Implicit Inverse Force Identification Method of Acoustic Liquid-structure Interaction Finite Element Model

The two-field vibroacoustic finite-element (FE) model requires a relatively large number of degrees of freedom compared to the monophysics model, and the conventional force identification method for structural vibration can be adjusted for multiphysics problems. In this study, an effective inverse force identification method for an FE vibroacoustic interaction model of an interior fluid-structure system was proposed. The method consists of: (1) implicit inverse force identification based on the Newmark-$\beta$ time integration algorithm for stability and efficiency, (2) second-order ordinary differential formulation by avoiding the state-space form causing large degrees of freedom, (3) projection-based multiphysics reduced-order modeling for further reduction of degrees of freedom, and (4) Tikhonov regularization to alleviate the measurement noise. The proposed method can accurately identify the unmeasured applied forces on the in situ application and concurrently reconstruct the response fields. The accuracy, stability, and computational efficiency of the proposed method were evaluated using numerical models and an experimental testbed. A comparative study with the augmented Kalman filter method was performed to evaluate its relative performance.Comment: 31 Pages, 20 Figures, 5 Table

Real-time response estimation of structural vibration with inverse force identification

This study aimed to develop a virtual sensing algorithm of structural vibration for the real-time identification of unmeasured information. First, certain local point vibration responses (such as displacement and acceleration) are measured using physical sensors, and the data sets are extended using a numerical model to cover the unmeasured quantities through the entire spatial domain in the real-time computation process. A modified time integrator is then proposed to synchronize the physical sensors and the numerical model using inverse dynamics. In particular, an efficient inverse force identification method is derived using implicit time integration. The second-order ordinary differential formulation and its projection-based reduced-order modeling is used to avoid two times larger degrees of freedom within the state space form. Then, the Tikhonov regularization noise-filtering algorithm is employed instead of Kalman filtering. The performance of the proposed method is investigated on both numerical and experimental testbeds under sinusoidal and random excitation loading conditions. In the experimental test, the algorithm is implemented on a single-board computer, including inverse force identification and unmeasured response prediction. The results show that the virtual sensing algorithm can accurately identify unmeasured information, forces, and displacements throughout the vibration model in real time in a very limited computing environment.Comment: 24 Pages, 15 Figures, 10 Table

Neodymium-doped cladding pumped aluminosilicate fiber laser tunable in the 0.9 micron wavelength range

A tunable high-power cladding-pumped neodymium-doped aluminosilicate fiber laser is demonstrated. The maximum power reached was 2.4 W with a slope efficiency of 41% and a threshold pump power of 1.68 W, both with respect to launched pump power, when cladding pumped by two 808 nm diode pump sources at both fiber ends. The dependence of the tuning range on the fiber length is investigated. The tuning range changed from 922 to 942 nm for a 25 m-long fiber to 908-938 nm with a 14 m-long fiber, because of reabsorption effects. The output linewidth was 0.26 nm in a diffraction-limited beam. Operation on the challenging 0.9 µm three-level transition in neodymium-doped double-clad fiber laser was facilitated by a W-type core refractive index profile. This filtered out the unwanted and competing strong transition at 1.06 µm while guidance of 0.9 µm remained intact

Initial bead growth and distribution under low speed icing condition

One of the critical issues in recent ice prediction studies is the modeling of roughness formation based on physical phenomena. While a number of experimental studies have been conducted to investigate the fundamental physics of roughness formation, initial bead growth is rarely studied despite its significance to determine bead size and distribution. In the present study, an experiment is conducted to provide physical insight and quantitative data of the initial bead growth. To minimize the uncertainty problem that is inherent in the photographic analysis technique, the experiment was conducted at low speed where beads grow at a more macroscopic scale. In addition, bead identification was conducted through an image processing technique to reduce subjective interpretation. In the data analysis process, the ‘characteristic parameter’ concept was adopted to represent the bead growth properties simply. It was verified that the parameter can be extended to initial bead growth studies through the acquired bead data. It was also found that surface coverage and bead distribution, which are the critical indicators of the bead growth process, were well characterized by the parameter. Finally, the correlation between characteristic parameters and icing condition was made, by using a scaling method that can implicitly represent the icing condition variable. In the process, the scaling approach was modified to reflect the surface coverage characteristics of the bead growth, and an improvement of the correlation was achieved. It is expected that the correlation acquired from this study contribute to the modeling of roughness formation, and the methods introduced for data analysis can be applied to subsequent studies of initial bead growth

Calcium Carbonate Precipitation for CO2 Storage and Utilization: A Review of the Carbonate Crystallization and Polymorphism

The transformation of CO2 into a precipitated mineral carbonate through an ex situ mineral carbonation route is considered a promising option for carbon capture and storage (CCS) since (i) the captured CO2 can be stored permanently and (ii) industrial wastes (i.e., coal fly ash, steel and stainless-steel slags, and cement and lime kiln dusts) can be recycled and converted into value-added carbonate materials by controlling polymorphs and properties of the mineral carbonates. The final products produced by the ex situ mineral carbonation route can be divided into two categories—low-end high-volume and high-end low-volume mineral carbonates—in terms of their market needs as well as their properties (i.e., purity). Therefore, it is expected that this can partially offset the total cost of the CCS processes. Polymorphs and physicochemical properties of CaCO3 strongly rely on the synthesis variables such as temperature, pH of the solution, reaction time, ion concentration and ratio, stirring, and the concentration of additives. Various efforts to control and fabricate polymorphs of CaCO3 have been made to date. In this review, we present a summary of current knowledge and recent investigations entailing mechanistic studies on the formation of the precipitated CaCO3 and the influences of the synthesis factors on the polymorphs