Continuous Mode Conversion Research Articles

Controlling the reaction network of Ni/silica derived conversion of bio-oil surrogate guaiacol

Replacing fossil carbon sources with green bio-oils is a promising route to switch to a sustainable chemical industry, although their high oxygen contents are challenging. Catalytic hydrodeoxygenation is a favored route to upgrade bio-oils to renewable fuels and basic chemicals. In this work, we investigated Ni/SiO2 catalysts with differing metal dispersity in continuous mode conversion of guaiacol with a statistical experimental design for 250 °C to 400 °C, 2 h up to 5 h time on stream (ToS) and subsequently different residence time besides other parameters. While low temperature (250 °C) promotes cyclohexanol formation from guaiacol, high temperature (400 °C) inhibits hydrogenation, leading to phenol and methane. For medium temperature (340 °C), the selectivity for cyclohexanone increases. Cyclohexanol and cyclohexanone (KA-oil) are the industrial basis for polyamide 6. Furthermore, we clarified the role of 2-methoxycyclohexanol (2MC) in the reaction network towards KA-oil for continuous-mode operation. Statistical analysis was used to predict and optimize product selectivity and yield, leading to the best yield of cyclohexanone/-ol at 327.5 °C, low ToS, medium residence time, high particle dispersity, and medium hydrogen pressure (15 bar(g)).

On the influence of the probabilistic microstructural characteristics of glass fiber‐reinforced composites on the wave propagation in GLARE

AbstractIn an attempt to reduce the crack propagation speed in structures made of fiber‐reinforced composites metal layers are added to the laminate forming a new group of materials, so‐called fiber metal laminates. GLARE, a combination of glass fiber‐reinforced polymer and aluminum, is well‐known and frequently used in the aeronautical industry. One major drawback of such materials is their susceptibility to impact damage, which is not detectable by visual inspections. Hence, an adequate structural health monitoring technique to detect interlaminar damage like delaminations is essential for components made from fiber metal laminates. One approach here is the use of guided ultrasonic waves because they travel long distances without substantial damping and cover the whole thickness of thin‐walled structures. However, the probabilistic microstructure causes a continuous mode conversion in wave guides made from fiber‐reinforced composites. This significantly influences the signal processing and as a consequence, the interpretation of captured time signals. This phenomenon is induced by the random spatial distribution of the fibers in the matrix material, leading to an ongoing excitation of new wave modes within the propagating S0 wave mode. In this research, the effect is studied for the wave propagation in GLARE 3/2‐0.4. Therefore, the spatial distribution of the transverse YOUNG's modulus for the glass fiber‐reinforced layers is represented by homogeneous second‐order GAUSSian random fields. Afterwards, the propagation of the guided ultrasonic wave is simulated numerically. The results reveal that the continuous mode conversion is not only observable within the glass fiber‐reinforced polymer layers but also at the top and bottom surface and hence, within the isotropic layers. This holds for the wave propagation both in and perpendicular to the fiber orientation of the glass fiber‐reinforced polymer layers.

Structured machine learning tools for modelling characteristics of guided waves

The use of ultrasonic guided waves to probe the materials/structures for damage continues to increase in popularity for non-destructive evaluation (NDE) and structural health monitoring (SHM). The use of high-frequency waves such as these offers an advantage over low-frequency methods from their ability to detect damage on a smaller scale. However, in order to assess damage in a structure, and implement any NDE or SHM tool, knowledge of the behaviour of a guided wave throughout the material/structure is important (especially when designing sensor placement for SHM systems). Determining this behaviour is extremely difficult in complex materials, such as fibre–matrix composites, where unique phenomena such as continuous mode conversion takes place. This paper introduces a novel method for modelling the feature-space of guided waves in a composite material. This technique is based on a data-driven model, where prior physical knowledge can be used to create structured machine learning tools; where constraints are applied to provide said structure. The method shown makes use of Gaussian processes, a full Bayesian analysis tool, and in this paper it is shown how physical knowledge of the guided waves can be utilised in modelling using an ML tool. This paper shows that through careful consideration when applying machine learning techniques, more robust models can be generated which offer advantages such as extrapolation ability and physical interpretation.

Influence of the correlation lengths on the continuous mode conversion

AbstractTo detect damages using guided waves, the local mode conversion of a symmetric S0 mode into an antisymmetric A0 mode can be utilized. In simulations which use a homogeneous material model, the conversion will take place only at structural irregularities, e.g. damages. In contrast, the wave propagation in carbon reinforced plastics (CFRP) is more complex. Due to the irregular arrangement of the fibres, regions with varying fibre volume fraction are present. This spatial fluctuation causes an inhomogeneous material behaviour, which significantly influences the wave propagation. In addition to the primary induced symmetric S0 waves, secondary A0‐waves arise which are caused by the material itself and extends over the entire structure, they are continuous. These are also present if the structure is intact and consequently makes it more difficult to detect damage. In order to include the spatial variation of the material properties in the numerical model, second order random fields, which are fully represented by their mean and covariance, can be used. The random distribution of the material properties over a region can be achieved by Karhunen‐Loève decomposition. The spatial structure of the decomposition and therefore the random field depend on the chosen covariance function.

A stochastic material model to describe continuous mode conversion

AbstractDeterministic material models are not able to comprehensively describe phenomena observed in experiments. The continuous mode conversion (CMC) of propagating waves in carbon fiber reinforced plastic (CFRP) plates is an example of this. The mechanism is similar to the conversion in the presence of defects. If a symmetrical mode while propagating through a plate‐like structure encounters a damage, which is non‐symmetric with respect to the waveguide thickness, the symmetrical mode converts into an asymmetric mode at the obstacle. The conversion is usually bounded to the location of the obstacle. In contrast, the CMC occurs even in damage free CFRP structures and manifests itself in conversion taking place permanently or continuously. The reason for this phenomenon is the irregular distribution of fiber and matrix material. With the extension to the stochastic context, it is possible to work out an enhanced material model which is able to reproduce the observed wave behaviour.

Analysis of the continuous mode conversion of Lamb waves in fiber composites by a stochastic material model and laser vibrometer experiments

The complex internal structure of modern laminate composite materials, for example, carbon fiber reinforced plastics (CFRP), has a pronounced influence on the propagation of elastic guided waves (GWs). Along with the well‐known anisotropy‐conditioned amplitude and dispersion directivity of source‐induced wavefields and their remarkable attenuation due to the polymer matrix viscosity, continuous mode conversion (CMC) of GWs in multilayered composites fabricated from unidirectional prepregs has been recently observed experimentally. The latter means that the symmetric fundamental mode continuously converts into the antisymmetric one without passing a damage, that is, even in an intact structure. Being strongly related to the inhomogeneous CFRP microstructure and possessing remarkable intensity for specific propagation directions, this phenomenon should be accounted for in ultrasonic nondestructive testing and structural health monitoring systems. In this work, we investigate the CMC phenomenon in an important class of laminates, namely cross‐ply ones, experimentally as well as numerically. In the computational model it is addressed through the concept of spatially varying material properties, and the finite element method (FEM) is employed for the GW propagation simulation. Experimental measurements are performed for piezoelectrically excited GWs with scanning laser Doppler vibrometry technique, allowing clear visualization of the CMC phenomenon and confirming theoretically predicted dependence of its intensity from propagation direction.

The Phenomenon of Continuous Mode Conversion of Lamb Waves in CFRP Plates

The effect of mode conversion of Lamb waves is a well known phenomenon. Lamb waves occur in multiple modes, which can transform into each other under special conditions. Typically mode conversion takes place at discrete positions inside a structure, e.g. damages and edges. However, we observed a continuous mode conversion in a multi-layer composite plate. The symmetric S0-mode converts continuously into the A0-mode without passing a macroscopic discontinuity. In the paper this phenomenon of continuous mode conversion is investigated experimentally as well as numerically.

Continuous mode conversion of Lamb waves in CFRP plates

Online damage detection in thin walled light weight structures with Lamb waves is one common way to develop structural health monitoring (SHM) systems. Lamb waves occur in multiple modes, which can convert into each other under special conditions. The effect of mode conversion of Lamb waves is a well known phenomenon. Typically mode conversion takes place at structural changes regarding the geometry and material, e.g. damage, cracks, delaminations, etc and can be used as a criterion to get information about the health of the structure. However, experimentally we observed an unexpected continuous mode conversion (CMC) of Lamb waves in a multi-layer composite plate partially made of fabric material, which means, e.g., that the symmetric S0-mode continuously converts into the A0-mode without passing a discontinuity. This effect causes a considerably more complex wavefield and makes the detection and localization of failures more complicated. In this work, the new phenomenon of CMC is described and investigated experimentally as well as numerically.

Latitudinally dependent Trimpi effects: Modeling and observations

Modeling studies show that the exclusion of the propagating VLF wave from the ionospheric region results in the decline of Trimpi magnitude with patch altitude. In large models such as Long Wave Propagation Capability (LWPC) this exclusion does not occur inherently in the code, and high‐altitude precipitation modeling can produce results that are not consistent with observations from ground‐based experiments. The introduction to LWPC of realistic wave attenuation of the height gain functions in the ionosphere solves these computational problems. This work presents the first modeling of (Born) Trimpi scattering at long ranges, taking into account global inhomogeneities and continuous mode conversion along all paths, by employing the full conductivity perturbation matrix. The application of the more realistic height gain functions allows the prediction of decreasing Trimpi activity with increasing latitude, primarily through the mechanism of excluding the VLF wave from regions of high conductivity and scattering efficiency. Ground‐based observations from Faraday and Rothera, Antarctica, in September and October 1995 of Trimpi occurring on the NPM (Hawaii) path provide data that are consistent with these predictions. Latitudinal variations in Trimpi occurrence near L = 2.5, with a significant decrease of about 70% occurrence between L = 2.4 and L = 2.8, have been observed at higher L shell resolution than in previous studies (i.e., 2 < L < 3).