A comprehensive physical-based methodology is introduced to predict weld bead properties in the Laser Edge Welding (LEW) process. Laser edge welding of AISI 316L stainless steel thin sheets are ...conducted to investigate the behavior of geometrical, mechanical and metallurgical properties of the weld bead. The effect of significant processing parameters including the laser power, speed and focal distance are considered. The method however, utilizes a set of physical-based contour plots to predict the trend of weld characteristics using the heat input and power density. A novel combined physical parameter is also introduced and optimized to indicate the exact quantitative effectiveness of each physical and processing parameter. The developed approach is utilized to analyze a broad range of weld bead characteristics. First, weld bead geometrical characteristics such as weld width, penetration and distortion are studied. The physical-based method revealed that the power density has a significant effect on the weld penetration-to-width ratio while distortion is governed by the heat input. Variations of the fracture load are analyzed based on the corresponding combined parameter. Interestingly, a greater penetration-to-width ratio results in a higher fracture load. Finally, microstructural evolutions are investigated in three main regions, including the top, middle and bottom of the weld bead. A skeletal ferrite phase is observed in the mid-zone, which increases with increase of power density. The presented methodology can be applied to a broad range of other laser materials processing techniques to obtain insightful process design tips in order to achieve tailor-made properties.
•Optical fiber sensors have several advantages for marine observation.•Marine gives a new opportunity for optical fiber sensing technology.•Overview about optical fiber sensing technology for marine ...observation.•From basic theory to different parameters monitoring in the ocean.
Optical fiber sensors have attracted considerable attention for marine environment and marine structural health monitoring, owing to advantages including resistance to electromagnetic interference, durability under extreme temperature and pressures, light weight, high transmission rate, small size and flexibility. In this paper, the optical fiber sensors employed for marine environment and marine structural health monitoring are summarized for the understanding of their basic sensing principles, and their various sensing applications such as physical parameters, chemical parameters and structural health monitoring. This review paper shows the feasibility of using optical fiber sensing technology for marine application and, due to the aforementioned advantages, it is possible to envisage a widespread use in this research field in the next few years.
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•Precursor-based method using physical parameters of MOF precursors was proposed.•BPNN models were optimized for predicting adsorptive selectivity of Xe/Kr.•Regression coefficients of ...BPNN models are all higher than 0.94.•Models were experimentally validated and proven to be reliable and generalizable.
Compared with traditional product-based prediction model, predicting adsorption and separation performance (nSP and nAPI) of Xe/Kr mixture in metal–organic frameworks (MOFs) using precursor-based prediction model can obviously enhance efficiency and save cost. In this study, nSP and nAPI of MOFs in M−IRMOF analogues database (MIAD) were calculated using Grand Canonical Monte Carlo (GCMC), Ideal Adsorbed Solution Theory (IAST). Combined with density functional theory and high-throughput screening, two novel artificial neural network models (BPNN-nSP and BPNN-nAPI) with low errors and high regression coefficients were built to predict nSP and nAPI of Xe/Kr in MOFs just using physical parameters of MOFs precursors (organic linker and metal center). In addition, tested by data of experimental MOFs, RMSE values of BPNN-nSP and BPNN-nAPI models are only 0.013 and 0.08. Therefore, these two models are reliable and generalizable for predicting nSP and nAPI, which contribute to development of nuclear power technology and satisfy industrial requirements.
The normal-stressed electromagnetic actuated fast tool servo (FTS) plays an important role in modern ultra-precision manufacturing due to its high actuation force density and fast dynamics response. ...In order to promote the design and control of the normal-stressed electromagnetic actuated FTS, this paper proposes a comprehensive dynamics model based on the principles of magnetic equivalent circuits, which can be described as a Hammerstein-like structure. The electromagnetic phenomena, including hysteresis, magnetic saturation, and eddy currents, as well as the coupling between electromagnetic and mechanical dynamics are explicitly represented in the model. Based on a simplified version of this model, an integrated optimal design method for simultaneously determining actuator and mechanism parameters of the FTS is developed with full consideration of various practical physical limitations, which is then systematically verified through the finite element analysis (FEA). Afterwards, the comprehensive model of the assembled FTS prototype is identified and experimentally verified with a two-step identification strategy. Finally, a dual-loop control scheme is employed to improve tracking accuracy while suppressing the hysteresis and lightly damped resonance. Both open-loop and closed-loop performance of the FTS prototype validate the feasibility and effectiveness of the proposed model and methods.
In this article, we consider the general task of performing Gaussian process regression (GPR) on pointwise observations of solutions of the 3 dimensional homogeneous free space wave equation. In a ...recent article, we obtained promising covariance expressions tailored to this equation: we now explore the potential applications of these formulas. We first study the particular cases of stationarity and radial symmetry, for which significant simplifications arise. We next show that the true-angle multilateration method for point source localization, as used in GPS systems, is naturally recovered by our GPR formulas in the limit of the small source radius. Additionally, we show that this GPR framework provides a new answer to the ill-posed inverse problem of reconstructing initial conditions for the wave equation from a limited number of sensors, and simultaneously enables the inference of physical parameters from these data. We finish by illustrating this “physics informed” GPR on a number of practical examples.
This paper includes examinations of thermo-physical parameters and performance evaluation of Al2O3- EG nanofluids with temperature ranging from 20 to 60 °C for volume fraction of 1.0 vol%. Two ...different surfactants of Polyvinylpyrrolidone (PVP) and Sodium Dodecyl Sulfate (SDS) are added to improve the stability of Al2O3- EG nanofluids. Firstly, sedimentation observation and TEM images confirm its stability and observe inherent morphology. Secondly, the ratio of surfactant mass fraction to volume fraction of nanofluid (ωpvp/φ) is optimized by measuring viscosity and thermal conductivity. Thirdly, two different evaluated criteria based on properties enhancement ratio (PER) and figure of merit (FOM) are used to assess the overall thermal performance of nanofluids under single phase forced convective flow. The results show that, according to TEM images and quantitatively calculated by the velocity ratio (uB/ut) of the Brownian to settling velocity ratio of nanoparticles, Al2O3 - EG nanofluids with PVP surfactant provide the best stable suspensions due to polymeric chain interaction. With the increase in PVP surfactant concentration, both viscosity and thermal conductivity firstly increase up to a maximum value, after which, it decreases. There is an optimum PVP concentration (ωpvp/φ = 0.15 for 1.0 vol% Al2O3- EG nanofluids) resulting in the highest thermal conductivity and relative low viscosity. From evaluated criteria, Al2O3-EG nanofluids with ωpvp/φ ratio ranged from 0 to 0.15 and temperature below 50 °C can be considered as efficient working fluids under the laminar and turbulent forced convective process. Therefore, this nanofluid is a promising approach for energy management in the low temperature waste heat recovery system.
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•The stability of Al2O3-EG-PVP nanofluids is qualitatively investigated by Sedimentation method and TEM images.•The degree of nanoparticles aggregation is quantitatively estimated by the Brownian to settling velocity ratio.•The effect of surfactant concentration on thermo-physical parameters is discussed.•Evaluated criteria are used to assess the thermal efficiency of Al2O3-EG nanofluids.
(AlTa0.76)xCoCrFeNi2.1 (x values in molar ratio, x = 0.1, 0.3, 0.5, 0.7, 1.0, and 1.5) alloys were designed to investigate the microstructure and mechanical properties of the eutectic high entropy ...alloys (EHEAs) consisting of FCC, B2, and Laves phases. Depending on the compositional variatio, clear microstructural variation was observed, as follows: (1) Group 1: FCC dendrite + Laves interdendrite (x = 0.1), (2) Group 2: FCC dendrite + fine-eutectic structure consisting of FCC and Laves phases (x = 0.3, 0.5 and 0.7), (3) Group 3: B2 dendrite + bimodal eutectic structure FCC/B2 +Laves (x = 1.0), (4) Group 4: Laves dendrite + eutectic structure consisting of B2 and Laves phases (x = 1.5). As the fraction of Laves or B2 phases increases, yield stress increases from 293 to 2336 MPa, while the plastic strain decreases from 50 % to 2%. Thermo-physical parameters, such as mixing entropy (ΔSmix), mixing enthalpy (ΔHmix), valence electron concentration (VEC), and atomic size difference (δr), were calculated to understand the microstructural variation. Two criteria (δr - VEC and δr - ΔHmix) were utilized to elucidate the formation of the eutectic structures in the present EHEAs, revealing the usefulness of the thermo-physical parameters in the development of EHEAs.
Physical parameter estimation of satellite is crucial in space situation awareness as it reflects valuable information. Polarimetric inverse synthetic aperture radar (Pol-ISAR) is a powerful sensor ...for space surveillance, providing rich information for satellite physical parameter estimation. Parabolic antennas, which are widely loaded in remote sensing and communication satellites, have received great attention recently. Dedicated to the space situation awareness issue using Pol-ISAR, a physical parameter joint estimation method of satellite parabolic antenna with key frame Pol-ISAR images is developed in this work. The core idea is to utilize the mapping relationship between parabolic antenna in 3-D space and its projection ellipse in 2-D ISAR image. Under special observation geometry, the closed-form expressions of parabolic antenna physical parameters are deduced for the first time, providing an efficient way for parameter estimation. Moreover, the abundant information within Pol-ISAR images is mined and utilized. Various polarimetric features are adopted for ellipse extraction and the subsequent physical parameter estimation. Compared with single-polarization channel data, the superiorities of polarimetric feature are validated using electromagnetic simulation data.
Adsorption and separation of Xe/Kr are significant for making high-density nuclear energy environmentally friendly and for meeting the requirements of the gas industry. Enhancing the accuracy of the ...adsorbate model for describing the adsorption behaviors of Xe and Kr in MOFs and the efficiency of the model for predicting the separation potential (SP) value of Xe/Kr separation in MOFs helps in searching for promising MOFs for Xe/Kr adsorption and separation within a short time and at a low cost. In this work, polarizable and transferable models for mimic Xe and Kr adsorption behaviors in MOFs were constructed. Using these models, SP values of 38 MOFs at various temperatures and pressures were calculated. An optimal neural network model called BPNN-SP was designed to predict SP value based on physical parameters of metal center (electronegativity and radius) and organic linker (three-dimensional size and polarizability) combined with temperature and pressure. The regression coefficient value of the BPNN-SP model for each data set is higher than 0.995. MAE, MBE, and RMSE of BPNN-SP are only 0.331, −0.002, and 0.505 mmol/g, respectively. Finally, BPNN-SP was validated by experiment data from six MOFs. The transferable adsorbate model combined with the BPNN-SP model would highly improve the efficiency for designing MOFs with high performance for Xe/Kr adsorption and separation.
