Pitting damage levels estimation for planetary gear sets based on model simulation and grey relational analysis

The planetary gearbox is a critical mechanism in helicopter transmission systems. Tooth failures in planetary gear sets will cause great risk to helicopter operations. A gear pitting damage level estimation methodology has been devised in this paper by integrating a physical model for simulation signal generation, a three-step statistic algorithm for feature selection and damage level estimation for grey relational analysis. The proposed method was calibrated firstly with fault seeded test data and then validated with the data of other tests from a planetary gear set. The estimation results of test data coincide with the actual test records, showing the effectiveness and accuracy of the method in providing a novel way to model based methods and feature selection and weighting methods for more accurate health monitoring and condition prediction

Adjoint sensitivity analysis of the two-phase two-fluid model based on an approximate Riemann solver

A new shock-capturing upwind numerical solver (i.e. forward solver) and an adjoint sensitivity analysis framework for the two-phase two-fluid model are developed and verified. Both the numerical solver and the adjoint sensitivity analysis framework are based on an analytical analysis of the two-phase two-fluid model. The challenge (due to the arbitrary equation of state) in the analytical analysis of the two-phase system is overcome by introducing several new auxiliary variables. With the help of new auxiliary variables and thermodynamic transformations, the Jacobian matrix of the system can be simplified to a well-structured form, which is convenient for an analytical analysis. Approximate eigenvalues and eigenvectors are obtained using the difference in the thermodynamic properties of liquid and gas phases. The approximate eigenvalues and eigenvectors are essential for constructing the upwind numerical solver, because they provide correct upwind information of the system. Both the numerical solver and the adjoint sensitivity analysis framework are verified with several numerical tests. For the forward tests, the results show that the solver is stable, accurate, and robust. Results from the new solver are in a very good agreement with either analytical solution or measurement data. The grid convergence study shows that the solver using a Roe-type numerical flux is first-order accurate in space and the solver using a WENO-type numerical flux is at least second-order accurate in space. For the adjoint tests, the results show that the adjoint sensitivity analysis framework works well for both steady-state problems and time-dependent problems. The adjoint sensitivities (with respect to initial conditions, boundary conditions, or physical model parameters) are verified by either analytical sensitivities or forward sensitivities. A critical and unique feature of the new solver is that the formulation does not depend on the form of equation of state, which ensures that the solver is applicable to practical two-phase flow problems, such as a boiling pipe. The successful application of the solver to a boiling pipe is very encouraging, as it opens up the possibility of applying many other advanced methods to two-phase flow problems

Inverse uncertainty quantification of trace physical model parameters using Bayesian analysis

Forward quantification of uncertainties in code responses require knowledge of input model parameter uncertainties. Nuclear thermal-hydraulics codes such as RELAP5 and TRACE do not provide any information on physical model parameter uncertainties. A framework was developed to quantify input model parameter uncertainties based on Maximum Likelihood Estimation (MLE), Bayesian Maximum A Priori (MAP), and Markov Chain Monte Carlo (MCMC) algorithm for physical models using relevant experimental data. The objective of the present work is to perform the sensitivity analysis of the code input (physical model) parameters in TRACE and calculate their uncertainties using an MLE, MAP and MCMC algorithm, with a particular focus on the subcooled boiling model. The OECD/NEA BWR full-size fine-mesh bundle test (BFBT) data will be used to quantify selected physical model uncertainty of the TRACE code. The BFBT is based on a multi-rod assembly with measured data available for single or two-phase pressure drop, axial and radial void fraction distributions, and critical power for a wide range of system conditions. In this thesis, the steady-state cross-sectional averaged void fraction distribution from BFBT experiments is used as the input for inverse uncertainty algorithm, and the selected physical model’s Probability Distribution Function (PDF) is the desired output quantity

FedMGDA+: Federated Learning meets Multi-objective Optimization

Federated learning has emerged as a promising, massively distributed way to train a joint deep model over large amounts of edge devices while keeping private user data strictly on device. In this work, motivated from ensuring fairness among users and robustness against malicious adversaries, we formulate federated learning as multi-objective optimization and propose a new algorithm FedMGDA+ that is guaranteed to converge to Pareto stationary solutions. FedMGDA+ is simple to implement, has fewer hyperparameters to tune, and refrains from sacrificing the performance of any participating user. We establish the convergence properties of FedMGDA+ and point out its connections to existing approaches. Extensive experiments on a variety of datasets confirm that FedMGDA+ compares favorably against state-of-the-art.Comment: 26 pages, 9 figures; initial draft, comments welcome

Effects of Cryogenic Treatment after Annealing of Ti-6Al-4V Alloy Sheet on Its Formability at Room Temperature

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This is an Open Access article made available under the terms of the Creative Commons Attribution licence CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.In this article, the effects of cryogenic treatment after annealing on the formability of Ti-6Al-4V alloy sheet were experimentally studied. The Ti-6Al-4V titanium alloy was treated by cryogenic treatment after annealing (ACT). Tensile tests were carried out using a universal machine at room temperature. The microstructure evolution of Ti-6Al-4V subjected to ACT was also investigated using an optical microscope (OM). Both the shearing performance and drawing formability were analyzed by punch shearing tests and deep drawing tests, respectively. Results showed that after ACT, the tendency of the β phase can be apparently changing into stable β’ and α’ phases. The elastic modulus is lower than that of the untreated material. It was found that both the yield strength and tensile strength are declined slightly, whereas the ductility is increased significantly. The shear strength in punch shearing is decreased at room temperature and cryogenic temperature. The ratio of smooth zone on the section after ACT3 is much larger than the others. The rollover diameters are not obviously greater than those of the untreated. Additionally, the height of the burr shows a decreasing trend after ACT. During deep drawing, drawing depth is deeper than that of the untreated material, the drawing load after ACT is reduced, and the decreasing tendency of the drawing load slows down. It is noted that the micro-cracks occur at the bottom of the sample.Peer reviewe

Eradication of unresectable liver metastasis through induction of tumour specific energy depletion.

Treatment of liver metastasis experiences slow progress owing to the severe side effects. In this study, we demonstrate a strategy capable of eliminating metastatic cancer cells in a selective manner. Nucleus-targeting W18O49 nanoparticles (WONPs) are conjugated to mitochondria-selective mesoporous silica nanoparticles (MSNs) containing photosensitizer (Ce6) through a Cathepsin B-cleavable peptide. In hepatocytes, upon the laser irradiation, the generated singlet oxygen species are consumed by WONPs, in turn leading to the loss of their photothermally heating capacity, thereby sparing hepatocyte from thermal damage induced by the laser illumination. By contrast, in cancer cells, the cleaved peptide linker allows WONPs and MSNs to respectively target nucleus and mitochondria, where the therapeutic powers could be unleashed, both photodynamically and photothermally. This ensures the energy production of cancer cells can be abolished. We further assess the underlying molecular mechanism at both gene and protein levels to better understand the therapeutic outcome

A bearing fault detection method based on compressive measurements of vibration signal

The general method for bearing fault detection is achieved by using bearing vibration signals which sampled in the frame of Shannon sampling theory. So it is necessary to sample and save abundant original vibration data in the process of uninterrupted monitoring, and this will generate masses of original data which would burden the storage and transmission. For this issue, a fault detection method based on compressed sensing theory is proposed in this paper. It only needs to sample and save fewer compressive measurements of bearing vibration signal directly compared to original signal. There is no need to recover the original signal accurately for detecting bearing faults, while it just requires referring to the prior training result and reconstructing the overall energy distribution of the original signal in some transform domain. The availability and effectiveness of the method proposed is validated with bearing vibration signals sampled in practice

Environmental economic impact assessment in China: Problems and prospects

The use of economic valuation methods to assess environmental impacts of projects and policies has grown considerably in recent years. However, environmental valuation appears to have developed independently of regulations and practice of environmental impact assessment (EIA), despite its potential benefits to the EIA process. Environmental valuation may be useful in judging significance of impacts, determining mitigation level, comparing alternatives and generally enabling a more objective analysis of tradeoffs. In China, laws and regulations require the use of environmental valuation in EIA, but current practice lags far behind. This paper assesses the problems and prospects of introducing environmental valuation into the EIA process in China. We conduct four case studies of environmental economic impact assessment (EEIA), three of which are based on environmental impact statements of construction projects (a power plant, a wastewater treatment plant and a road construction project) and one for a regional pollution problem (wastewater irrigation). The paper demonstrates the potential usefulness of environmental valuation but also discusses several challenges to the introduction and wider use of EEIA, many of which are likely to be of relevance far beyond the Chinese context. The paper closes with suggesting some initial core elements of an EEIA guidelineEnvironmental impact assessment; Environmental valuation; China; Economic analysis