Sequential Monte Carlo Methods for System Identification

One of the key challenges in identifying nonlinear and possibly non-Gaussian state space models (SSMs) is the intractability of estimating the system state. Sequential Monte Carlo (SMC) methods, such as the particle filter (introduced more than two decades ago), provide numerical solutions to the nonlinear state estimation problems arising in SSMs. When combined with additional identification techniques, these algorithms provide solid solutions to the nonlinear system identification problem. We describe two general strategies for creating such combinations and discuss why SMC is a natural tool for implementing these strategies.Comment: In proceedings of the 17th IFAC Symposium on System Identification (SYSID). Added cover pag

Управление рисками как способ обеспечения экономической безопасности предприятия

Материалы XV Междунар. науч.-техн. конф. студентов, аспирантов и молодых ученых, Гомель, 23–24 апр. 2015 г

Core–Shell Carbon Nanofibers-NiFe Structure on 3D Porous Carbon Foam: Facilitating a Promising Trajectory toward Decarbonizing Energy Production

In this work, a low-cost, light-weight, highly efficient, and durable electrode in which NiFe-layered double hydroxide is electrodeposited on a carbon nanofiber (CNF) core supported on a carbon foam (CF) is introduced. The resulting 3D NiFe-CNFs-CF electrode shows excellent oxygen evolution reaction and hydrogen evolution reaction performance in alkaline media. When used as an anode and a cathode in the same cell, a current density of 10 mA cm−2 is achieved, at a cell voltage of 1.65 V. Moreover, good stability over a long testing time (50 h) is demonstrated. The ternary hybrid electrode gives rise to an excellent performance-to-weight ratio owing to its very low bulk density (≈34 mg cm−3) inherited from super lightweight components composed of CF and CNFs. The developed electrode can potentially be used in large-scale alkaline water electrolysis, in facilities such as offshore hydrogen production platforms, which can complement the variable renewable energy production of wind farms through hydrogen storage and fuel cells.</p

Stainless Steel as A Bi-Functional Electrocatalyst – A Top-Down Approach

For a hydrogen economy to be viable, clean and economical hydrogen production methods are vital. Electrolysis of water is a promising hydrogen production technique with zero emissions, but suffer from relatively high production costs. In order to make electrolysis of water sustainable, abundant, and efficient materials has to replace expensive and scarce noble metals as electrocatalysts in the reaction cells. Herein, we study activated stainless steel as a bi-functional electrocatalyst for the full water splitting reaction by taking advantage of nickel and iron suppressed within the bulk. The final electrocatalyst consists of a stainless steel mesh with a modified surface of layered NiFe nanosheets. By using a top down approach, the nanosheets stay well anchored to the surface and maintain an excellent electrical connection to the bulk structure. At ambient temperature, the activated stainless steel electrodes produce 10 mA/cm(2) at a cell voltage of 1.78 V and display an onset for water splitting at 1.68 V in 1M KOH, which is close to benchmarking nanosized catalysts. Furthermore, we use a scalable activation method using no externally added electrocatalyst, which could be a practical and cheap alternative to traditionally catalyst-coated electrodes

High pressure studies of alkali metal doped fullerides A4C60

The electrical resistance R of K4C60 and Li4C60 has been measured between 100 and 300 K under pressures up to 1 and 2 GPa, respectively. For both materials, the temperature coefficient of R is negative at all pressures and temperatures in this range. The transport properties of Li4C60 at low pressure are compatible with a recent observation of high ionic conductivity, but surprisingly, this conductivity term increases strongly with increasing pressure, contradicting an intuitive model. For K4C60 we see no sign of a recently suggested structural phase transformation at low temperature, nor can we find any convincing evidence for a lattice disproportionation as recently observed for Rb4C60

Bayesian nonparametric identification of piecewise affine ARX systems

We introduce a Bayesian nonparametric approach to identification of piecewise affine ARX systems. The clustering properties of the Dirichlet process are used to construct a prior over the partition of the regressor space as well as the parameters of each local model. This enables us to probabilistically reason about and to identify the number of modes, the partition of the regressor space, and the linear dynamics of each local model from data. By appropriate choices of base measure and likelihood function, we give explicit expressions for how to perform both inference and prediction. Simulations and experiments on real data from a pick and place machine are used to illustrate the capabilities of the new approach

Hydrogen Evolution Reaction Activity of Heterogeneous Materials : A Theoretical Model

In this study, we present a new comprehensive methodology to quantify the catalytic activity of heterogeneous materials for the hydrogen evolution reaction (HER) using ab initio simulations. The model is composed of two parts. First, the equilibrium hydrogen coverage is obtained by an iterative evaluation of the hydrogen adsorption free energies (ΔGH) using density functional theory calculations. Afterward, the ΔGH are used in a microkinetic model to provide detailed characterizations of the entire HER considering all three elementary steps, i.e., the discharge, atom + ion, and combination reactions, without any prior assumptions of rate-determining steps. The microkinetic model takes the equilibrium and potential-dependent characteristics into account, and thus both exchange current densities and Tafel slopes are evaluated. The model is tested on several systems, from polycrystalline metals to heterogeneous molybdenum disulfide (MoS2), and by comparing to experimental data, we verify that our model accurately predicts their experimental exchange current densities and Tafel slopes. Finally, we present an extended volcano plot that correlates the electrical current densities of each elementary reaction step to the coverage-dependent ΔGH

Electrochemical N2 reduction at ambient condition : overcoming the selectivity issue via control of reactants' availabilities

Ammonia production via the electrochemical N2 reduction reaction (NRR) at ambient conditions is highly desired as an alternative to the Haber-Bosch process, but remains a great challenge due to the low efficiency and selectivity caused by the competing hydrogen evolution reaction (HER). Herein we investigate the effect of availabilities of reactants (protons, electrons and N2) on NRR using a FeOx-coated carbon fiber paper cathode in various electrochemical configurations. NRR is found viable only under the conditions of low proton- and high N2 availabilities, which are achieved using 0.12 vol% water in LiClO4-ethyl acetate electrolyte and gaseous N2 supplied to the membrane-electrode assembly cathode. This results in an NRR rate of 29 ± 19 pmolNH3 s−1 cm−2 at a Faradaic efficiency of 70 ± 24% at the applied potential of −0.1 V vs. NHE. Other conditions (high proton-, or low N2-availability, or both) yield a lower or negligible amount of ammonia due to the competing HER. Our work shows that promoting NRR by suppressing the HER requires optimization of the operational variables, which serves as a complementary strategy to the development of NRR catalysts