Ice Gouge Depth Determination Via an Efficient Stochastic Dynamics Technique

A simplified model of the motion of a grounding iceberg for determining the gouge depth into the seabed is proposed. Specifically, taking into account uncertainties relating to the soil strength, a nonlinear stochastic differential equation governing the evolution of the gouge length/depth in time is derived. Further, a recently developed Wiener path integral (WPI) based approach for solving approximately the nonlinear stochastic differential equation is employed; thus, circumventing computationally demanding Monte Carlo based simulations and rendering the approach potentially useful for preliminary design applications. The accuracy/reliability of the approach is demonstrated via comparisons with pertinent Monte Carlo simulation (MCS) data

One-step synthesis of metal/oxide nanocomposites by gas phase condensation

Metallic nanoparticles (NPs), either supported on a porous oxide framework or finely dispersed within an oxide matrix, find applications in catalysis, plasmonics, nanomagnetism and energy conversion, among others. The development of synthetic routes that enable to control the morphology, chemical composition, crystal structure and mutual interaction of metallic and oxide phases is necessary in order to tailor the properties of this class of nanomaterials. With this work, we aim at developing a novel method for the synthesis of metal/oxide nanocomposites based on the assembly of NPs formed by gas phase condensation of metal vapors in a He/O2 atmosphere. This new approach relies on the independent evaporation of two metallic precursors with strongly different oxidation enthalpies. Our goal is to show that the precursor with less negative enthalpy gives birth to metallic NPs, while the other to oxide NPs. The selected case study for this work is the synthesis of a Fe-Co/TiOx nanocomposite, a system of great interest for its catalytic and magnetic properties. By exploiting the new concept, we achieve the desired target, i.e., a nanoscale dispersion of metallic alloy NPs within titanium oxide NPs, the structure of which can be tailored into TiO1-\u3b4 or TiO2 by controlling the synthesis and processing atmosphere. The proposed synthesis technique is versatile and scalable for the production of many NPs-assembled metal/oxide nanocomposites

Investigations on nucleophilic layers made with a novel plasma jet technique

In this work a novel plasma jet technique is used for the deposition of nucleophilic films based on (3-aminopropyl)trimethoxysilane at atmospheric pressure. Film deposition was varied with regard to duty cycles and working distance. Spectral ellipsometry and chemical derivatization with 4-(trifluoromethyl)benzaldehyde using ATR- FTIR spectroscopy measurements were used to characterize the films. It was found that the layer thickness and the film composition are mainly influenced by the duty cycle

Uncertainty Quantification of Power Spectrum and Spectral Moments Estimates Subject to Missing Data

In this paper, the challenge of quantifying the uncertainty in stochastic process spectral estimates based on realizations with missing data is addressed. Specifically, relying on relatively relaxed assumptions for the missing data and on a kriging modeling scheme, utilizing fundamental concepts from probability theory, and resorting to a Fourier-based representation of stationary stochastic processes, a closed-form expression for the probability density function (PDF) of the power spectrum value corresponding to a specific frequency is derived. Next, the approach is extended for also determining the PDF of spectral moments estimates. Clearly, this is of significant importance to various reliability assessment methodologies that rely on knowledge of the system response spectral moments for evaluating its survival probability. Further, utilizing a Cholesky decomposition for the PDF-related integrals kept the computational cost at a minimal level. Several numerical examples are included and compared against pertinent Monte Carlo simulations for demonstrating the validity of the approach

A review of stochastic sampling methods for Bayesian inference problems

This study was done with the aim to analyze and evaluate the strengths and limitations of the Markov Chain Monte-Carlo (MCMC), Transitional Markov Chain Monte-Carlo (TMCMC), and Sequential Monte-Carlo (SMC) sampling methods in the context of solving engineering design problems. For each of these methods discussed in this paper, a case example will also be presented in the form of simple toy-model problems to demonstrate its use and effectiveness in estimating parameters under uncertainty and comparing it with determined results. For the MCMC case example, a simple harmonic oscillator will be looked into to estimate the value of the spring constant, k. For the TMCMC case example, the problem will be extended into a coupled oscillator problem and the goal would be to estimate the values of two spring constants to which there is imprecise knowledge: κ and κ12. Finally, for the SMC case example, a simple harmonic oscillator will be analyzed once again as a static linear system to estimate the spring constant, k. As such, this conference paper is also targeted at readers who are new to these methods and to provide succinct information in facilitating the understanding of the three sampling approaches

Tuning ZnO nanorods photoluminescence through atmospheric plasma treatments

Room temperature atmospheric plasma treatments are widely used to activate and control chemical functionalities at surfaces. Here, we investigated the effect of atmospheric pressure plasma jet (APPJ) treatments in reducing atmosphere (Ar/1 parts per thousand H-2 mixture) on the photoluminescence (PL) properties of single crystal ZnO nanorods (NRs) grown through hydrothermal synthesis on fluorine-doped tin oxide glass substrates. The results were compared with a standard annealing process in air at 300 degrees C. Steady-state photoluminescence showed strong suppression of the defect emission in ZnO NRs for both plasma and thermal treatments. On the other side, the APPJ process induced an increase in PL quantum efficiency (QE), while the annealing does not show any improvement. The QE in the plasma treated samples was mainly determined by the near band-edge emission, which increased 5-6 fold compared to the as-prepared samples. This behavior suggests that the quenching of the defect emission is related to the substitution of hydrogen probably in zinc vacancies (V-Zn), while the enhancement of UV emission is due to doping originated by interstitial hydrogen (H-i), which diffuses out during annealing. Our results demonstrate that atmospheric pressure plasma can induce a similar hydrogen doping as ordinarily used vacuum processes and highlight that the APPJ treatments are not limited to the surfaces but can lead to subsurface modifications. APPJ processes at room temperature and under ambient air conditions are stable, convenient, and efficient methods, compared to thermal treatments to improve the optical and surface properties of ZnO NRs, and remarkably increase the efficiency of UV emission. (c) 2019 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)

Derivative based global sensitivity measures

The method of derivative based global sensitivity measures (DGSM) has recently become popular among practitioners. It has a strong link with the Morris screening method and Sobol' sensitivity indices and has several advantages over them. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is generally much lower than that for estimation of Sobol' sensitivity indices. This paper presents a survey of recent advances in DGSM concerning lower and upper bounds on the values of Sobol' total sensitivity indices $S\_{i}^{tot}$. Using these bounds it is possible in most cases to get a good practical estimation of the values of $S\_{i}^{tot}$. Several examples are used to illustrate an application of DGSM

A novel plasma jet with RF and HF coupled electrodes

In order to achieve low processing temperature and efficient coatings deposition for manufacturing applications, a novel torch has been developed that couples in a double DBD design high frequency (HF ~17 kHz) and radio frequency (RF ~27 MHz) excitations. The design allows to obtain a stable RF plasma also in reactive processes and with the possibility to control on the treated substrates ions flux and surface charging, avoiding the micro-discharges. The plasma has been electrically and optically characterized by emission spectroscopy

Low-Cost Battery Monitoring by Converter-Based Electrochemical Impedance Spectroscopy

The use of batteries and other electrochemical devices in modern power systems is rapidly increasing, with stricter requirements in terms of cost, efficiency and reliability. Innovative monitoring solutions are therefore urged to allow a successful development of a wide range of emerging applications, including electric vehicles and large-scale energy storage to support renewable energy generation. Presently, a huge gap still exists between the accurate and sophisticated monitoring techniques commonly employed in laboratory tests, on the one hand, and the simple and rough solutions available in most commercial applications, on the other hand. The objective of this paper is therefore to contribute to the development of low-cost but accurate solutions for commercial battery condition monitoring, by proposing an embedded system that combines real-time digital signal processing with the high computational power and user friendly interface of a modern computer, at a cost comparable to a simple micro-controller. In more detail, the paper focuses on electrochemical impedance spectroscopy on a battery performed by a DC-DC power converter, and it explains how the proposed low-cost off-the-shelf hardware can control the converter, acquire the measurement signals, accurately process them in the time and frequency domains, and estimate the result uncertainty in real-time, which is necessary to promptly and reliably detect any variation in the battery condition