A Class of Reduced-Order Regenerator Models

We present a novel class of reduced-order regenerator models that is based on Endoreversible Thermodynamics. The models rest upon the idea of an internally reversible (perfect) regenerator, even though they are not limited to the reversible description. In these models, the temperatures of the working gas that alternately streams out on the regenerator’s hot and cold sides are defined as functions of the state of the regenerator matrix. The matrix is assumed to feature a linear spatial temperature distribution. Thus, the matrix has only two degrees of freedom that can, for example, be identified with its energy and entropy content. The dynamics of the regenerator is correspondingly expressed in terms of balance equations for energy and entropy. Internal irreversibilities of the regenerator can be accounted for by introducing source terms to the entropy balance equation. Compared to continuum or nodal regenerator models, the number of degrees of freedom and numerical effort are reduced considerably. As will be shown, instead of the obvious choice of variables energy and entropy, if convenient, a different pair of variables can be used to specify the state of the regenerator matrix and formulate the regenerator’s dynamics. In total, we will discuss three variants of this endoreversible regenerator model, which we will refer to as ES, EE, and EEn-regenerator models.

A supervised learning algorithm for interacting topological insulators based on local curvature

Topological order in solid state systems is often calculated from the integration of an appropriate curvature function over the entire Brillouin zone. At topological phase transitions where the single particle spectral gap closes, the curvature function diverges and changes sign at certain high symmetry points in the Brillouin zone. These generic properties suggest the introduction of a supervised machine learning scheme that uses only the curvature function at the high symmetry points as input data. { We apply this scheme to a variety of interacting topological insulators in different dimensions and symmetry classes. We demonstrate that an artificial neural network trained with the noninteracting data can accurately predict all topological phases in the interacting cases with very little numerical effort.} Intriguingly, the method uncovers a ubiquitous interaction-induced topological quantum multicriticality in the examples studied.

Effect of Two- and Three-Dimensionally Designed Guide Vanes with Different Camber Length on Static Pressure Recovery of a Wall-Mounted Axial Fan

This study was based on a numerical effort to use the motor support (prop) as a guide vane when the motor of a wall-mounted axial fan was located at the fan outlet while maintaining the structural and spatial advantage. The design for the guide vane followed two- and three-dimensional methods. The inlet vane angle, meridional length (total), and meridional length with a vane angle of zero (0) degrees (linear) were considered as design variables. At the design and some low flow rate points, the 2D design offered the most favorable performance when the meridional length with a vane angle of zero (0) degrees (linear) was 30% based on total length, and was the worst for 70%. The 3D design method applied in this study did not outperform the 2D design. In the 2D design concept, averaging the flow angle for the entire span at the design flow rate could ensure a better pressure rise over a more comprehensive flow rate range than weighting the flow angle for a specific span. In addition, the numerical results were validated through an experimental test, with an important discussion of the swirl (dynamic pressure) component. The influence of the inlet motor and turbulence model are presented as a previous confirmation.

Modeling glacial and fluvial landform evolution at large scales using a stream-power approach

Modeling glacial landform evolution is more challenging than modeling fluvial landform evolution. While several numerical models of large-scale fluvial erosion are available, there are only a few models of glacial erosion, and their application over long time spans requires a high numerical effort. In this paper, a simple formulation of glacial erosion which is similar to the fluvial stream-power model is presented. The model reproduces the occurrence of overdeepenings, hanging valleys, and steps at confluences at least qualitatively. Beyond this, it allows for a seamless coupling to fluvial erosion and sediment transport. The recently published direct numerical scheme for fluvial erosion and sediment transport can be applied to the entire domain, where the numerical effort is only moderately higher than for a purely fluvial system. Simulations over several million years on lattices of several million nodes can be performed on standard PCs. An open-source implementation is freely available as a part of the landform evolution model OpenLEM.

CFD modeling and validation of heat transfer inside an autoclave based on a mesh independency study

Autoclave processing is the main technology used in the manufacturing of structural aerospace composite parts. To optimize the autoclave process, the thermal behavior of the part and mold can be investigated through simulations. Computational fluid dynamics (CFD) provide a significant contribution to studies on heat transfer and airflow patterns, which are key points in an optimization applied to achieve a homogeneous temperature distribution inside composite parts. The solution is produced by solving the 3 D unsteady Navier–Stokes equations. This paper describes a systematic numerical study using the CFD approach to significantly improve the modeling efficiency of the heat transfer coefficient (HTC) inside an autoclave and maintain a high level of accuracy. Considering the modeling cost, calculation time, and accuracy of the results, a reasonable hybrid mesh is used based on a mesh independency study. The level of grid independence is examined using the general Richardson extrapolation method. In addition, a more robust autoclave model is presented, which is unaffected by the inlet turbulence. Further, the inlet fluid velocity and turbulence models have been identified as sensitive influencing factors. In this study, the Spalart–Allmaras turbulence model shows the best performance compared with the standard [Formula: see text] and [Formula: see text] SST models. Finally, the results are validated with the experimental data. The mean error of the simulated temperatures in the calorimeter for the front, middle and rear positions are [Formula: see text]C, [Formula: see text]C, and [Formula: see text]C, indicating a good agreement with the experiments. This paper provides guidelines on the use of a CFD simulation to predict the heat transfer during the autoclave curing process with high accuracy and reduced numerical effort.

A stream-power law for glacial erosion and its implementation in large-scale landform-evolution models

Modeling glacial landform evolution is more challenging than modeling fluvial landform evolution. While several numerical models of large-scale fluvial erosion are available, there are only a few models of glacial erosion, and their application over long time spans requires a high numerical effort. In this paper, a simple formulation of glacial erosion which is similar to the fluvial stream-power model is presented. The model reproduces the occurrence of overdeepenings, hanging valleys, and steps at confluences at least qualitatively. Beyond this, it allows for a seamless coupling to fluvial erosion and sediment transport. The recently published direct numerical scheme for fluvial erosion and sediment transport can be applied to the entire domain, where the numerical effort is only moderately higher than for a purely fluvial system. Simulations over several million years on lattices of several million nodes can be performed on standard PCs. An open-source implementation is freely available as a part of the landform evolution model OpenLEM.

The Influence of Loading Position in A Priori High Stress Detection using Mode Superposition

For the analysis of structural components, the finite element method (FEM) has become the most widely applied tool for numerical stress- and subsequent durability analyses. In industrial application advanced FE-models result in high numbers of degrees of freedom, making dynamic analyses time-consuming and expensive. As detailed finite element models are necessary for accurate stress results, the resulting data and connected numerical effort from dynamic stress analysis can be high. For the reduction of that effort, sophisticated methods have been developed to limit numerical calculations and processing of data to only small fractions of the global model. Therefore, detailed knowledge of the position of a component’s highly stressed areas is of great advantage for any present or subsequent analysis steps. In this paper an efficient method for the a priori detection of highly stressed areas of force-excited components is presented, based on modal stress superposition. As the component’s dynamic response and corresponding stress is always a function of its excitation, special attention is paid to the influence of the loading position. Based on the frequency domain solution of the modally decoupled equations of motion, a coefficient for a priori weighted superposition of modal von Mises stress fields is developed and validated on a simply supported cantilever beam structure with variable loading positions. The proposed approach is then applied to a simplified industrial model of a twist beam rear axle.

Transport-limited fluvial erosion – simple formulation and efficient numerical treatment

Most of the recent studies modeling fluvial erosion in the context of tectonic geomorphology focus on the detachment-limited regime. One reason for this simplification is the simple relationship of the constitutive law used here – often called stream-power law – to empirical results on longitudinal river profiles. Another no less important reason lies in the numerical effort that is much higher for transport-limited models than for detachment-limited models. This study proposes a formulation of transport-limited erosion where the relationship to empirical results on river profiles is almost as simple as it is for the stream-power law. As a central point, a direct solver for the fully implicit scheme is presented. This solver requires no iteration for the linear version of the model, allows for arbitrarily large time increments, and is almost as efficient as the established implicit solver for detachment-limited erosion. The numerical scheme can also be applied to linear hybrid models that cover the range between the two end-members of detachment-limited and transport-limited erosion.

Mean Shift versus Variance Inflation Approach for Outlier Detection—A Comparative Study

Outlier detection is one of the most important tasks in the analysis of measured quantities to ensure reliable results. In recent years, a variety of multi-sensor platforms has become available, which allow autonomous and continuous acquisition of large quantities of heterogeneous observations. Because the probability that such data sets contain outliers increases with the quantity of measured values, powerful methods are required to identify contaminated observations. In geodesy, the mean shift model (MS) is one of the most commonly used approaches for outlier detection. In addition to the MS model, there is an alternative approach with the model of variance inflation (VI). In this investigation the VI approach is derived in detail, truly maximizing the likelihood functions and examined for outlier detection of one or multiple outliers. In general, the variance inflation approach is non-linear, even if the null model is linear. Thus, an analytical solution does usually not exist, except in the case of repeated measurements. The test statistic is derived from the likelihood ratio (LR) of the models. The VI approach is compared with the MS model in terms of statistical power, identifiability of actual outliers, and numerical effort. The main purpose of this paper is to examine the performance of both approaches in order to derive recommendations for the practical application of outlier detection.

Transport-limited fluvial erosion – simple formulation and efficient numerical treatment

Most of the recent studies modeling fluvial erosion in the context of tectonic geomorphology focus on the detachment-limited regime. One reason for this simplification is the direct relationship of the constitutive law used here – often called stream-power law – to empirical results on longitudinal river profiles. Another, not less important reason lies in the numerical effort that is much higher for transport-limited models than for detachment-limited models. This study proposes a simple formulation of transport-limited erosion that is as close to empirical results on river profiles as the stream-power law is. As a central point, a direct solver for the fully implicit scheme is presented. This solver requires no iteration for the linear version of the model, allows for arbitrarily large time increments, and is almost as efficient as the established implicit solver for transport-limited erosion. The numerical scheme can also be applied to linear models between the two extremes of detachment-limited and transport-limited erosion.