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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Effect of Topology on Transient Dynamic and Shock Response of Polymeric Lattice Structures

Architected cellular materials, such as lattice structures, offer potential for tunable mechanical properties for dynamic applications of energy absorption and impact mitigation. In this work, the static and dynamic behavior of polymeric lattice structures was investigated through experiments on octet-truss, Kelvin, and cubic topologies with relative densities around 8%. Here, dynamic testing was conducted via direct impact experiments (25–70 m/s) with high-speed imaging coupled with digital image correlation and a polycarbonate Hopkinson pressure bar. Mechanical properties such as elastic wave speed, deformation modes, failure properties, particle velocities, and stress histories were extracted from experimental results. At low impact velocities, a transient dynamic response was observed which was composed of a compaction front initiating at the impact surface and additional deformation bands whose characteristics matched low strain-rate behavior. For higher impact velocities, shock analysis was carried out using compaction wave velocity and Eulerian Rankine–Hugoniot jump conditions with parameters determined from full-field measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Linking classical PRA models to a dynamic PRA

Here, this paper presents a series of methods designed to incorporate classical Probabilistic Risk Assessment (PRA) models such as Event Trees (ETs) and Fault Trees (FTs) into dynamic PRA. In contrast to classical PRA, dynamic PRA couples stochastic methods with system simulators to determine the risks associated with complex systems such as nuclear power plants. Compared with classical PRA methods, they can evaluate with higher resolution the safety impact of timing and sequencing of events on the progression of the accident. As part of a dynamic PRA analysis, it is not uncommon that parts of the system to be analyzed might not require a computationally expensive simulation model. These parts could be in fact modeled by employing classical PRA models (e.g., a FT). Here, we present a set of methods and tools that can be used to link the most common classical PRA models (ETs, FTs, reliability block diagrams and Markov models) to simulation codes such as RELAP5-3D: creating a “hybrid PRA.” In order to show the potential of such an hybrid PRA we employ this method to verify ET modeling assumptions (e.g., success criteria) using a large break loss of coolant accident initiating event as a test case. In this respect, we link a set of FTs from the original PRA to the RELAP5-3D code and perform a hybrid PRA. The FTs are employed to model the control logic of several safety systems and to propagate component failures throughout the system. Provided the generated dynamic PRA data, we show how conservative assumptions in the original PRA can be identified and how such original PRA can be modified by updating success criteria captured by the set of RELAP5-3D simulation runs.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Revealing meso-structure dynamics in additive manufacturing of energy storage via operando coherent X-ray scattering

3D printing is an emerging technology for the fabrication of energy storage devices, offering advantages over traditional manufacturing methods. However, optimization and design of such devices requires an understanding of the meso-structure formation during the 3D printing process. This study utilizes operando coherent X-ray scattering, X-ray Photon Correlation Spectroscopy (XPCS), to study the spatiotemporally-resolved far-from-equilibrium dynamics during direct ink writing 3D printing. Here, Lithium Titanate (LTO) based ink is prepared and rheologically tested for its shear-thinning properties. Two-time intensity-intensity functions are calculated to be used in subsequent quantitative analysis, which allows for an overall characterization of the dynamics, description of an initial fast decorrelation and identification of sudden rearrangements of subdomains of the sample. The results show the dynamics to be anisotropic, spatiotemporally heterogenous and marked by distinct rearrangement events, all of which impact the electrochemical performance of energy storage devices. The studied 3D printing ink is used to fabricate electrodes which are then electrochemically tested, showing good performance in cycling and retaining structural integrity. This work furthers the understanding of the far-from-equilibrium material dynamics during 3D printing, giving quantitative characterization of this process, and highlights aspects of structure formation relevant to the electrochemical performance of the resultant energy storage device.

36 MATERIALS SCIENCE↗
DOE OSTI2020

An error-in-constitutive equations strategy for topology optimization for frequency-domain dynamics

This paper presents a topology optimization formulation for frequency-domain dynamics to reduce solution dependence upon initial guess and considered loading conditions. Due to resonance phenomena in undamped steady-state dynamics, objectives measuring dynamic response possess many local minima that may represent poor solutions to a design problem, an issue exacerbated for design with respect to multiple frequencies. In this work, we propose an extension of the modified error-in-constitutive-equations (MECE) method, used previously in material identification inverse problems, as a new approach for frequency-domain dynamics topology optimization to mitigate these issues. The main idea of the proposed framework is to incorporate an additional penalty-like term in the objective function that measures the discrepancy in the constitutive relations between stresses and strains and between inertial forces and displacements. Then, the design problem is cast within a PDE-constrained optimization formulation in which we seek displacements, stresses, inertial forces, and a density-field solution that minimize our new objective subject to conservation of linear momentum plus some additional constraints. We show that this approach yields superior designs to conventional gradient-based optimization approaches that solely use a functional of displacements as the objective, while strictly enforcing the constitutive equations. The MECE strategy integrates into a density-based topology optimization scheme for void–solid or two-phase material structural design. We highlight the merits of our approach in a variety of scenarios for direct frequency response design, considering multiple frequency load cases and structural objectives.

42 ENGINEERING↗
DOE OSTI2022

Development of novel dynamic machine learning-based optimization of a coal-fired power plant

The increasing fraction of intermittent renewable energy in the electrical grid is resulting in coal-fired boilers now routinely ramp up and down. The current state-of-the-art operation for such boilers is to apply steady-state, neural network-based optimization to make control decisions in real-time, and this report demonstrates the feasibility of extending this to dynamic, neural network-based optimization using a long short-term memory neural network. A simplified numerical simulation of a t-fired coal boiler and supporting equipment is used to represent a real plant subjected to both steady-state, neural network-based optimization and dynamic, neural network-based optimization. Using the same intervals and a particle swarm optimization algorithm, the dynamic optimization outperforms the steady-state optimization and realizes up to 4.58% improvement in thermal efficiency. Dynamic optimization with a long short-term memory neural network is shown to both be feasible and beneficial for operation of a coal-fired boiler under changing load.

42 ENGINEERING↗
DOE OSTI2021

Evaluating dynamic thermal performance of building envelope components using small-scale calibrated hot box tests

The hot box test method has been applied to evaluate both the steady-state (U-value) and dynamic thermal properties of building envelopes. However, the high construction cost of full-scale hot box apparatus and the testing time required (usually several days) may prevent its wider adoption. To overcome the limitations of full-scale hot box tests, here we propose a novel method to evaluate the dynamic thermal performance of building envelope components using a small-scale calibrated hot box and scaled-down specimen. In this paper, the scaling relationships of thermal properties evaluated using a full-size specimen and a scaled-down specimen are established based on the Laplace transform of the heat transfer equations. In addition, dynamic thermal properties obtained from scaled-down experimental tests are compared to the values calculated by the EN ISO13768 (ISO) method. A small-scale hot box with a 355 mm × 355 mm metering area was constructed and calibrated to validate the correlations. Three scaled-down concrete sandwich wall panels were then tested and the scaling relationship was cross-validated using the experimental results, finite difference (FD) simulations, and the ISO method. The results indicate that the dynamic thermal properties obtained from a scaled-down hot box test can be correlated to its full-size counterpart when certain conditions are met. The scaled-down hot box test is demonstrated to be an effective yet economical alternative to a full-scale test with significantly reduced experimentation cost and turn-around time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Thermal and electric multidomain dynamic model for integration of power grid distribution with behind-the-meter devices

As renewable energy sources like solar and wind power become more integrated into the grid, coordinated control of behind-the-meter devices is crucial for enhancing grid flexibility and reliability and for meeting cost targets, with standardized models being developed to support this transition. The increasing flexibility and uncertainty of integrated renewable energy grids, along with interactions between various subsystems, make traditional steady-state modeling insufficient to capture transient and dynamic behaviors. Current models (e.g., composite load and battery equivalent models) focus on thermodynamic or electrical characteristics but overlook critical electromechanical interactions. This limits the ability to share performance information for grid services and hampers fast dynamic simulations. In addition, motor stalling is usually triggered by a fault event and attributed to the characteristics of the mechanical torque of the motor, resulting in absorption of a large amount of reactive power during the stalling period. Further, this significant withdrawal of reactive power will deteriorate the dynamic voltage stability of power grids and cause delayed voltage recovery. Therefore, an in-depth modeling of the thermodynamics or mechanical torque is essential to study the impacts of the realistic torque characteristics of those behind-the-meter devices on power system voltage stability. This study developed a dynamic multidomain model for building HVAC systems, such as air-source heat pumps, to simulate their thermal and electrical responses to grid transients. The model can accurately predict power metrics with a mean absolute percentage error of 10%, by validating against with power system computer-aided design performance data. Case studies demonstrate the model capability of capturing the transient response to sudden voltage changes, rapid load fluctuations, and system shutdowns respectively. During a sudden voltage drop (30% for 0.1s), a fully loaded heat pump’s motor speed dropped, continued declining, and shut down after 3.6s, with severe power oscillations and a torque spike. A partially loaded unit experienced temporary oscillations but stabilized. Under higher building loads, compressor speed increased from 64% to 100%, with power and torque rising before stabilizing. In safety-triggered shutdowns, power decreased after minor fluctuations, and torque briefly spiked before dropping to zero.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Certification and prediction of post-disturbance states in dynamic security assessment

Dynamic security assessment usually involves the simulation of system dynamics under large disturbances. The instant large disturbance occurs, the post-disturbance state of the system could deviate significantly from the pre-disturbance one. It is desirable and necessary to develop an efficient method to certify the existence of state and predict the approximate post-disturbance state because: (1) faster warning can be made in online assessment; and (2) the dynamic simulator can be given better initial values to calculate precise solutions, which prevents convergence failure brought on by poor initial values. We propose a novel approach for efficiently certifying and predicting the post-disturbance states in dynamic security assessment. Based on the fixed-point power flow mapping approach applied to salient pole generator models, the criterion for determining the existence and uniqueness of the post-disturbance solution is derived, and the bounds of post-disturbance solution can be rigorously characterized.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Sluggish atomic dynamics in a Y-Sc-Co-Al high entropy bulk metallic glass

We present how 20 at% Sc addition affects the atomic packing and dynamics in a Y-Co-Al metallic glass (MG) and find that it greatly suppresses the dynamics of Co atoms by reducing the atomic packing difference in their surroundings. The Co atoms tending to be mobile or static depend on their nearest neighbors, i.e., possessing more Y/Y+Sc atoms but fewer Co atoms or vice versa. The X-ray absorption fine structure results confirm that Sc addition mainly changes the local environment around Co atoms, forming more Co-Co and Co-Sc pairs but significantly fewer Co-Y pairs than in the ternary counterpart, which can seriously slow the atomic dynamics and stabilize the competing phases. Our findings shed new light on the understanding of strong glass forming ability of the Sc-added Y-based high entropy MG from its local structure and dynamics and will be helpful in developing new bulk MGs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Incorporating point defect generation due to jog formation into the vector density-based continuum dislocation dynamics approach

During plastic deformation of crystalline materials, point defects such as vacancies and interstitials are generated by jogs on moving dislocations. A detailed model for jog formation and transport during plastic deformation was developed within the vector density-based continuum dislocation dynamics framework. Here as a part of this model, point defect generation associated with jog transport was formulated in terms of the volume change due to the non-conservative motion of jogs. Balance equations for the vacancies and interstitials including their rate of generation due to jog transport were also formulated. A two-way coupling between point defects and dislocation dynamics was then completed by including the stress contributed by the eigen-strain of point defects. A jog drag stress was further introduced into the mobility law of dislocations to account for the energy dissipation during point defects generation. A number of test problems and a fully coupled simulation of dislocation dynamics and point defects generation and diffusion were performed. The results show that there is an asymmetry of vacancy and interstitial generation due to the different formation energies of the two types of defects. The results also show that a higher hardening rate and a higher dislocation density are obtained when the point defect generation mechanism is coupled to dislocation dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strongly nonlinear wave propagation in elasto-plastic metamaterials: Low-order dynamic modeling

Nonlinear elastic metamaterials are known to support a variety of dynamic phenomena that enhance our capacity to manipulate elastic waves. Since these properties stem from complex, subwavelength geometry, full-scale dynamic simulations are often prohibitively expensive at scales of interest. Prior studies have therefore utilized low-order effective medium models, such as discrete mass-spring lattices, to capture essential properties in the long-wavelength limit. While models of this type have been successfully implemented for a wide variety of nonlinear elastic systems, they have predominantly considered dynamics depending only on the instantaneous kinematics of the lattice, neglecting history-dependent effects, such as wear and plasticity. Here, to address this limitation, the present study develops a lattice-based modeling framework for nonlinear elastic metamaterials undergoing plastic deformation. Due to the history- and rate-dependent nature of plasticity, the framework generally yields a system of differential-algebraic equations whose computational cost is significantly greater than an elastic system of comparable size. We demonstrate the method using several models inspired by classical lattice dynamics and continuum plasticity theory and explore means to obtain empirical plasticity models for general geometries, thereby gaining insight into the influence of microstructural plasticity on effective material performance, which can be used to improve the design of nonlinear mechanical metamaterials.

Dynamic simulation↗
DOE OSTI2022

Dynamic machine learning-based optimization algorithm to improve boiler efficiency

With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. Further, the best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Influence of high-strain-rate compression and subsequent heat treatment on (TiNbZr) 89 (AlTa) 11 refractory high-entropy alloys: Dynamic-mechanical behavior and microstructural changes

This study explored the dynamic-mechanical behavior of a novel low-density (TiNbZr) 89 (AlTa) 11 refractory high-entropy alloy (RHEA) across strain rates ranging from 1.0×10 3 to 3.5×10 3 s –1 . A significant increase in the yield and ultimate compressive strengths with rising strain rates up to 3.0×10 3 s –1 was observed and attributed to enhanced dislocation activities and stress-induced microstructural transformations. The formation of the B2 phase and Zr 5 Al 3 precipitates was found to be crucial in bolstering the alloy strength at high strain rates. Beyond strain rates of 3.0×10 3 s –1 , a decrease in strength occurred due to thermal softening and strain localization. Microstructural analyses at 3.5×10 3 s –1 revealed grain refinement, the development of micro shear bands, and dislocation tangles, which were indicative of dynamic recrystallization. Besides, the findings also revealed that the post-dynamic compression heat treatment further enhanced the hardness and microstructural stability of the alloy. These results highlight the potential of the (TiNbZr) 89 (AlTa) 11 RHEA for applications requiring materials with high strength-to-weight ratios, particularly in dynamically loaded environments. It is expected that the results of this study will further advance our fundamental understanding of the behavior of RHEAs under extreme conditions, thereby opening new avenues for material innovation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamically preferred state with strong electronic fluctuations from electrochemical synthesis of sodium manganate

Electrochemical (de)intercalation is a delicate method to precisely control the alkaline ion composition in alkaline transition metal oxides. Because of complicated interactions, metal charge ordering patterns can form spontaneously at special fractional alkaline compositions and orderings. In this study, we show that this elegant electrochemical process can create dynamically preferred structures in an anharmonic energy landscape that conventional syntheses and computations can rarely visit. Specifically, electrochemically prepared Na 1/2 MnO 2 ordering exhibits abnormal structure distortions, charge orderings, and dynamical activities. Strong magnetic fluctuations and lattice dynamics are observed in an unusually wide temperature range in Na 1/2 MnO 2 , which distinguishes it from all other Na x MnO 2 at higher or lower Na compositions. The results emphasize the unique opportunity of using electrochemical processes to design and create novel quantum states with strongly coupled and mutually enhanced electronic and lattice fluctuations, likely through a special dynamic charge flux functional, as suggested by our computational investigations.

25 ENERGY STORAGE↗
DOE OSTI2026

The effect of hydroxyl spacing in diols on the solvation structure, dynamics, and transport properties of choline chloride-based deep eutectic solvents

Deep eutectic solvents (DESs) are a class of liquids that offer great potential in alleviating some of the challenges present in today's long-term energy storage methods because they have physical properties that are favorable for storable electrolyte solutions. In this work, a series of glycols (ethylene glycol, 1,3-propanediol, 1,4-butanediol, and 1,5-pentanediol) were studied as potential hydrogen bond donors (HBD) with a common choline chloride (ChCl) as the hydrogen bond acceptor (HBA). The solvation dynamics of the prepared systems were studied by measuring the solvent reorganization response using femtosecond transient absorption spectroscopy (fs-TA). Conductivity, viscosity, density, ET(30) polarity, and dynamics of the prepared DESs were analyzed, with a particular interest in determining the effect of HBD chain length on these parameters. Here, classical molecular dynamics simulations were employed to investigate how the local liquid structure, solvent dynamics, and bulk solvent properties vary with changes in glycol chain length.

Conductivity↗
DOE OSTI2022

Monolayer-like lattice dynamics in bulk WSe 2

Understanding the microscopic lattice dynamics is essential for regulating the thermal properties in two-dimensional layered materials. In transition metal dichalcogenides, the layered structures result in different but closely related phonon dispersions between monolayer and bulk. Here, by combining inelastic X-ray scattering and first-principles calculations, the lattice dynamics of tungsten diselenide (WSe 2 ) was investigated comprehensively, and a monolayer-like lattice dynamics in the bulk WSe 2 was revealed. We performed the first temperature-dependent phonon dispersions measurement and obtained the mode Grüneisen parameters of bulk WSe 2 , which are found to be in better agreement with the calculations on the monolayer system than those of the bulk. This observation indicates that lattice dynamics in bulk WSe 2 hold the characteristic of monolayers. The result provides valuable insights into the thermal properties of WSe 2 -based devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multicolored microwave absorbers with dynamic frequency modulation

Microwave-absorbing materials are extensively used in intelligent electronic devices and stealth technologies where the ability to dynamically adjust microwave-absorbing capacity in response to specific requirements is vitally important. Herein, we report a new approach for constructing dynamically tunable microwave absorbers with ultrawide tunable frequency ranges that are simultaneously endowed with vibrant structural colors. Here, the methodology produces structural colors and adjusts absorption properties by constructing ZnO coatings with precisely adjustable thicknesses on a polypyrrole/melamine foam (PPy/MF) surface by atomic layer deposition (ALD) in conjunction with a pressure-driven strategy that regulates the compression ratio. The electrical conductivity, electromagnetic parameters, thickness, and pore size of the ZnO-coated PPy/MF (ZnO/PPy/MF) are effectively adjusted, and simply applying external pressure widens the tunable frequency range and the effective absorption bandwidth. As a result, the effective absorption frequency of ZnO/PPy/MF is dynamically adjustable from the S band to the Ku band, thereby covering 94.3% of the entire microwave spectrum. Moreover, the brilliant and uniform structural colors of ZnO/PPy/MF, which span various color categories, are precisely regulated by tuning the thickness of the ZnO coating by adjusting the number of ALD cycles. ZnO/PPy/MF is strongly hydrophobic, which endows it with remarkable self-cleaning properties. Therefore, ZnO/PPy/MF provides a conceptually novel platform for the development of next-generation smart microwave-absorbing materials due to its integrated dynamic frequency-regulating ability, brilliant structural coloration, and self-cleaning features.

36 MATERIALS SCIENCE↗
DOE OSTI2022

CoSyR: A novel beam dynamics code for the modeling of synchrotron radiation effects

The self-consistent nonlinear dynamics of a relativistic charged particle beam interacting with its complete self-fields is a fundamental problem underpinning many of the accelerator design issues in high brightness beam applications, as well as the development of advanced accelerators. Particularly, synchrotron radiation induced effects in a magnetic dispersive beamline element can lead to collective beam instabilities and emittance growth. A novel beam dynamics code is developed based on a Lagrangian method for the calculation of the particles’ radiation near-fields using wavefront/wavelet meshes via the Green’s function of the Maxwell equations. These fields are then interpolated onto a moving mesh for dynamic update of the beam. This method allows radiation co-propagation and self-consistent interaction with the beam in 2D/3D simulations at greatly reduced numerical errors. Multiple levels of parallelisms are inherent in this method and implemented in our code CoSyR to enable at-scale simulations of nonlinear beam dynamics on modern computing platforms using MPI, multi-threading, and GPUs. Here, the current 2D implementation of CoSyR has been used to evaluate the transverse and longitudinal coherent radiation effects on the beam and to investigate beam optics designs proposed for mitigation of beam brightness degradation in a magnetic bunch compressor. In this paper, the design of CoSyR, as well as the benchmark with other coherent synchrotron radiation models, are described and discussed. Extension of the core algorithms to 3D is possible and planned.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗