Physics-based Analysis Research Articles

(Invited) Joint Time-frequency Analysis of Lithium-ion Batteries Undergoing Dynamic EIS

Joint time-frequency analysis (JTFA) is an important domain of signal processing that is widely applied as a real time diagnostic tool in acoustics, optics, and electronics. The conversion of time series data into dynamic spectral components can be accomplished using a variety of mathematical transforms, such as short-time Fourier transforms (st-FTs), Gabor expansions, wavelets, and others.[1] Electrochemists have used JTFA methods for probing dynamic change in lithium ion batteries undergoing active charge or discharge when the applied current has a superimposed small amplitude oscillation of frequency w. These methods are sometimes called dynamic electrochemical impedance spectroscopy (DEIS) or in situ EIS, and typically involve st-FTs of the voltage and current to get an impedance-like response function.[2,3] Physics-based analysis of DEIS experiments, when performed at all, has involved computationally expensive brute force calculations of the full time series response, followed by st-FT analysis.[4] In this invited talk, we explore the math and physics associated with efficient computations of the dynamic st-FT voltage spectrum generated by batteries undergoing active charge or discharge when the applied current has a superimposed small amplitude oscillation of frequency w. Computationally efficient physics-based predictions of battery st-FT voltage spectra have the potential to significantly improve the value of this diagnostic method for applications such as super fast charging, especially if the underlying physics revealed by the st-FT spectrum can be connected to degradation and safety. Our approach is to apply st-FTs to the physics-based pseudo-two dimensional (P2D) model of a lithium ion battery prior to solving, transforming the time domain equations into a hierarchical set of mixed time and frequency domain equations that are separated by time-scales and sequentially solvable. Slow dynamics associated with the charge-discharge cycle are solved in the time domain and faster dynamics from current oscillations are solved in the frequency domain. Slow time domain terms are included in the frequency domain solutions, creating a mixed time-frequency set of equations for the st-FT voltage spectra that is efficient to solve. The governing equations show the impedance-like nature of the dynamic voltage signal as a function of frequency w, while also clearly revealing time-dependent differences between DEIS and stationary EIS that offers insights into the method as a real-time diagnostic of batteries. Using realistic Li-ion battery model parameters, we show how the selected frequency, C-rate, and cell charge-discharge history affects the st-FT voltage signal amplitude and phase. We evaluate the dynamic results as the battery cycles through different states of charge, and compare DEIS impedance-like response to the stationary EIS signals at the same states. Finally, we show some of our initial experimental results looking at this method from a theory-based perspective. References Qian and D. Chen, IEEE Signal Proc. Mag., 16(2), 52-67 (1999).Itagaki, K. Honda, Y. Hoshi, and I. Shitanda, J. Electroanal. Chem., 737, 78–84 (2015).Huang, Z. Li, J.B. Zhang, J. Power Sources, 273, 1098-1102 (2015).Huang and J.B. Zhang, J. Electrochem. Soc., 163 (9), A1983-A2000 (2016).

Interactions between vortical, acoustic and thermal components during hypersonic transition

Discrete unstable modes of hypersonic laminar boundary layers, obtained from an eigenvalue analysis, provide insight into key transition scenarios. The character of such modes near the leading edge is often identified with the corresponding asymptotic free-stream behaviour of acoustic, vortical or entropic (thermal) content, which we designate fluid-thermodynamic (FT) components. In downstream regions, however, this direct one-to-one correspondence between discrete modes and FT components does not hold, since FT components interact in well-defined ways with the basic state and with each other (even under linear scenarios). In the present work, we perform an FT decomposition of discrete modes using momentum potential theory, to yield a physics-based analysis that complements linear stability theory in the linear regime, and seamlessly extends to the nonlinear domain where direct numerical simulations are appropriate. Linear and nonlinear saturated disturbance effects, different forcing types and wall thermal conditions are considered, with emphasis on phenomena occurring near stability-mode synchronization locations. The results show that, in the linear regime, each discrete mode contains all FT components, whose relative amplitudes vary with streamwise distance. Vortical components are always the largest, followed by thermal and acoustic components. These latter two show distinct fore and aft signatures near mode synchronization. The vortical component displays a series of rope-shaped recirculation-cell patterns across the generalized inflection point. However, both acoustic and thermal components display ‘trapped’ structures. The former contains an alternating monopole array between the wall and the critical layer, while the latter is confined to an undulating region between the wall and a wavy locus straddling the generalized inflection point. Nonlinear saturation in the region of Mack-mode growth further strengthens the rope-shaped structures in the vortical component and higher harmonics appear, whose form and location depend on the specific component. Wall cooling modifies the eigenfunctions such that the acoustic component accounts for more of its composition, consistent with its destabilization. Analysis of energy interactions among the FT components indicates that, even though the vorticity component is the largest, the thermal component induces the most significant source term for the growth of acoustic perturbations, possibly due to the trapped nature of both.

Role of flying cars in sustainable mobility

Interest and investment in electric vertical takeoff and landing aircraft (VTOLs), commonly known as flying cars, have grown significantly. However, their sustainability implications are unclear. We report a physics-based analysis of primary energy and greenhouse gas (GHG) emissions of VTOLs vs. ground-based cars. Tilt-rotor/duct/wing VTOLs are efficient when cruising but consume substantial energy for takeoff and climb; hence, their burdens depend critically on trip distance. For our base case, traveling 100 km (point-to-point) with one pilot in a VTOL results in well-to-wing/wheel GHG emissions that are 35% lower but 28% higher than a one-occupant internal combustion engine vehicle (ICEV) and battery electric vehicle (BEV), respectively. Comparing fully loaded VTOLs (three passengers) with ground-based cars with an average occupancy of 1.54, VTOL GHG emissions per passenger-kilometer are 52% lower than ICEVs and 6% lower than BEVs. VTOLs offer fast, predictable transportation and could have a niche role in sustainable mobility.

Twofold Variation Propagation Modeling and Analysis for Roll-to-Roll Manufacturing Systems

Roll-to-roll (R2R) manufacturing has emerged as one of the most cost-effective manufacturing techniques for high-volume production of flexible printing electronics, graphene films, thin-film batteries, and solar cells, as opposed to low-volume batch production. However, in practice, real-time monitoring of the R2R process and in situ measurement of fabricated materials during production are challenging because of the high speed and dynamic variation of the web. In addition, due to the lack of cost-effective sensors and in-line metrology systems with a large range and high resolution, effective quality control and defect diagnosis are difficult to achieve. To address these challenges, this paper aims to develop analytical models that can serve as virtual sensing and metrology tools to quantify process state variation and estimate product quality in R2R processes with limited accessibility of in situ sensor. First, the quality variation propagation mechanism in R2R processes is investigated. Second, a hybrid multistage modeling method is proposed to characterize the twofold variation propagation—product-centric and process-centric variations, and its relationship with product quality in R2R processes. Note to Practitioner s—The novel modeling method developed in this paper employs both physics-based analysis (e.g., web handling system dynamics) and regression methods [e.g., censored regression and linear/logistic regression (LG)] using multisensor signals. The estimation results from the model can serve as virtual sensing and virtual metrology tools to increase the system visibility and be applied for process monitoring and error detection in real time. A print registration unit of elastic film in a roll-to-roll system is employed to demonstrate and validate the proposed modeling method in terms of the accuracy of state estimates and quality prediction. Based on the comparison results, the hybrid modeling method shows higher accuracy in state estimation and quality prediction than do the models with data-driven methods only.

FV-MP model to predict lean blowout limits for multi-point lean direct injection combustors

The lean blowout (LBO) limit is a crucial performance for aircraft engine combustors. It is essential to obtain the LBO limit during the design stage of the aircraft engine combustors. The semi-empirical correlation is an important tool for quick prediction of the LBO limits. Among all the semi-empirical correlations for the prediction of the LBO limits, Lefebvre's LBO model is widely used for the swirl stabilized combustors. The Flame Volume (FV) model was proposed based on Lefebvre's LBO model to accommodate the effects of the geometry of the flame tube on the LBO. Meanwhile, the multi-point lean direct injection (MPLDI) combustor whose geometry of the dome is different from the traditional combustors is a promising low NOx emission combustor. Up to now, there are few existing semi-empirical correlations to predict the LBO limit for the MPLDI combustors although the prediction of the LBO limit is critical for them. Based on the FV concept and new physics-based analysis, the FV-MP (Flame Volume for the Multi-Point) model is derived to predict the LBO limits for the MPLDI combustors. The FV-MP model could accommodate the effects of the fuel staging and recessed pilot stage, in addition to the operating conditions, on the LBO limits of the MPLDI combustors and achieve better prediction accuracy than both the FV and Lefebvre's LBO models within the range of corresponding validation experiments. Compared with Lefebvre's LBO model, the FV model could double the prediction accuracy. Compared with the FV model, the FV-MP model could further double the prediction accuracy.

A physics-based framework for analyzing the resilience of interdependent civil infrastructure systems: A climatic extreme event case in Hong Kong

Operationalizing resilience concepts and principles, in particular when interdependency is considered, remains a major challenge for the sustainable development of urban infrastructures and future cities. From theoretical perspective, not only does it call for sector-specific infrastructure asset management knowledge, traditional risk-based disaster analysis and emergency management techniques, but it also demands quality data and stakeholders’ competency to holistically integrate the information and analyze the data. To address these limitations, this research provides a physics-based synthesis framework for interdependent civil infrastructure system resilience analysis. The framework consists of four major components: (i) setting resilience analysis boundary through the prescribed criteria; (ii) establishing an infrastructure resilience management lifecycle; (iii) defining the physics-based modeling of infrastructure system functions; and (iv) designing the interfaces between interdependent infrastructure systems. The feasibility and applicability of the proposed framework are tested through a case study involving two interconnected infrastructure systems (i.e. stormwater drainage system and road transport system) located in Hong Kong. It incorporates relevant infrastructure information by using the ArcGIS platform which is integrated with the physics-based vulnerability analysis methods from the two distinct knowledge domains. Cascading effects of adverse events propagating through the two infrastructures are delineated using an empirical nominal damage function.

A Physics-Based Model Capacity Fade Analysis of LiMn2O4/Graphite Cell at Different Temperatures

The capacity fading behavior of a LiMn2O4/graphite lithium ion cells at different temperatures is analyzed using a physics-based porous composite electrode model and a parameter estimation technique. The parameter estimation technique is used to extract capacity fade dependent model parameters from experimental cycling data. Although the capacity fading mechanism of the LiMn2O4/graphite lithium ion cells are greatly influenced by temperature, major capacity fading mechanism is closely related to the trapping of Li ions into solid electrolyte interphase on the graphite negative electrode and the reduction in the volume fraction of the active material in the LiMn2O4 positive electrode. At 25°C, the dominant capacity fading mechanisms is the formation of the solid electrolyte interphase while at 60°C the dominant capacity fading mechanism is the reduction in the volume fraction of the positive active material. The efficacy of the physics-based composite electrode model is validated with experimental discharge profiles obtained from cells cycled at 25 and 60°C.

Assessing impact of uncertainties in decline curve analysis through hindcasting

This study attempts to characterize the uncertainties in production forecasting for unconventional gas wells through hindcasting. The analysis focuses on how results from decline analyses change as the well population ages. The study is based on publicly available and subscription-based production data on 34,000 shale gas wells in the Marcellus, Fayetteville, Haynesville and Barnett plays. A hindcasting analysis was performed on wells, where production has been forecast using a physics-based decline curve analysis. This allows the accuracy of decline methods to be tested and the nature of errors to be assessed. Based on this analysis, the study identified systematic and random errors that impact estimates of ultimate recovery. Fields where few wells have entered boundary-dominated flow show higher uncertainty for field-wide production forecasts. Uncertainty decreases as more production history is accumulated. The physics-based approach for decline curve analysis is shown to be robust through hindcast analysis. The uncertainty in per-well recoveries for the fields studied are in the range 4–8%. The uncertainty in field-wide average ultimate recovery is less than 4% for three of the fields and 5.6% for the Marcellus. Understanding the sources and magnitudes of errors and uncertainties in estimated ultimate recovery values for unconventional gas wells allows operators to account for these in determining economic outcomes and performing financial planning of wells.

Resolvent analysis for jet noise source identification

We use resolvent analysis and spectral proper orthogonal decomposition (SPOD) to deduce the acoustic sources for an isothermal Mach 1.5 round jet. Both physics-based resolvent analysis and data-driven SPOD (using a high-fidelity, experimentally-verified, large-eddy simulation (LES) database) provide a basis for predicting the perturbation field. Singular value decomposition of the resolvent operator based upon the LES baseflow provides optimal volumetric forcing modes, or sources, and their associated linear responses. To identify physically relevant resolvent modes, comparisons are made between the highest gain responses and the highest energy SPOD modes computed directly from LES realizations. The prevalence of the associated resolvent forcing modes in the data are then assessed by projecting them onto the full LES nonlinear terms. The resulting distributions are presented and a jet noise model leveraging these forcing statistics is discussed. [This research was supported by a grant from the Office of Naval Research (Grant No. N00014- 16-1-2445). Ethan Pickering was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.]

Frequency domain scanning acoustic microscopy for power electronics: Physics-based feature identification and selectivity

In the evaluation of power electronic components non-destructive test methods (NDT) such as scanning acoustic microscopy (SAM) are valuable tools in packaging and failure analysis. As power modules become more compact and power devices thinner, echo overlap and interference can hamper the imaging capability and analysis of the conventional SAM time domain-based imaging techniques. Frequency domain analysis offers increased resolution and contrast but the interpretation and feature identification of waveforms is less obvious and interpretation guidelines have received little attention. In this paper a physics-based analysis of the frequency domain response is presented in a power module case study. The analysis is used to demonstrate physics-based feature selective contrast in such systems and offers guidelines for feature prediction. The approach is verified on full scan datasets from acoustic scans of a hybrid multilayer stack. Distinct features in the echo frequency domain are identified as resonances associated with multiple internal reflections in the layer structure. Where such features may hamper analysis in the conventional approach these can, if properly assigned, be exploited to yield selective and improved contrasts and allow accurate structural and material analysis.

Friction of sea ice.

Static and kinetic friction play a fundamental role in sea-ice mechanics. The coefficient of static friction increases with hold time under normal load and is modelled in terms of creep and fracture of asperities in contact. The coefficient of kinetic friction exhibits velocity strengthening at lower speeds and velocity weakening at intermediate speeds. Strengthening is modelled in terms of asperity creep and hardness; weakening is modelled in terms of a progressive increase in the true area of contact wetted by meltwater produced through frictional heating. The concept is introduced of contact size distribution in which the smallest contacts melt first, leading to the onset of weakening; the largest melt last, leading to a third regime of kinetic friction and again to strengthening where hydrodynamics governs. Neither the static nor the kinetic coefficient is significantly affected by the presence of sea water. The paper closes with a few implications for sea-ice mechanics. The paper is based largely upon a critical review of the literature, but includes a more quantitative, physics-based analysis of velocity strengthening and a new analysis of velocity weakening that incorporates parameters that describe the (proposed) fractal character of the sliding interface.This article is part of the theme issue ‘Modelling of sea-ice phenomena’.

Hybrid Sensor Network-Based Indoor Surveillance System for Intrusion Detection

This paper presents a novel hybrid sensor-based intrusion detection system for low-power surveillance in an empty, sealed indoor space with or without illumination. The proposed system includes three functional steps: (i) initial detection of an intrusion event using a sound field sensor; (ii) automatic lighting control based on the detected event, and (iii) detection and tracking the intruder using an image sensor. The proposed hybrid sensor-based surveillance system uses a sound field sensor to detect an abnormal event in a very low-light or completely dark environment for 24 h a day to reduce the power consumption. After detecting the intrusion by the sound sensor, a collaborative image sensor takes over an accurate detection and tracking tasks. The proposed hybrid system can be applied to various surveillance environments such as an office room after work, empty automobile, safety room in a bank, and armory room. This paper deals with fusion of computer-aided pattern recognition and physics-based sound field analysis that reflects the symmetric aspect of computer vision and physical analysis

Physics-based analysis and simulation model of electromagnetic interference induced soft logic upset in CMOS inverter**Project supported by the National Natural Science Foundation of China (Grant No. 60776034) and the Open Fund of Key Laboratory of Complex Electromagnetic Environment Science and Technology, China Academy of Engineering Physics (Grant No. 2015-0214.XY.K).

The instantaneous reversible soft logic upset induced by the electromagnetic interference (EMI) severely affects the performances and reliabilities of complementary metal–oxide–semiconductor (CMOS) inverters. This kind of soft logic upset is investigated in theory and simulation. Physics-based analysis is performed, and the result shows that the upset is caused by the non-equilibrium carrier accumulation in channels, which can ultimately lead to an abnormal turn-on of specific metal–oxide–semiconductor field-effect transistor (MOSFET) in CMOS inverter. Then a soft logic upset simulation model is introduced. Using this model, analysis of upset characteristic reveals an increasing susceptibility under higher injection powers, which accords well with experimental results, and the influences of EMI frequency and device size are studied respectively using the same model. The research indicates that in a range from L waveband to C waveband, lower interference frequency and smaller device size are more likely to be affected by the soft logic upset.

Graphene Heat Spreaders for Thermal Management of InGaP/GaAs Collector-Up HBTs

We present a novel thermal management design for InGaP/GaAs power amplifiers (PAs) by placing the graphene heat spreader (GHS) at the backside of GaAs/InGaAs/InGaP collector-up (C-up) heterojunction bipolar transistors (HBTs), including n-p-n and p-n-p types. The GHS was used to create extra escape channel for thermal spread, and a physics-based analysis was performed to justify heat-dissipation improvements. Temperature distribution in the GHS and the application of these spreaders to ameliorate thermal coupling effects on multifinger transistors were discussed. Compared to the n-p-n device, the p-n-p device exhibits greater thermal stability enhancement results, which are extraordinary and reproducible. Both numerical simulation and experimental measurement were achieved to scrutinize thermal performance of the GHS. This brief demonstrates the potential of the suggested structure in replacing the conventional thermal-removal configuration of GaAs-based HBTs used in high-efficiency cellular handset PAs.

Analysis of Li-Ion Battery Electrochemical Impedance Spectroscopy Data: An Easy-to-Implement Approach for Physics-Based Parameter Estimation Using an Open-Source Tool

The quantitative analysis of electrochemical impedance spectroscopy (EIS) data is important for both characterization and prognostic applications in many electrochemical systems. Here we describe an open-source platform, the ImpedanceAnalyzer, for easy-to-use physics-based analysis of experimental EIS spectra. To demonstrate the use of the platform, we explore the basic capabilities of the pseudo two-dimensional (P2D) battery model to predict publicly available experimental EIS data from a 1500 mAh commercial lithium-ion (LiCoO2/graphite) cell. An a priori computed dataset of 38,800 P2D-based impedance spectra simulations, covering a wide range of frequencies (1 mHz to 100 kHz) and model parameters, enables a straightforward least squares matching approach for analyzing experimental spectra. We find an average error of 1.73% between the best-matching computed spectrum from the 38,800 member library and the experimental spectrum being analyzed. Our analysis shows there is significant opportunity to improve the fit between experimental data and physics-based impedance simulations by a combination of a larger computed dataset, local optimization, and further additions to the model physics. The approach and open source tools developed here can be easily extended to other electrochemical systems.

Physics-based data analysis for wind turbine condition monitoring

Abstract This article presents methodologies for improving wind turbine condition monitoring using physics-based data analysis techniques. The unique operating conditions of the wind turbine drivetrain are described, and the complex kinematics of the gearbox is analyzed in detail. The pros and cons of the current wind turbine condition monitoring system (CMS) are evaluated. To improve the wind turbine CMS capability, it is suggested to use linear models with unsteady excitations, instead of using nonlinear and nonstationary process models, when dealing the wind turbine dynamics response model. An analysis is undertaken of the damage excitation mechanisms cause for various components in a gearbox, especially for those associated with lower-speed shafts. Physics (mechanics)-based data analysis methods are presented for different component damage excitation mechanisms. Validation results, using the wind farm and manufacturing floor data, are reported.

Multi-Gate FinFET Mixer Variability Assessment Through Physics-Based Simulation

In this letter, we show that innovative physics-based simulations can be used for a comprehensive analysis of RF stages subject to random variations of technological parameters, including the computation of the average (deterministic) RF performance along with their statistical deviation. The variability analysis is addressed by means of the recently developed physics-based sensitivity analysis of AC parameters through Green’s functions. To demonstrate the technique, we address the analysis of a FinFET mixer exploiting an innovative independent gates topology, showing that a careful design allows to maximize the mixer conversion gain, while minimizing its variability versus several physical parameters, such as the gate length, oxide thickness, and fin width.

Efficient Wireless Power Charging of Electric Vehicle by Modifying the Magnetic Characteristics of the Transmitting Medium

There is a developing enthusiasm for electric vehicle (EV) innovations because of their lower fuel utilization and greenhouse emission output. Integrating EVs with highway wireless power transfer (WPT) technology can appropriately reduce charging time and possibly expand their travel distance. There are several issues with the current WPT technology for EVs: 1) low efficiency due to large coil-coil distance and 2) slow charging time. Two ideas are proposed in this paper to increase system efficiency: 1) using a modified cement for covering the transmitting antenna area and 2) using high frequency wide bandgap switches, which can transfer a high amount of power in a short time. The optimization study of the receiving and transmitting coils is implemented with and without a core through 3-D finite-element analysis. The physics-based analysis is coupled with circuit-based analysis for utilizing high frequencies wide bandgap switch (SiC MOSFET). On the material side, the electromagnetic and mechanical properties of the modified cementitious composite are characterized and the results show significant improvement in the system efficiency.

Using Online Interactive Physics-based Video Analysis Exercises to Enhance Learning

As part of our new digital video age, physics students throughout the world can use smart phones, video cameras, computers and tablets to produce and analyze videos of physical phenomena using analysis software such as Logger Pro, Tracker or Coach. For several years, LivePhoto Physics Group members have created short videos of physical phenomena. They have also developed curricular materials that enable students to make predictions and use video analysis software to verify them. In this paper a new LivePhoto Physics project that involves the creation and testing of a series of Interactive Video Vignettes (IVVs) will be described. IVVs are short webbased assignments that take less than ten minutes to complete. Each vignette is designed to present a video of a phenomenon, ask for a student’s prediction about it, and then conduct on-line video observations or analyses that allow the user to compare findings with his or her initial prediction. The Vignettes are designed for web delivery as ungraded exercises to supplement textbook reading, or to serve as pre-lecture or pre-laboratory activities that span a number of topics normally introduced in introductory physics courses. A sample Vignette on the topic of Newton’s Third Law will be described, and the outcomes of preliminary research on the impact of Vignettes on student motivation, learning and attitudes will be summarized.

Fragment Acceleration Modeling for Pressurized Tank Burst

As part of comprehensive efforts to develop physics-based risk assessment techniques for space systems at NASA, coupled computational fluid and rigid-body dynamic simulations are carried out to investigate the flow mechanisms that accelerate tank fragments in bursting pressurized vessels. Simulations of several configurations are compared to analyses based on the industry-standard Baker-type explosion model, and they are used to formulate an improved version of the model. A validation against the experiment is carried out for one configuration. The standard model, which neglects an external fluid, is found to agree best with simulation results only in configurations where the internal-to-external pressure ratio is very high. An improved model introduces terms that accommodate an external fluid and better account for the pressure at the fragment wall. A physics-based analysis is critical in increasing the model’s range of applicability. The improved tank burst model can be used to produce more accurate risk assessments of space vehicle failure modes that involve high-speed debris, such as exploding propellant tanks and bursting rocket engines.