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Khasin, Michael

Publications and source records attributed to Khasin, Michael.

Parameters Inference and Model Reduction for the Single-Particle Model of Li Ion Cells

The Single-Particle Model (SPM) of Li ion cell is a computationally efficient model for simulating Li ion cell for weak to moderate currents. The model depends n a number of parameters describing the geometry and material properties of a cell components. In order to apply the model to simulating a cell, the best-fit parametric values have to be inferred from a constant discharge data. We report our efforts to determine the best-fit set for 18650 LP batteries. We found that rather than being best-fit by a particular point in the parametric space the data is fit equally well by an ensemble of points clustering about an effective multidimensional manifold in the parametric space. This property of the SPM is known to be shared by a multitude of the so-called "sloppy models" of complex systems, characterized by a few stiff directions in the parametric space, in which the predicted behavior varies significantly, and a number of sloppy directions in which the behavior doesn't change appreciably. Only the stiff parameters combinations are identifiable. Geometrical features of the BFM give insights to possible reduction of the SPM to a model having fewer sloppy parameters. We have constructed a hierarchy of such models. The fully reduced model depends on only stiff effective parameters which are identifiable and can be used for characterization of the battery's state of health.

Khasin, Michael↗

Spectral Mass Gauging of Unsettled Liquid with Acoustic Waves

Propellant mass gauging is one of the key technologies required to enable the next step in NASA's space exploration program. At present, there is no reliable method to accurately measure the amount of unsettled liquid propellant of an unknown configuration in a propellant tank in micro- or zero gravity. We propose a new approach to use sound waves to probe the resonance frequencies of the two-phase liquid-gas mixture and take advantage of the mathematical properties of the high frequency spectral asymptotics to determine the volume fraction of the tank filled with liquid. We report the current progress in exploring the feasibility of this approach, both experimental and theoretical. Excitation and detection procedures using solenoids for excitation and both hydrophones and accelerometers for detection have been developed. A 3% uncertainty for mass-gauging was demonstrated for a 200-liter tank partially filled with water for various unsettled configurations, such as tilts and artificial ullages. A new theoretical formula for the counting function associated with axially symmetric modes was derived. Scaling analysis of the approach has been performed to predict an adequate performance for in-space applications.

Feller, Jeffrey↗

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics↗

Inferential Framework for Autonomous Cryogenic Loading Operations

We address problem of autonomous cryogenic management of loading operations on the ground and in space. As a step towards solution of this problem we develop a probabilistic framework for inferring correlations parameters of two-fluid cryogenic flow. The simulation of two-phase cryogenic flow is performed using nearly-implicit scheme. A concise set of cryogenic correlations is introduced. The proposed approach is applied to an analysis of the cryogenic flow in experimental Propellant Loading System built at NASA KSC. An efficient simultaneous optimization of a large number of model parameters is demonstrated and a good agreement with the experimental data is obtained.

Luchinsky, Dmitry G.↗

Risk Assessment and Scaling for the SLS LH2 ET

In this report the main physics processes in LH2 tank during prepress and rocket flight are studied. The goal of this investigation is to analyze possible hazards and to make risk assessment in proposed LH2 tank designs for SLS with 5 engines (the situation with 4 engines is less critical). For analysis we use the multinode model (MNM) developed by us and presented in a separate report and also 3D ANSYS simulations. We carry out simulation and theoretical analysis the physics processes such as (i) accumulation of bubbles in LH2 during replenish stage and their collapsing in the liquid during the prepress; (ii) condensation-evaporation at the liquid-vapor interface and tank wall, (iv) heating the liquid near the interface and wall due to condensation and environment heat, (v) injection of hot He during prepress and of hot GH2 during flight, (vi) mixing and cooling of the injected gases due to heat transfer between the gases, liquid and the tank wall. We analyze the effects of these physical processes on the thermo- and fluid gas dynamics in the ullage and on the stratification of temperature in the liquid and assess the associated hazards. A special emphasize is put on the scaling predictions for the larger SLS LH2 tank.

Hafiychuk, Halyna↗

Risk Assessment and scaling for the SLS LOx ET

In this report we analyze the transpiration cooling by He bubble injection of the long LOx tank feedline heated by the environment heat. We consider possible hazards that can arise in the proposed design of the SLS core stage where the feedline length is much longer than that used in the Space Shuttle.

Osipov, Viatcheslav V.↗