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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Sloshing of Cryogenic Helium Driven by Lateral Impulse/Gravity Gradient-Dominated/or g-Jitter-Dominated Accelerations and Orbital Dynamics

The coupling of slosh dynamics within a partially filled rotating dewar of superfluid helium 11 with spacecraft orbital dynamics is investigated in response to the environmental disturbances of (a) lateral impulses, (b) gravity gradients and (c) g-jitter forces. The purpose of this study is to investigate how the coupling of helium 11 fluid slosh dynamics driven by three cases of environmental force with spacecraft dynamics can affect the bubble deformations and their associated fluid and spacecraft mass centre fluctuations. The numerical computation of slosh dynamics is based on a rotational frame, while the spacecraft dynamics is associated with a non-rotational frame. Results show that the major contribution of orbital dynamics is driven by coupling with slosh dynamics. Neglecting the effect of slosh dynamics acting on the spacecraft may lead to the wrong results for the development of orbital and attitude control techniques.

Hung, R. J.↗
NASA NTRS1996

Development of High Speed Imaging and Analysis Techniques Compressible Dynamics Stall

Dynamic stall has limited the flight envelope of helicopters for many years. The problem has been studied in the laboratory as well as in flight, but most research, even in the laboratory, has been restricted to surface measurement techniques such as pressure transducers or skin friction gauges, except at low speed. From this research, it became apparent that flow visualization tests performed at Mach numbers representing actual flight conditions were needed if the complex physics associated with dynamic stall was to be properly understood. However, visualization of the flow field during compressible conditions required carefully aligned and meticulously reconstructed holographic interferometry. As part of a long-range effort focused on exposing of the physics of compressible dynamic stall, a research wind tunnel was developed at NASA Ames Research Center which permits visual access to the full flow field surrounding an oscillating airfoil during compressible dynamic stall. Initially, a stroboscopic schlieren technique was used for visualization of the stall process, but the primary research tool has been point diffraction interferometry(PDI), a technique carefully optimized for use in th is project. A review of the process of development of PDI will be presented in the full paper. One of the most valuable aspects of PDI is the fact that interferograms are produced in real time on a continuous basis. The use of a rapidly-pulsed laser makes this practical; a discussion of this approach will be presented in the full paper. This rapid pulsing(up to 40,000 pulses/sec) produces interferograms of the rapidly developing dynamic stall field in sufficient resolution(both in space and time) that the fluid physics of the compressible dynamic stall flowfield can be quantitatively determined, including the gradients of pressure in space and time. This permits analysis of the influence of the effect of pitch rate, Mach number, Reynolds number, amplitude of oscillation, and other parameters on the dynamic stall process. When interferograms can be captured in real time, the potential for real-time mapping of a developing unsteady flow such as dynamic stall becomes a possibility. This has been achieved in the present case through the use of a high-speed drum camera combined with electronic circuitry which has resulted in a series of interferograms obtained during a single cycle of dynamic stall; images obtained at the rate of 20 KHz will be presented as a part of the formal presentation. Interferometry has been available for a long time; however, most of its use has been limited to visualization. The present research has focused on use of interferograms for quantitative mapping of the flow over oscillating airfoils. Instantaneous pressure distributions can now be obtained semi-automatically, making practical the analysis of the thousands of interferograms that are produced in this research. A review of the techniques that have been developed as part of this research effort will be presented in the final paper.

Chandrasekhara, M. S.↗
NASA NTRS2010

Verification Challenges of Dynamic Testing of Space Flight Hardware

The Six Degree-of-Freedom Dynamic Test System (SDTS) is a test facility at the National Aeronautics and Space Administration (NASA) Johnson Space Center in Houston, Texas for performing dynamic verification of space structures and hardware. Some examples of past and current tests include the verification of on-orbit robotic inspection systems, space vehicle assembly procedures and docking/berthing systems. The facility is able to integrate a dynamic simulation of on-orbit spacecraft mating or demating using flight-like mechanical interface hardware. A force moment sensor is utilized for input to the simulation during the contact phase, thus simulating the contact dynamics. While the verification of flight hardware presents many unique challenges, one particular area of interest is with respect to the use of external measurement systems to ensure accurate feedback of dynamic contact. There are many commercial off-the-shelf (COTS) measurement systems available on the market, and the test facility measurement systems have evolved over time to include two separate COTS systems. The first system incorporates infra-red sensing cameras, while the second system employs a laser interferometer to determine position and orientation data. The specific technical challenges with the measurement systems in a large dynamic environment include changing thermal and humidity levels, operational area and measurement volume, dynamic tracking, and data synchronization. The facility is located in an expansive high-bay area that is occasionally exposed to outside temperature when large retractable doors at each end of the building are opened. The laser interferometer system, in particular, is vulnerable to the environmental changes in the building. The operational area of the test facility itself is sizeable, ranging from seven meters wide and five meters deep to as much as seven meters high. Both facility measurement systems have desirable measurement volumes and the accuracies vary within the respective volumes. In addition, because this is a dynamic facility with a moving test bed, direct line-of-sight may not be available at all times between the measurement sensors and the tracking targets. Finally, the feedback data from the active test bed along with the two external measurement systems must be synchronized to allow for data correlation. To ensure the desired accuracy and resolution of these systems, calibration of the systems must be performed regularly. New innovations in sensor technology itself are periodically incorporated into the facility s overall measurement scheme. In addressing the challenges of the measurement systems, the facility is able to provide essential position and orientation data to verify the dynamic performance of space flight hardware.

Winnitoy, Susan↗
NASA NTRS2010

Operational Dynamic Configuration Analysis

Sectors may combine or split within areas of specialization in response to changing traffic patterns. This method of managing capacity and controller workload could be made more flexible by dynamically modifying sector boundaries. Much work has been done on methods for dynamically creating new sector boundaries [1-5]. Many assessments of dynamic configuration methods assume the current day baseline configuration remains fixed [6-7]. A challenging question is how to select a dynamic configuration baseline to assess potential benefits of proposed dynamic configuration concepts. Bloem used operational sector reconfigurations as a baseline [8]. The main difficulty is that operational reconfiguration data is noisy. Reconfigurations often occur frequently to accommodate staff training or breaks, or to complete a more complicated reconfiguration through a rapid sequence of simpler reconfigurations. Gupta quantified a few aspects of airspace boundary changes from this data [9]. Most of these metrics are unique to sector combining operations and not applicable to more flexible dynamic configuration concepts. To better understand what sort of reconfigurations are acceptable or beneficial, more configuration change metrics should be developed and their distribution in current practice should be computed. This paper proposes a method to select a simple sequence of configurations among operational configurations to serve as a dynamic configuration baseline for future dynamic configuration concept assessments. New configuration change metrics are applied to the operational data to establish current day thresholds for these metrics. These thresholds are then corroborated, refined, or dismissed based on airspace practitioner feedback. The dynamic configuration baseline selection method uses a k-means clustering algorithm to select the sequence of configurations and trigger times from a given day of operational sector combination data. The clustering algorithm selects a simplified schedule containing k configurations based on stability score of the sector combinations among the raw operational configurations. In addition, the number of the selected configurations is determined based on balance between accuracy and assessment complexity.

Lai, Chok Fung↗
NASA NTRS2011

Extensions to the Dynamic Aerospace Vehicle Exchange Markup Language

The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) is a syntactical language for exchanging flight vehicle dynamic model data. It provides a framework for encoding entire flight vehicle dynamic model data packages for exchange and/or long-term archiving. Version 2.0.1 of DAVE-ML provides much of the functionality envisioned for exchanging aerospace vehicle data; however, it is limited in only supporting scalar time-independent data. Additional functionality is required to support vector and matrix data, abstracting sub-system models, detailing dynamics system models (both discrete and continuous), and defining a dynamic data format (such as time sequenced data) for validation of dynamics system models and vehicle simulation packages. Extensions to DAVE-ML have been proposed to manage data as vectors and n-dimensional matrices, and record dynamic data in a compatible form. These capabilities will improve the clarity of data being exchanged, simplify the naming of parameters, and permit static and dynamic data to be stored using a common syntax within a single file; thereby enhancing the framework provided by DAVE-ML for exchanging entire flight vehicle dynamic simulation models.

Brian, Geoffrey J.↗
NASA NTRS2020

Generation and Calibration of Linear Models of Aircraft with Highly Coupled Aeroelastic and Flight Dynamics

The lightweight structures and unconventional configurations being considered for the next generation of aircraft mean that any effort to predict or control the flight dynamics is impacted by the structural dynamics. One of the most severe forms of coupling between aeroelasticity and flight dynamics is an instability called body freedom flutter. The existing tools often assume a relatively weak effect of structural dynamics on the flight dynamics, and are therefore incapable of modeling strong interactions like body freedom flutter. A method of combining different sources of data traditionally used for aeroelasticity and flight dynamics is described by reconciling many of the differences between these models. By building upon past modeling efforts, a level of familiarity in the approach is achieved. Generally the differences from the traditional approaches are subtle but significant. The traditional frequency domain flutter model in a modal coordinate system is converted to a form consistent with a time domain flight dynamics model. The time domain rational function approximation about a non-inertial coordinate system and the unique constraints for the conversion between the inertial and non-inertial coordinate systems are discussed. A consistent transformation of the states of aeroelastic models to flight dynamics models is derived, which enables the integration of data from higher fidelity computational fluid dynamics models or wind-tunnel testing. The present method of integrating multidisciplinary data was used to create models that compare well with X-56A flight-test data, including conditions past the flutter speed.

Ouellette, Jeffrey↗
NASA NTRS2018

Flux-Pinned Dynamics Model Parameterization and Sensitivity Study

Flux-pinned interfaces for spacecraft are an action-at-a-distance technology that can maintain a passively stable equilibrium between two spacecraft in close-proximity using the physics of magnetic flux pinning. Although flux pinning dynamics have been studied from a material-science perspective and at an interface level, there is a need to better understand the sensitivities and implications of system-level designs on the flux-pinned interface dynamics, especially in designs with multiple magnets and superconductors. These interfaces have highly nonlinear, coupled dynamics that are influenced by physical parameters including but not limited to strength of magnetic field sources, field-cooled position, and superconductor geometry. This paper addresses that gap by codifying parametric terms into an improved dynamics model, which can then be used to simulate the interaction of a multiple-superconductor-multiple-magnet interface. A standard starting point for modeling flux pinning dynamics is Kordyuk’s frozen image model, which defines a geometric mapping between magnetic field sources and their corresponding magnetic point source “images inside the volume of the superconductor.” The frozen image model successfully approximates the characteristics of flux pinning dynamics, but could provide more precise position and orientation predictions with the addition of various physical parameter refinements. The sensitivity of the general flux-pinned dynamics model is studied by varying the physical parameters and simulating the systems level dynamics. A predictive dynamics model is crucial to the maturation of this technology so it can be utilized in spacecraft systems, and this work represents a critical step in the development of that model.

Peck, Mason↗
DOE OSTI2020

Inertial dynamics of an interface with interfacial mass flux: Stability and flow fields’ structure, inertial stabilization mechanism, degeneracy of Landau’s solution, effect of energy fluctuations, and chemistry-induced instabilities

This work focuses on the long-standing problem of inertial dynamics of an interface with interfacial mass flux and reports new mechanisms for the interface stabilization and destabilization. The interface is a phase boundary separating fluids of different densities and having interfacial mass flux. To analyze the interface dynamics from a far field, we develop and apply the general matrix method to rigorously solve the boundary value problem involving the governing equations in the fluid bulk and the boundary conditions at the interface and at the outside boundaries of the domain. We find the fundamental solutions for the linearized system of equations and analyze the interplay of interface stability with flow fields’ structure by directly linking rigorous mathematical attributes to physical observables. We find that the interface is stable when the dynamics conserves the fluxes of mass, momentum, and energy; the stabilization is due to an inertial mechanism causing small oscillations of the interface velocity. In the classic Landau’s dynamics, the postulate of perfect constancy of the interface velocity leads to the development of Landau–Darrieus instability. This destabilization is also linked to the imbalance of the perturbed energy at the interface. The classic Landau’s solution is found to have degeneracy; lifting of the degeneracy may lead to singularity and self-similar dynamics. Our results compare well with traditional theories of combustion and propose new experiments to study the dynamics of the interface and the flow fields in combustible systems. We further conduct reactive molecular dynamics simulations to elucidate the complexity of chemical processes, to study the destabilizing effect of energy fluctuations on the interface stability, and to illustrate the chemistry-induced instabilities. In summary, we identify the extreme sensitivity of the interface dynamics to the interfacial boundary conditions, including the formal properties of fundamental solutions and the qualitative and quantitative properties of the flow fields. This provides new opportunities for studies, diagnostics, and control of multiphase flows in a broad range of processes in nature and technology.

42 ENGINEERING↗
DOE OSTI2021

Operator learning for predicting multiscale bubble growth dynamics

We report simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investigated systematically by deep neural networks (DNNs). Herein, we develop a framework based on operator regression, the so-called deep operator network (DeepONet), with the long-term objective to simplify multiscale modeling by avoiding the fragile and time-consuming “hand-shaking” interface algorithms for stitching together heterogeneous descriptions of multiscale phenomena. To this end, as a first step, we investigate if a DeepONet can learn the dynamics of different scale regimes, one at the deterministic macroscale and the other at the stochastic microscale regime with inherent thermal fluctuations. Specifically, we test the effectiveness and accuracy of the DeepONet in predicting multirate bubble growth dynamics, which is described by a Rayleigh–Plesset (R–P) equation at the macroscale and modeled as a stochastic nucleation and cavitation process at the microscale by dissipative particle dynamics (DPD). First, we generate data using the R–P equation for multirate bubble growth dynamics caused by randomly time-varying liquid pressures drawn from Gaussian random fields (GRFs). Our results show that properly trained DeepONets can accurately predict the macroscale bubble growth dynamics and can outperform long short-term memory networks. We also demonstrate that the DeepONet can extrapolate accurately outside the input distribution using only very few new measurements. Subsequently, we train the DeepONet with DPD data corresponding to stochastic bubble growth dynamics. Although the DPD data are noisy and we only collect sparse data points on the trajectories, the trained DeepONet model is able to predict accurately the mean bubble dynamics for time-varying GRF pressures. Taken together, our findings demonstrate that DeepONets can be employed to unify the macroscale and microscale models of the multirate bubble growth problem, hence providing new insight into the role of operator regression via DNNs in tackling realistic multiscale problems and in simplifying modeling with heterogeneous descriptions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Emergent facilitation and glassy dynamics in supercooled liquids

In supercooled liquids, dynamical facilitation refers to a phenomenon where microscopic motion begets further motion nearby, resulting in spatially heterogeneous dynamics. This is central to the glassy relaxation dynamics of such liquids, which show super-Arrhenius growth of relaxation timescales with decreasing temperature. Despite the importance of dynamical facilitation, there is no theoretical understanding of how facilitation emerges and impacts relaxation dynamics. Here, we present a theory that explains the microscopic origins of dynamical facilitation. We show that dynamics proceeds by localized bond-exchange events, also known as excitations, resulting in the accumulation of elastic stresses with which new excitations can interact. At low temperatures, these elastic interactions dominate and facilitate the creation of new excitations near prior excitations. Using the theory of linear elasticity and Markov processes, we simulate a model, which reproduces multiple aspects of glassy dynamics observed in experiments and molecular simulations, including the stretched exponential decay of relaxation functions, the super-Arrhenius behavior of relaxation timescales as well as their two-dimensional finite-size effects. The model also predicts the subdiffusive behavior of the mean squared displacement (MSD) on short, intermediate timescales. Furthermore, we derive the phonon contributions to diffusion and relaxation, which when combined with the excitation contributions produce the two-step relaxation processes, and the ballistic–subdiffusive–diffusive crossover MSD behaviors commonly found in supercooled liquids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Transonic Correction Method for Flight Dynamic Stability Analysis of Mach 0.745 Transonic Truss-Braced Wing

This paper presents a transonic correction method for obtaining dynamic stability derivatives for flight dynamic stability analysis. The method provides a transonic correction to the Theodorsen's theory of unsteady aerodynamics using FUN3D CFD solver of unsteady Reynolds-averaged Navier-Stokes equations (RANS) for a series of wing sections of the Mach 0.745 Transonic Truss-Braced Wing in pitch and plunge oscillations. Unsteady lift and pitching moment coefficients are obtained and used to develop the correction terms in the Theodorsen's theory to account for transonic aerodynamics. The unsteady lift and pitching moment derivatives with respect to the unsteady angle of attack are obtained as frequency response functions of the reduced frequency. These frequency response functions are used to compute the dynamic stability derivatives of lift and pitching moment due to the angle of attack and pitch rate and the dynamic stability derivatives for the rolling moment and yawing moment with respect to the roll rate and yaw rate. A transonic correction is applied to steady-state stability derivatives computed by VSPAERO solver using transonic small disturbance code TSFOIL coupled to an integral boundary method. A dynamic stability analysis is conducted for longitudinal and lateral-directional motions. Without transonic corrections and dynamic stability derivatives, the analysis indicates an unstable phugoid mode. The transonic correction applied to the steady-state stability derivatives computed by VSPAERO shows a stable phugoid mode. This is due to the increase of the drag stability derivatives as a result of the additional wave drag contribution in transonic flow. The effect of the transonic dynamic stability derivatives is observed to be a significant contributor to the increase in the damping values of all the flight dynamic modes of the Mach 0.745 Transonic-Truss Braced Wing.

Transonic↗
DOE OSTI2020

On the advantages of exploiting memory in Markov state models for biomolecular dynamics

Biomolecular dynamics play an important role in numerous biological processes. Markov State Models (MSMs) provide a powerful approach to study these dynamic processes by predicting long time scale dynamics based on many short molecular dynamics (MD) simulations. In an MSM, protein dynamics are modeled as a kinetic process consisting of a series of Markovian transitions between different conformational states at discrete time intervals (called “lag time”). To achieve this, a master equation must be constructed with a sufficiently long lag time to allow interstate transitions to become truly Markovian. This imposes a major challenge for MSM studies of proteins since the lag time is bound by the length of relatively short MD simulations available to estimate the frequency of transitions. Here, we show how one can employ the generalized master equation formalism to obtain an exact description of protein conformational dynamics both at short and long time scales without the time resolution restrictions imposed by the MSM lag time. Using a simple kinetic model, alanine dipeptide, and WW domain, we demonstrate that it is possible to construct these quasi-Markov State Models (qMSMs) using MD simulations that are 5–10 times shorter than those required by MSMs. These qMSMs only contain a handful of metastable states and, thus, can greatly facilitate the interpretation of mechanisms associated with protein dynamics. A qMSM opens the door to the study of conformational changes of complex biomolecules where a Markovian model with a few states is often difficult to construct due to the limited length of available MD simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Dynamic Tensile Experimental Techniques for Geomaterials: A Comprehensive Review

Here, this review article is dedicated to the Dynamic Behavior of Materials Technical Division for celebrating the 75th anniversary of the Society for Experimental Mechanics (SEM). Understanding dynamic behavior of geomaterials is critical for analyzing and solving engineering problems of various applications related to underground explosions, seismic, airblast, and penetration events. Determining the dynamic tensile response of geomaterials has been a great challenge in experiments due to the nature of relatively low tensile strength and high brittleness. Various experimental approaches have been made in the past century, especially in the most recent half century, to understand the dynamic behavior of geomaterials in tension. In this review paper, we summarized the dynamic tensile experimental techniques for geomaterials that have been developed. The major dynamic tensile experimental techniques include dynamic direct tension, dynamic split tension, and spall tension. All three of the experimental techniques are based on Hopkinson or split Hopkinson (also known as Kolsky) bar techniques and principles. Finally, uniqueness and limitations for each experimental technique are also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Review of rotating wing dynamic stall: Experiments and flow control

Dynamic stall has been a technical challenge and a fluid dynamical subject of interest for more than fifty years; but in the last decade significant advances have been made in the understanding, prediction, modeling, and control of dynamic stall on rotors. This paper provides a summary of the state of the art of dynamic stall experiments and future directions in the understanding of dynamic stall on rotors. Experimental data sets are discussed, as well the direction of future research for control of dynamic stall. Coordinated testing between airfoils and rotating blades, as well as close integration between computational and experimental studies were found to be productive approaches. Advanced analysis methods, including statistical methods, modal representations, and artificial intelligence methods have led to significant advances in the understanding of dynamic stall. Investigations of dynamic stall control devices have allowed many useful targeted investigations of the transition to separated flow, but have not yet resulted in a commercially implemented device.

42 ENGINEERING↗
DOE OSTI2020

Structural Dynamics in UV Curable Resins Resolved by In Situ 3D Printing X-ray Photon Correlation Spectroscopy

Additive manufacturing (AM) is a promising technique to rapidly produce polymeric materials into complex 3-dimensional (3D) geometries. While AM is widespread and relevant for a range of applications, implementation in industry has outpaced our fundamental understanding of polymer dynamics and structure development during the printing process. Characterization and quantification of such dynamics is necessary to optimize final material properties and design future materials and processes for 3D printing. Here, we utilize X-ray photon correlation spectroscopy (XPCS) to measure spatial and time-resolved, out-of-equilibrium dynamics during direct ink write (DIW) 3D printing. Specifically, we investigate the progression of structural dynamics in a dual cure (UV/thermal) nanocomposite during and directly after printing. As the filament is printed and cured in situ, the relaxation processes of the cross-linking network are measured through the dynamics of inorganic filler particles. The characteristic relaxation time of the dynamics is calculated through the intensity–intensity autocorrelation function g 2 and directly correlated to the printing process parameters, such as printhead velocity and UV light intensity. The time-resolved evolution of nanoscale dynamics follows a power-law dependence as the filament is cured. Additionally, bulk rheological characterizations reveal the macroscopic solidification of the resin, providing correlation of material properties across a wide range of length and time scales. Overall, the measurement of multiscale, out-of-equilibrium dynamics provides insight into the development of structure in polymer nanocomposite filaments during 3D printing and is used to further understand the influence of such parameters on the AM process.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Next generation extended Lagrangian first principles molecular dynamics

Extended Lagrangian Born-Oppenheimer molecular dynamics [Phys. Rev. Lett., 100, 123004 (2008)] is formulated for general Hohenberg-Kohn density functional theory and compared to the extended Lagrangian framework of rst principles molecular dynamics by Car and Parrinello [Phys. Rev. Lett. 55, 2471 (1985)]. It is shown how extended Lagrangian Born-Oppenheimer molecular dynamics overcomes several shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while improving or maintaining important features of Car-Parrinello simulations. The accuracy of the electronic degrees of freedom in extended Lagrangian Born-Oppenheimer molecular dynamics, with respect to the exact Born-Oppenheimer solution, is of second order in the size of the integration time step and of fourth order in the potential energy surface. Improved stability over recent formulations of extended Lagrangian Born-Oppenheimer molecular dynamics is achieved by generalizing the theory to finite temperature ensembles, using fractional occupation numbers in the calculation of the inner-product kernel of the extended harmonic oscillator that appears as a preconditioner in the electronic equations of motion. Materials systems that normally exhibit slow self-consistent field convergence can be simulated using integration time steps of the same order as in direct Born- Oppenheimer molecular dynamics, but without the requirement of an iterative, non-linear electronic ground state optimization prior to the force evaluations and without a systematic drift in the total energy. In combination with proposed low-rank and on-the- y updates of the kernel, this formulation provides an efficient and general framework for quantum based Born-Oppenheimer molecular dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Efficient Phasor-Based Dynamic Volt/VAr and Volt/Watt Analysis of Large Distribution Grid with High Penetration of Smart Inverters

As the penetration of power-electronics based smart inverters (SIs) is increasing in distribution grids, it adds computational challenges in solving dynamic models of large-scale distribution feeders. Voltage and reactive power (Volt/VAr), and voltage and active power (Volt/Watt) dynamics have been analyzed at slower time scales akin to the control of legacy grid devices. However, smart inverters, being power-electronics based devices, can provide dynamic active/reactive power support at a faster time scale, which necessitates Volt/VAr and Volt/Watt dynamics to be analyzed at a faster time scale. The existing dynamic models are overly detailed and computationally intractable for distribution feeders with a large number of inverters. In this context, this proposed work aims towards developing a computationally tractable, scalable, and accurate phasor-based model for dynamic Volt/VAr and Volt/Watt analyses of large distribution systems with high penetration of smart inverters. Case studies demonstrate that the proposed phasor-based model sufficiently captures the Volt/VAr and Volt/Watt dynamics, and is computationally faster by one order of magnitude compared to the average model and by two orders of magnitude compared to the detailed switching model. Case studies also demonstrate the efficacy and scalability of the proposed model in analyzing Volt/VAr and Volt/Watt dynamics of large-scale power networks with hundreds of SIs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Robust Large-Scale Dynamic Windows using Reversible Metal Electrodeposition

This project funded the study and development of dynamic windows based on reversible metal electrodeposition (RME). Dynamic windows allow user control over light and heat flow into and out of buildings, which offer both advantages in building aesthetics (with worker productivity improvement of 2%) and energy efficiency (up to 20% savings) compared to static controls such as low emissivity coatings and blinds/shades. Despite these advantages, dynamic windows, which traditionally rely on electrochromic metal oxides or conductive organic molecules for light modulation have failed to significantly impact the market due to issues related to cost, color, and optical dynamic range. Dynamic windows based on reversible metal electrodeposition (RME) are an exciting alternative approach and have the potential to overcome the issues associated with traditional technologies. A RME dynamic window is an electrochemical cell that modulates light using the reversible electrodeposition of metal on and off a transparent conducting oxide (TCO), which serves as the working electrode. The electrolyte has nearly colorless metal salts dissolved, and application of a cathodic potential on the TCO reduces the metal cations across the TCO surface to their metallic form, making a thin film that is efficient at blocking out light. A reverse in polarity oxidizes the metal, where it dissolves into solution, returning the window back to transparent. The counter electrode typically employed is a metal mesh, which is used to balance the electrochemical reactions happening on the TCO working electrode. These RME dynamic windows have the largest dynamic range (capable of reaching <<0.1% transmission) with color neutral tinting of any existing technology using solution processed techniques, which positions the technology as a promising candidate to penetrate the residential market. We have successfully scaled up the windows from 25 cm2 to 929 cm 2 , and we have demonstrated significant improvements to both the cycle life (10,000 cycles in a 3-electrode half-cell) and shelf life (>1 month) of our windows. We have published our work in high impact journals (6 published and 2 manuscripts in prep), filed 5 patents, and have incorporated TYNT Technologies to commercialize the technology.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗