Analysis Of Propagation Research Articles

Characteristics analysis of flame propagation and its coupling effect with other parameters in LPG pipeline

AbstractTo study the flame propagating characteristic and its coupling effect with other parameters in the LPG pipeline, a typical pipeline model with two equal‐length branches perpendicular to each other is designed for experiment and simulation. Then, gas explosion scenarios are experimentally tested and numerically simulated, which is followed by the analysis of flame shape changing with time and peak temperature changing with space. Results show that when passing through the bifurcation, flame propagates to vertical branch B in a sharp knife shape affected by the strong vortex, reflected airflow, and compressed pressure wave in the pipeline with a diameter of 0.125 m. At the monitoring point that is 0.4 m away from the bifurcation point, the peak temperature of the vertical branch B is 57.87% bigger than that of the horizontal branch C, and its arrival time is 80% longer than that of the horizontal branch C, due to the existence of flame in vertical branch B. What's more, in both branches, the coupling results between peak temperature and peak velocity agree very well with the growth function, while the coupling results between peak temperature and peak pressure agree well with the decay function, providing aids to the optimal layout design of industrial pipeline branches as well as to the explosion suppression measures.

A 1 × 8 Optical Splitter Based on Polycarbonate Multicore Polymer Optical Fibers.

Visible light communication (VLC) is becoming more relevant due to the accelerated advancement of optical fibers. Polymer optical fiber (POF) technology appears to be a solution to the growing demand for improved transmission efficiency and high-speed data rates in the visible light range. However, the VLC system requires efficient splitters with low power losses to expand the optical energy capability and boost system performance. To solve this issue, we propose an effective 1 × 8 optical splitter based on multicore polycarbonate (PC) POF technology suitable for functioning in the green-light spectrum at a 530 nm wavelength. The new design is based on replacing 23 air-hole layers with PC layers over the fiber length, while each PC layer length is suitable for the light coupling of the operating wavelength, which allows us to set the right size of each PC layer between the closer PC cores. To achieve the best result, the key geometrical parameters were optimized through RSoft Photonics CAD suite software that utilized the beam propagation method (BPM) and analysis using MATLAB script codes for finding the tolerance ranges that can support device fabrication. The results show that after a light propagation of 2 mm, an equally green light at a 530 nm wavelength is divided into eight channels with very low power losses of 0.18 dB. Additionally, the splitter demonstrates a large bandwidth of 25 nm and stability with a tolerance range of ±8 nm around the operated wavelength, ensuring robust performance even under laser drift conditions. Furthermore, the splitter can function with 80% and above of the input signal power around the operated wavelength, indicating high efficiency. Therefore, the proposed device has a great potential to boost sensing detection applications, such as Raman spectroscopic and bioengineering applications, using the green light.

Thermal propagation analysis of 2G HTS stacked wires based on a dimensional coupling method

Stacked structures of high-temperature superconducting (HTS) tapes are usually employed to enhance current-carrying capacity in cable or magnet applications, but their multilayer characteristics may result in local hot spots due to uneven cooling. Besides, the inconsistencies along the length of tapes introduced during manufacturing process and the significant transverse Lorentz forces experienced in magnet operations can lead to weak parts, bringing uncertainties to thermal stability. Finite-element methods are widely used to predict thermal propagations, but 3D models encounter challenges such as distorted mesh elements and convergence issues, particularly when combining electromagnetic and heat transfer modules for long-distance wires. In this work, we have developed a Dimensional Coupling Method (DCM) to assess the thermal impact of weak parts in stacked wires applying coupled 1D and 2D models. The 2D model analyzes the electromagnetic and heat characteristics of stacked surfaces, and provides an initial heat source for the 1D model, which evaluates thermal propagation longitudinally. Simulation results of the 1D module are then transferred back to update the 2D outcomes. Models of distinct dimensions are coupled sequentially in physical steps but simultaneously in the time domain. Our approach is verified by 3D model benchmarks and offers a computational cost reduction of approximately 60 % compared to the benchmarks, making it more suitable for applications with large Iop/Ic ratios. Specially, multi-layer stacked wires under low ratios cases are also been analyzed. What’s more, two influencing factors of heat propagation, the weak-part length and position, are also investigated.

Dispersion Analysis of Plane Wave Propagation in Lattice-Based Mechanical Metamaterial for Vibration Suppression

Phononic crystals based on lattice structures provide important wave dispersion characteristics as band structures, showing excellent compatibility with additive manufacturing. Although the lattice structures have shown the potential for vibration suppression, a design guideline to control the frequency range of the bandgap has not been well established. This paper studies the dispersion characteristics of plane wave propagation in lattice-based mechanical metamaterials to realize effective vibration suppression for potential aerospace applications. Triangular and hexagonal periodic lattice structures are mainly studied in this paper. The influence of different geometric parameters on the bandgap characteristics is investigated. A finite element approach with Floquet–Bloch’s principles is implemented to effectively evaluate the dispersion characteristics of waves in lattice structures, which is validated numerically and experimentally with a 3D-printed lattice plate. Based on numerical studies with the developed analysis framework, the influences of the geometric parameters of lattice plate structures on dispersion characteristics can mainly be categorized into three patterns: change in specific branches related to in-plane or out-of-plane vibrations, upward/downward shift in frequency range, and drastic change in dispersion characteristics. The results obtained from the study provide insight into the design of band structures to realize vibration suppression at specific frequencies for engineering applications.

The influence of length under blast load on the propagation mechanism of interconnected cracks

In order to study the influence of interconnected defects on the rock breaking effect under blast load, the relevant explosion experiment was carried out by prefabricating interconnected cracks on plexiglass plates (PMMA), and the propagation mechanism of interconnected cracks under blast load was studied from the length level. The dynamic caustic line system and finite element analysis software were combined to analyze the stress intensity factor, propagation velocity of the interconnected crack tip, and full-field stress of the specimen; the results show that with the radial stress wave propagation direction as the axis of symmetry, the two interconnected cracks with symmetrical angles but different lengths are under the action of blast load; there is a certain competition between the two cracks; the longer cracks are more likely to initiate and propagate, and the shorter cracks almost do not propagate. In addition, in terms of energy accumulation at the tips of the two cracks, the longer crack has a certain inhibitory effect on the shorter crack, and when the length of the longer crack remains unchanged, the inhibition effect weakens with the increase of the length of the shorter crack, and when the length of the shorter crack remains unchanged, the inhibitory effect increases with the increase of the length of the longer crack. After the crack initiation of the longer crack, the relationship curve between the stress intensity factor and the crack propagation velocity and time of the longer crack tip decreases first, and then the relationship curve rises to the peak as the energy of the tip of the shorter crack is transferred to the longer crack, and then the oscillation decreases, while the stress intensity factor and crack propagation rate of the shorter side crack tip show an overall downward trend. The numerical simulation is used to supplement the analysis of the stress propagation in the full-field of the specimen, which corroborates with the experiment results. The experimental study provides a theoretical basis for the analysis of the propagation mechanism of interpenetrating cracks under blast load in practical engineering.

Analyzing Thermal Runaway Propagation in Lithium-Ion Battery Modules with Reduced Flammability Electrolyte Cells

A thorough analysis of thermal runaway propagation was conducted, focusing on both module and cell levels, using a range of standard flammability and reduced flammability electrolytes in 18650 cells sourced from Eagle-Picher Technologies. Utilizing techniques such as accelerated rate calorimetry; cell enthalpy, maximum thermal runaway temperature, and thermal runaway onset and initiation temperatures were evaluated, consistently demonstrating their reliability. Employing the NASA X-57 module billet as a strategy for mitigating thermal runaway propagation, the absorption of cell energy during failure events was observed, effectively preventing the spread of thermal runaway between cells. Notably, the use of reduced flammability electrolyte resulted in an average reduction of 104 °C in maximum thermal runaway temperature at the module level, thereby offering decreased risk in preventing thermal runaway propagation during failures. Note the relatively modest 51 °C difference observed between reduced flammability and standard flammability cells during individual cell tests. This underscores the importance of conducting tests at both the cell and module levels in the development of systems for certification, where the cell-level data indicate a 51 °C discrepancy, while the module-level analysis shows a more substantial 104 °C differentiation.

Integrated finite element analysis and machine learning approach for propagation pressure prediction in hybrid Steel-CFRP subsea pipelines

Accurate prediction of the propagation pressure (PP) in hybrid steel-CFRP pipe systems presents a substantial challenge due to intricate interactions and complex collapse failure modes. An efficient FE-based algorithm is programmed using ANSYS to numerically estimate the PP of hybrid steel-CFRP pipe, subjected to external pressure. This study employs a machine learning (ML) framework, addressing the inherent complexity with a three-phase approach: Parameter Design, Buckle Propagation Analysis, and ML Model Development. The dataset, encompassing about two thousand observations with four key features, undergoes k-fold cross-validation and min-max normalization for robust ML performance. Five ML models—Random Forest (RF), K-Nearest Neighbors (KNN), Genetic Programming (GP), Multi-layer Perceptron (MLP), and Support Vector Machine (SVM)—are developed and evaluated. The results revealed a significant influence of Ds/ts, a three-phase relationship with ts/tc, and a substantial decrease in PPh/PPs with increasing σys/σuc, predominantly exhibiting U-shaped or dog-bone failure modes in different scenarios. Proven that GP, KNN, and RF are the superior performers, ranking ahead of SVM with Gaussian Kernel (SVM-GK), MLP, and SVM with Linear Kernel (SVM-LK). Statistical metrics, Taylor Diagram analysis, and comparisons with FE results emphasize the effectiveness of GP, KNN, and RF. Additionally, normality tests and feature importance analysis provide nuanced insights.

A variable kinematic multi-field model for lamb wave propagation analysis in smart composite panels

The study explores the propagation of symmetric and antisymmetric fundamental Lamb waves in laminated composite strips, employing multi-field piezo-elastic plate models. The findings indicate the necessity of employing higher-order kinematic models to enhance the accuracy of wave propagation assessments. To further optimize computational efficiency, node-dependent kinematic models are utilized. The research delves into the tradeoff between reducing computational costs and maintaining result accuracy demonstrating a reduction of up to 60% in computational expenses in simple models while keeping the error below 1%. Two-dimensional wave propagation in laminated composite plates was further considered, expanding the scope due to material orthotropy.

Stochastic mesoscale characterization of ablative materials for atmospheric entry

This study addresses the estimation of material properties at a mesoscopic level using the PuMA software from an uncertainty quantification perspective. Stochastic simulation with PuMA is primarily related to the random distribution of fibers, which is an intrinsic source of uncertainty. Additionally, the selection of certain physical parameters, such as the fiber's thermal conductivity, introduces further uncertainties. The first contribution of this study is to propose a low-cost surrogate-based methodology with an unequal allocation scheme, applied for the first time to the stochastic mesoscale characterization of ablative materials. The second contribution is a study on uncertainty propagation and sensitivity analysis of material properties, providing a systematic assessment of the choice of voxel resolution for both the fibers and the domain. Specifically, the convergence of quantities of interest can be monitored, thus identifying the minimal reference elementary volume.

Inter-laboratory reproduction and sensitivity study of a finite element model to quantify human femur failure load: Case of metastases

IntroductionMetastases increase the risk of fracture when affecting the femur. Consequently, clinicians need to know if the patient's femur can withstand the stress of daily activities. The current tools used in clinics are not sufficiently precise. A new method, the CT-scan-based finite element analysis, gives good predictive results. However, none of the existing models were tested for reproducibility. This is a critical issue to address in order to apply the technique on a large cohort around the world to help evaluate bone metastatic fracture risk in patients. The aim of this study is then to evaluate 1) the reproducibility 2) the transposition of the reproduced model to another dataset and 3) the global sensitivity of one of the most promising models of the literature (original model). MethodsThe model was reproduced based on the paper describing it and discussion with authors to avoid reproduction errors. The reproducibility was evaluated by comparing the results given in the original model by the original first team (Leuven, Belgium) and the reproduced model made by another team (Lyon, France) on the same dataset of CT-scans of ex vivo femurs. The transposition of the model was evaluated by comparing the results of the reproduced model on two different datasets. The global sensitivity analysis was done by using the Morris method and evaluates the influence of the density calibration coefficient, the segmentation, the orientations and the length of the femur. ResultsThe original and reproduced models are highly correlated (r2 = 0.95), even though the reproduced model gives systematically higher failure loads. When using the reproduced model on another dataset, predictions are less accurate (r2 with the experimental failure load decreases, errors increase). The global sensitivity analysis showed high influence of the density calibration coefficient (mean variation of failure load of 84 %) and non-negligible influence of the segmentation, orientation and length of the femur (mean variation of failure load between 7 and 10 %). ConclusionThis study showed that, although being validated, the reproduced model underperformed when using another dataset. The difference in performance depending on the dataset is commonly the cause of overfitting when creating the model. However, the dataset used in the original paper (Sas et al., 2020a) and the Leuven's dataset gave similar performance, which indicates a lesser probability for the overfitting cause. Also, the model is highly sensitive to density parameters and automation of measurement may minimize the uncertainty on failure load. An uncertainty propagation analysis would give the actual precision of such model and improve our understanding of its behavior and is part of future work.

Analysis of crack propagation of PLA fabricated by the additive manufacturing technique

Understanding crack propagation is crucial for evaluating the structural integrity and reliability of additive manufacturing components, as cracks can compromise mechanical properties and potentially lead to catastrophic failures. The study of crack propagation in additive manufacturing components is used to develop strategies for mitigating crack initiation and growth, improving material properties, and optimising the design and manufacturing processes. Crack propagation in additive manufacturing components can be influenced by various factors, including material properties, design considerations, manufacturing defects, and loading conditions. Due to the identified issue, the study was carried out to investigate the crack propagation of the Fused Deposition Modeling (FDM) component using compact tension fracture testing. The experimental work started with fabricating the samples using PLA material, followed by a fracture test based on the compact tension specimen test to get a response of the structure and its crack propagation under tensile. Material properties were also collected using the dog bone tensile test. The material properties of the testing were then imported to Finite Element Analysis for further investigation of fracture mechanics. It was found that the maximum force of the sample was 141.7 ± 28 N at 1.70 ± 0.26 mm displacement, and cracks initiated around the tip and propagated upward or downward based on the initial crack location. The deformation patterns of PLA material have shown it to be brittle plastic deformation and low energy absorption before fracture.

Multimodal uncertainty propagation analysis for the morphing wings of cross-domain variant aircraft

Multimodal uncertainty propagation analysis for the morphing wings of cross-domain variant aircraft

Thermal runaway front propagation characteristics, modeling and judging criteria for multi-jelly roll prismatic lithium-ion battery applications

Large-format prismatic Li-ion batteries (LIBs) are prominent energy storage devices in electric transportation applications. However, large-format LIB induces severe thermal runaway (TR) disasters. Battery failure commonly initiates from a local point of one jelly roll and then propagates to the whole cell, called thermal runaway front (TRF) propagation. This study investigates the TRF propagation mechanism of multi-jelly roll-based LIBs through experiments, modeling, and theoretical analysis for thermal runaway propagation (TRP) mitigation. Experiments prove that battery venting changes along the jelly roll-safety valve directions during the TRF boundary movement. Besides, TRF propagation speed is found to be accelerated inside each cell (from 3.6 to 10.6 mm/s) during TRP, driven by a significant temperature gradient, chemical reactions, and gas flow along the TRP direction. The in-cell TRF acceleration behavior is more noticeable for batteries with more jelly rolls. The TRF speed-jelly roll index equations are proposed to reveal the propagation acceleration principle mathematically. Furthermore, a thermal-physical model is developed to precisely simulate in-cell TRF propagation behavior, which is validated by experimental data. Moreover, the TRF boundary temperature equation and “No TRP” judging criteria are proposed through theoretical analysis. This study proposes promising strategies for potential TRP suppression, contributing to future safe battery system design.

Analysis of the ice front propagation in heart tissues: First results

Experimental tests were conducted simultaneously using an infrared (IR) camera and a standard camera in the visible range (VR) to detect the ice front propagation as a function of time and space in different sections of pig heart laid on the surface of a cold spherical aluminum source (30 mm in diameter). The goal of the experiments was to simulate the conditions during the medical practice of internal cryotherapy, which aims to eliminate the tissues responsible for atrial fibrillation in the human heart. Freezing temperatures and related times were also measured, although they were affected by several uncertainties associated with the tests, such as air trapping between the metal sphere and flesh, inhomogeneity of the flesh samples, and the low spatial resolution and accuracy of the IR camera. A comparison with the results of previously conducted numerical simulations (Potenza et al., 2023) [1] is also discussed.

Spiking neural networks in the Alexiewicz topology: A new perspective on analysis and error bounds

In order to ease the analysis of error propagation in neuromorphic computing and to get a better understanding of spiking neural networks (SNN), we address the problem of mathematical analysis of SNNs as endomorphisms that map spike trains to spike trains. A central question is the adequate structure for a space of spike trains and its implication for the design of error measurements of SNNs including time delay, threshold deviations, and the design of the reinitialization mode of the leaky-integrate-and-fire (LIF) neuron model. First, we identify the underlying topology by analyzing the closure of all sub-threshold signals of a LIF model. For zero leakage this approach yields the Alexiewicz topology, which we adopt to LIF neurons with arbitrary positive leakage. As a result, LIF can be understood as spike train quantization in the corresponding norm. This way we obtain various error bounds and inequalities such as a quasi-isometry relation between incoming and outgoing spike trains. Another result is a Lipschitz-style global upper bound for the error propagation and a related resonance-type phenomenon.

Nonlinear wave propagation in homogenized strain gradient 1D and 2D lattice materials: Applications to hexagonal and triangular networks

AbstractThis work aims to analyze the propagation of fully nonlinear waves, encompassing shear, extension, and bending deformation modes, within homogenized periodic nonlinear hexagonal and triangular networks, successively considering 1D and 2D situations. The wave analysis is conducted from the expression of the effective strain energy density of periodic hexagonal and triangular lattices in the nonlinear regime by a continualization of the discrete lattice equations, considering all forms of energy. We incorporate strain gradient effects into the continuous model to account for the wave‐dispersive nature. The resulting second‐gradient nonlinear continuum exhibits subsonic and supersonic propagation modes. We first examine in a 1D situation the dynamical response of the hexagonal and triangular lattices, considering varying levels of nonlinearity quantified by a single scalar valued parameter. We further evaluate the impact of a fully nonlinear analysis compared to an analysis solely based on the shear energy, regarding both supersonic and subsonic modes. The nonlinear wave propagation analysis is then extended to a 2D situation for the same two lattices. It is shown that the longitudinal mode exhibits a higher frequency at a low degree of nonlinearity; however, as the degree of nonlinearity increases, the shear mode surpasses the longitudinal mode in terms of frequency. As the wavenumber increases, the nonlinearity has a lesser impact on the frequency behavior, and the phase velocity is more influenced by other factors, such as the second gradient contributions of the effective constitutive law. Such a behavior indicates a transition from a highly nonlinear behavior at lower wave numbers to a more linear behavior at higher wave numbers.

Error propagation and model update analysis in three-dimensional CSEM inversion

SUMMARY This study examines error propagation from data to model space during 3-D inversion of controlled-source electromagnetic (CSEM) data using a Gauss–Newton-based algorithm. An expression for model parameter correction is obtained using higher order generalized singular value decomposition for various regularization strategies. Inverse modelling is performed for different types of noise employing distinct regularization schemes to investigate the impact of error. Data corrupted with random noise suggest that the random noise mainly propagates when regularization parameters are small, owing to the high-frequency nature of random noise. Furthermore, the random noise predominantly causes artefacts in the shallower part of the inverted model. However, it has little impact on the estimation of major anomalies because the anomaly primarily depends on the smoothly varying parts of data. These observations are valid for both isotropic and anisotropic inversions. Resistive geological anomalies, like vertical dyke or vertical fractures, may pose a significant challenge for isotropic inversion in terms of convergence and data fit, even if the subsurface is isotropic. On the other hand, anisotropic inversion performs remarkably well in such cases, showing faster convergence and better data fit than isotropic inversion. Anisotropic inversion is indispensable in the case of an anisotropic host medium, as isotropic inversion produces significant artefacts and poorer data fit. Numerical experiments suggest that, in general, anisotropic inversion produces relatively better data fit and faster convergence, even in the case of isotropic subsurface. However, due to the varying degree of sensitivity of CSEM data on thin resistive bodies, caution is required in interpreting an anisotropy obtained using anisotropic inversion. An investigation of field data also supports the observations obtained using synthetic experiments.

Dynamics of thermal plumes for large spaces: A comparative study of in-situ smoke test and a CFD model

This study focuses on natural convection heat transfer in building heating and ventilation. Amid advancements in natural ventilation and a changing energy landscape, innovative heating methods are crucial. Thermal radiators play a key role in enhancing heat convection and understanding thermal plumes to optimize heating efficiency.This study investigates the use of coloured smoke sources to visualize thermal plume flow fields in real-scale (in-situ), naturally ventilated large spaces, distinguishing itself from most studies that prioritize enhancing thermal efficiency radiator. It offers a way for both qualitative and quantitative validation of a CFD model using passive scalars and experimental images to illustrate thermal plume propagation. This novel approach provides an effective way to visualize and understand thermal plumes in spaces where other experimental techniques are challenging to implement.Experimental results showed high consistency between measured and CFD values for velocity, temperature, and heat exchange, with differences below 10 %. The study unveiled a low impact of initial smoke source velocities on plume visualization. Using coloured smoke images to validate the CFD model yielded errors from 2.3 % to 14.5 %, proving the method’s reliability for both qualitative and quantitative analysis of plume propagation, offering valuable insights into air propagation in naturally ventilated spaces.

Rest length controlled tunable band structure in periodic tensegrity metastructure – a numerical study using a novel consistent stiffness and mass formulation

Elastic wave propagation in various periodic metastructures and its application to wave filtering, vibration isolation, acoustic cloaking, etc., have gained significant attention among researchers in recent years. Despite the presence of band gaps, traditional lattice structures lack dynamic tunability. The solution lies in using tensegrity as unit cells. This article presents analysis of tunable wave propagation through a metastructure formed by tessellation of a 2D tensegrity unit cell in one dimension. Equations of motion of the unit cell are derived with consideration of flexibility and distributed mass of the bars, which is often neglected in the literature. The formulation is extended for wave dispersion analysis using the Floquet–Bloch theory. Next, the order of the formulation is reduced for decoupled analysis of symmetric and antisymmetric modes. The dispersion relations for different modes have been validated with nonlinear as well as linearized frequency response analysis under impulse load. Next, the effect of rest length of strings and alternating arrangement of bars on band gaps is studied in detail.

Three-dimensional thermomechanical wave propagation analysis of sandwich nanoplate with graphene-reinforced foam core and magneto-electro-elastic face layers using nonlocal strain gradient elasticity theory

This article investigates the propagation of bending, longitudinal, and shear waves in a smart sandwich nanoplate with a graphene platelet (GPL)-reinforced foam core and magneto-electro-elastic (MEE) surface layers using sinusoidal higher-order shear deformation theory (SHSDT). The suggested nanoplate is comprised of a Ti–6Al–4V foam core placed between MEE surface layers. The MEE surface layers are composed of a volumetric combination of cobalt-ferrite (CoFe2O4) and barium-titanate (BaTiO3). The foam core and MEE face layers’ material characteristics are temperature dependent. In this study, three different core types are considered: metallic solid core (Type-I), GPL-reinforced solid core (Type-II) and GPL-reinforced foam core (Type-III), as well as three different foam distributions: symmetrical foam I (S-Foam I), symmetrical foam II (S-Foam II) and uniform foam (U-Foam). To derive the nanoplate's equations of motion and determine the system response, Hamilton's principle and Navier's method are employed. The effects of various parameters such as the wave number, nonlocal parameter, foam void coefficient and distribution pattern, GPL volume fraction, and thermal, electric, and magnetic charges, on the phase velocity and wave frequency are investigated via analytical calculations. The findings of the research indicate that the 3-D wave propagation characteristics of the sandwich nanoplate can be considerably modified or tuned with respect to external loads and material parameters. Thus, the proposed sandwich structure is expected to provide important contributions to radar stealth applications, protection of nanoelectromechanical devices from high frequency and temperature environments, advancement of smart nanoelectromechanical sensors characterized by lightweight and temperature sensitivity and wearable health equipment applications.