich Lukas , Wagner Arndt , Ehlers Wolfgang
Published: January 2021

The formation of extracellular ice within plant tissues is regarded as one of their crucial factors to withstand subzero temperatures without any (biologically irreversible) damage. In this regard, extracellular ice implies two important consequences, which are the dehydration of the tissue cells to prevent intracellular ice formation, which would be fatal for the plant, and the attraction of water towards the freezing site. However, the pattern of ice formation may vary significantly among various types of plants. There might be rather dispersed ice formation distributed in large parts of the plant or localised ice formation at internal surfaces. Within this contribution, the latter‐mentioned case is addressed with a macroscopic modelling approach based on the Theory of Porous Media. The appearing water management is discussed at a representative numerical example.
Analysis of the fractal properties of silica aerogels using diffusion‐limited aggregation
Authors: Abdusalamov Rasul , Itskov Mikhail , Milow Barbara , Rege Ameya
Published: January 2021

Silica aerogels are highly porous solids with very low densities and thermal conductivities. Their high porosity results in a fractal morphology which has a strong influence on mechanical properties. In this work, the diffusion‐limited cluster aggregation (DLCA) method is implemented to model silica aerogel aggregates. A preliminary model based on this approach demonstrates good agreement with experimental data [1]. The influence on the fractal properties of different input parameters as for example the particle size is investigated. Moreover, the resulting geometries are compared to fractal features of silica aerogels determined by experimental data from small angle X‐ray scattering (SAXS). The mechanical response of these aggregation models is analyzed by a finite element analysis (FEA) for the generated representative volume elements (RVE). The effect of varying densities on the mechanical properties, for e.g., Young's modulus, is further elucidated.
Modeling the microstructure of biopolymer aerogels using Voronoi tessellation method
Authors: Chandrasekaran Rajesh , Hillgärtner Markus , Rege Ameya , Milow Barbara , Itskov Mikhail
Published: January 2021

The bulk properties of biopolymer aerogels depend on their microstructure, which can be tailored by different synthesis and drying methods. Biopolymer aerogels are characterized by a fibrillar morphology having a cellular‐like network. The recently proposed constitutive modeling approach by Rege et al. [1] has shown good predictive capabilities in describing the mechanical behavior of such aerogels. Although the model describes the cellular nature and adheres to the cell‐size distributions of aerogels, it is based on the assumption that the network is made up of idealized square‐shaped cells. In this contribution, the diversified cellular morphology of aerogels is described computationally using a Laguerre‐Voronoi tessellation based approach [2]. The pore‐size distribution (PSD) data obtained from experiments accounts for the random cell sizes within the network. Accordingly, Voronoi tessellations are generated to create periodic representative volume elements (RVEs) resembling the microstructural properties of the cellular network. This work is an extension of our previous Voronoi tessellation‐based 2‐d description of biopolymer aerogels [3].
Identifying equivalent transversely isotropic material parameters for full‐surface bonded sheet‐layered lamination stacks
Authors: Baloglu Maximilian Volkan , Willner Kai
Published: January 2021

The accurate prediction of the structural properties of sheet‐layered lamination stacks in rotors and stators of electric motors is a challenging task due to the special layer design. The joining technology has a major influence on the individual sheet interactions and on the macroscopic quantities. Here, full‐surface bonded lamination stacks are considered for which equivalent linear transversely isotropic material parameters are determined by modeling the bonding varnish using Zero‐Thickness interface elements. It is shown that this procedure delivers comparable results to those obtained with traditional methods, like the rule of mixture or by modeling the adhesive layer with 3D continuum elements.
Topology and material optimization of anisotropic materials including a filter to smooth fiber pathways
Authors: Jantos Dustin Roman , Hackl Klaus , Junker Philipp
Published: January 2021

A three‐dimensional topology optimization of anisotropic materials including the optimization of the local material orientation based on thermodynamic principles is presented. To this end, the topology is parameterized by a continuous density variable with penalization of intermediate densities (SIMP) [1]. The material orientation is defined by the rotation of a given anisotropic base material and the rotation is parameterized by a set of three Euler angles. A novel filtering technique is presented to provide a smoothing of the material orientation, i.e. the fiber paths. The influence of the filter parameter on the maximum allowed fiber path curvature is shown. The constraint on the maximum fiber curvature also influences the results for the optimal topology. Corresponding numerical results for the simultaneous optimization of the topology and local material optimization for the two‐dimensional and three‐dimensional case will be presented.
GPU‐accelerated simulation of a non‐local conservation law
Authors: Göttlich Simone , Müller Jann , Weissen Jennifer
Published: January 2021

The model under consideration is a non‐local conservation law in two space dimensions that might be used to model material or pedestrian flow. We accelerate the simulation of the non‐local model using parallelization of the non‐local terms in the programming language Haskell. The implementation allows for the computation of the solution to the conservation law with a finite volume method at reasonable computational cost even for large domains and fine discretizations.
Daily Precipitation Generation using a Hidden Markov Model with Correlated Emissions for the Potomac River Basin
Authors: Kroiz Gerson C. , Majumder Reetam , Gobbert Matthias K. , Neerchal Nagaraj K. , Markert Kel , Mehta Amita
Published: January 2021

A daily precipitation generator based on a hidden Markov model with Gaussian copulas (HMM‐GC) is constructed using remote sensing data from GPM‐IMERG for the Potomac river basin on the East Coast of the USA. Daily precipitation over the basin from 2001–2018 for the wet season months of July to September is modeled using a 4‐state HMM, and correlated precipitation amounts are generated from a mixture of Gamma distributions using Gaussian copulas for each state. Synthetic data from a model using a mixture of two Gamma distributions for the non‐zero precipitation is shown to replicate the historical data better than a model using a single Gamma distribution.
Plate theories: A mixed Vekua and consistent approximation approach
Authors: Meyer-Coors Michael , Kienzler Reinhold , Schneider Patrick
Published: January 2021

By the use of Taylor series expansion, we arrive from the three‐dimensional theory of linear elasticity at the exact two‐dimensional plate problem which consists of infinitely many equations and unknowns. Applying the approximation approach of Vekua or the consistent‐approximation approach to this exact problem leads to hierarchical PDE‐systems. For the latter approach a modular structure of the displacement coefficients is assumed and proved for several orders. With this modularity we show that “fully” reducible PDE‐systems, so called complete plate theories, can be obtained by using a special schema. The results of the complete plate theories coincide with the classical theories and also fulfill several local conditions. When proving the existence of “fully” reducible PDE‐systems for an Nth order complete plate theory, Hilbert‐type matrices appear. We calculate the determinant for these matrices and present a sketch of evidence.
The Invention of the Eigenstress Calculation in Plasticity
Authors: Bruhns Otto T.
Published: January 2021

Almost one hundred years ago, Heinrich Hencky, in a work published in German and probably for this reason less noticed, laid the essential foundations for today's calculation methods of elastic‐plastically deformed structures. In short remarks the importance of this work for several of today's commonly used methods is underlined.
Towards a stochastic model for electrohydrodynamic turbulence with application to electrolytes
Authors: Klein Marten , Schmidt Heiko
Published: January 2021

We investigate turbulent Couette flows of dilute, weakly‐conducting electrolytes by utilizing the stochastic one‐dimensional turbulence (ODT) model. The flow is driven by relative motion of the top and bottom wall and affected by an electric field between these walls that is prescribed by a voltage difference. The electrolytes considered have zero bulk charge and consist of two ion species with the same mobility, valence, and initial concentration. The stochastic model predicts a decrease of the mean streamwise velocity when an external voltage is applied provided that both Schmidt (Sc) and Reynolds (Re) numbers are sufficiently large, that is, Sc ≥ 30 for Re = 12000 investigated. The effect observed is relevant for flow control, but the mechanism awaits clarification. Present ODT results may help to develop this understanding or design laboratory experiments.