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Results for “Loads and Dynamics”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Room-Temperature Microstructural Evolution of Extruded AM80 Magnesium Alloys under Dynamic Loading

Dynamic compression tests were conducted using a split Hopkinson pressure bar along the transverse direction at strain rates (SRs) of 3200 and 6000 s{sup −1}. The initial microstructure significantly affected the flow stress behavior and microstructural evolution of the two studied AM80 magnesium alloys. Under the same SR loading, the as-extruded alloy exhibited an apparently higher flow stress. At a SR of 6000 s{sup −1}, the flow stress of the as-extruded alloy exhibited a visible decrease (~ 34 MPa) as the strain increased to ~ 0.2, whereas a constant flow stress was exhibited by the solution-treated alloy. High-density dislocations and mechanical twins were detected in the two alloys at a SR of 3200 s{sup −1}. Interestingly, dynamic recrystallization (DRX) with an average grain size of ~ 2 µm was only identified in the as-extruded alloy as the applied SR increased to 6000 s{sup −1}. The increased localized deformation in the as-extruded alloy due to the retained strain energy and high critical twinning stress improved the DRX driving force, thereby resulting in visibly different micrographs of the two alloys when impacted at the SR of 6000 s{sup −1}.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Discrete Empirical Interpolation Method Based Dynamic Load Model Reduction

Dynamic load models add significant complexity to bulk power system time-domain simulations. The complexity is due to the large number of ordinary differential equations (ODEs) introduced by the dynamic load components such as induction motors. It is challenging to derive reduced-order models (ROMs) for dynamic loads due to the nonlinear functions in their governing equations. This paper applies the discrete empirical interpolation method enhanced proper orthogonal decomposition (DEIM-POD) to approximate the full dynamic load model with the ROM that minimizes the projection error of the nonlinear functions in dynamic load ODEs onto their dominant modes. This approach only requires evaluation of nonlinear functions at selected observation points. The observation points selected by DEIM also provide information for screening critical load buses where dynamic load model parameters contribute the most to the accuracy of ROM across multiple contingencies. The proposed approach is validated on IEEE 9-bus, WECC 179-bus and 2384-bus Polish systems.

bulk power system↗
DOE OSTI2018

Dynamic Load Balancing Based on Constrained K-D Tree Decomposition for Parallel Particle Tracing

Particle tracing is a fundamental technique in flow field data visualization. In this work, we present a novel dynamic load balancing method for parallel particle tracing. Specifically, we employ a constrained k-d tree decomposition approach to dynamically redistribute tasks among processes. Each process is initially assigned a regularly partitioned block along with duplicated ghost layer under the memory limit. During particle tracing, the k-d tree decomposition is dynamically performed by constraining the cutting planes in the overlap range of duplicated data. This ensures that each process is reassigned particles as even as possible, and on the other hand the new assigned particles for a process always locate in its block. Result shows good load balance and high efficiency of our method.

Zhang, Jiang↗
DOE OSTI2018

In-situ Experiments to Capture the Evolution of Microstructure During Phase Transformation of Titanium Under Dynamic Loading

Under sufficient stresses, such as during dynamic loading, titanium experiences a phase transformation from hcp alpha phase to hexagonal omega phase. Omega phase is often retained in the microstructure after unloading, and has a strong influence on subsequent mechanical properties. Simulations suggest there are multiple pathways and underlying mechanisms for this transformation. Due to the incredibly short timescales involved, experimental measurements for model validation have been difficult. However, new capabilities at the Advanced Photon Source have enabled diffraction measurements during plate impact experiments to study the evolution of titanium during transformation. These high-rate data allow us to probe the mechanism and kinetics of phase transformations in new ways. Recent results will be presented and compared to post-mortem characterization of soft-recovered shocked specimens. Comparisons are then made with previous tests where material was shock-loaded and soft recovered for microstructural analysis. Together these techniques create a consistent picture of material behavior during the shock-induced α–ω phase transformation in titanium.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Response of Graphite to Dynamic Loading and Hypervelocity Jet Impacts

The compressive strengths of three varieties of high purity graphite, PCEA, NBG-18, and NBG-25, as well as the depth of penetration of small-scale charges into these materials was experimentally determined. These grades are similar in density, ranging from 1.80 – 1.85 g/cc, and nominal apparent porosity, ranging from 18% to 20%, but provide a wide range in maximum grain or particle size from 10s to 1000s of µm. Two very different manufacturing methods are also represented; PCEA is extruded while NBG-18 and NBG-25 are iso-molded. The quasistatic and dynamic strengths of each grade were determined on a load frame and split-Hopkinson pressure bar, respectively. The depth of penetration (DOP) of two small-scale shaped charges, the Teledyne RP-1 and RP-4, was determined against graphite. The global response of the RP-4 impacts was markedly different as the PCEA samples remained intact while all the NBG-25 samples split into 2 or 3 pieces after the jet penetration had completed. However, for all tests, the trusted DOPs fell within 2 cm. Preliminary hydrocode modeling of the penetration events used existing models that were not designed for graphite. The results can be tuned to reasonably reproduce the DOP, but the wound channel geometry is not reproduced well. A model designed for graphite would need to represent graphite’s non-linear and energy dissipation characteristics.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Modeling Load Dynamics to Support Resiliency-based Operations in Low-Inertia Microgrids

Microgrids have repeatedly demonstrated the ability to provide uninterrupted service to critical end-use loads during normal outages, severe weather events, and natural disasters. While their ability to provide critical services is well documented, microgrids present a more dynamic operational environment than grid-connected distribution systems. The dynamics of a microgrid are commonly driven by the high inertia of rotating generators, which are common in many microgrids. In such high-inertia systems, the impact of end-use load dynamics are often not examined. However, with the increased penetration of inverter-based generation with little or no inertia, it is necessary to consider the impact that the dynamics of the end-use loads have on the operations of microgrids, particularly for a resiliency-based operation. These operations include, but are not limited to, switching operations, loss of generating units, and the starting of induction motors. This paper examines the importance of including dynamic models of the end-use load when evaluating the operations of low inertia microgrids, and shows that by properly representing their behavior, it is possible to cost effectively size equipment while supporting resilient operations of critical end-use loads.

Tuffner, Francis K.↗
DOE OSTI2022

Examination of the cerium α-ε phase transition under dynamic loading with x-ray diffraction

Recent examination of the cerium Hugoniot with pyrometry and x-ray diffraction (XRD) has revealed a narrow solid-liquid two-phase region. It has been suggested that nonequilibrium melting may be occurring along the Ce Hugoniot, with either melt kinetics or a sluggish α-ε transition impeding the transition. In particular, the kinetics of the α-ε is unknown and the location of the phase boundary is in dispute. Static measurements suggest a nearly vertical phase boundary that intersects the Hugoniot at 6–7 GPa. This lies in direct conflict with dynamic measurements along the Hugoniot observing α-Ce through incipient melt. This work presents dynamic experiments using XRD to examine the behavior of the α-ε phase transition. The results show that the α-ε phase transition occurs through a tetragonal distortion, with the transition beginning at temperatures below the solid Hugoniot. Following the initial deviation from an ideal fcc structure, the c/a ratio is found to gradually increase with no steady value observed in the ε phase within the range of these experiments (below 17 GPa). Multiple diffraction patterns captured during the peak stress state show no significant change in c/a ratio prior to uniaxial release, upon which Ce reverts to an fcc structure. Furthermore, the results indicate that the α-ε transition occurs rapidly, both on loading and release. An examination of the c/a ratio with increasing temperatures suggests 11.5 GPa as a lower bound for the location of the α-ε-liquid triple point.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Emerging Technologies for Improved Plug Load Management Systems: Learning Behavior Algorithms and Automatic and Dynamic Load Detection

Plug loads are responsible for a significant portion of the energy consumed in commercial buildings, yet their distributed and ever-changing nature makes them one of the most challenging building end uses to manage. Plug load management systems exist today that utilize smart plugs to meter and control devices at the outlet level, however, their uptake has been relatively slow in part due to the significant labor required for installation and maintenance. Learning behavior algorithms and automatic and dynamic load detection have been identified as two technology areas that could accelerate the adoption of plug load management systems by reducing these labor demands and providing additional energy efficiency and non-energy benefits. Learning behavior algorithms learn occupant behavior and adjust plug load management systems accordingly, allowing for the automatic creation of optimized control schedules. Automatic and dynamic load detection allows a plug load management system to identify devices as they are plugged in to a building and keeps the system up to date as devices are moved throughout a building. In this paper, we present our findings with respect to the current state of these two technologies based on a review of existing research and patents, as well as a series of interviews with companies working in the plug load space. We have found that, as of now, no commercialized solutions exist for these plug load technologies and that more work is needed to bring them to market. In addition, we summarize our findings related to the technology challenges, market barriers, drivers, and opportunities for these technologies moving forward.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2017

Exploring dynamic load imbalance solutions with the CoMD proxy application

Proxy applications are developed to simplify studying parallel performance of scientific simulations and to test potential solutions for performance problems. However, proxy applications are typically too simple to allow work migration or to represent the load imbalance of their parent applications. To study the ability of load balancing solutions to balance work effectively, we enable work migration in one of the Exascale Co-design Center for Materials in Extreme Environments (ExMatEx) [1] applications, CoMD. We design a methodology to parameterize three key aspects necessary for studying load imbalance correction: (1) the granularity with which work can be migrated; (2) the initial load imbalance; (3) the dynamic load imbalance (how quickly the load changes over time). Finally, we present a study of the impact of flexibility in work migration in CoMD on load balance and the associated rebalancing costs for a wide range of initial and dynamic load imbalance scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Particle Swarm Optimization of Dynamic Load Model Parameters in Large Systems

This paper considers two dynamic load models that are widely used in industry to account for induction motor behavior: CMLD and CLOD. These models must be parametrized for the specific utility system in a general way so that they can be used in planning studies and provide a conservative but realistic representation of load behavior. This study considers a measurement-based approach to tuning both models. The load modeling study compares the response of the tuned models to generic candidate models using historical events. This study considers one area-based subsystem to simplify the modeling approach and reduce the number of models required for simulations. Additionally, because dynamic load models often produce similar results for different sets of parameters, a sensitivity study was conducted to assess the parameter impacts on the voltage response. The sensitivity study covers the parameters that are tuned using event measurements. The process to estimate the parameters uses the particle-swarm optimization algorithm. Overall, the performance of the tuned model more accurately captures recovery voltage, delayed recovery, and settling voltage than its predecessor models while not being overly tuned so that it remains general for peak summer conditions.

dynamic load modeling↗
DOE OSTI2020

The effect of loading direction on the fracture behaviors of cortical bone at a dynamic loading rate

Here, the dynamic cracking processes in porcine cortical bone were visualized in real-time using the high-speed synchrotron X-ray phase-contrast imaging (PCI) technique in three osteon orientations: in-plane transverse, out-of-plane transverse and in-plane longitudinal. The dynamic flexural loading applied on the pre-notched bone specimens was introduced by a modified Kolsky compression bar. High-speed X-ray images of the entire loading events were documented with a high-speed camera. Three-dimensional X-ray micro-computed tomography was conducted to examine the intact microstructures and obtain the basic material properties of the bone material used for mechanical characterizations. The onset location, where crack initiated, and the subsequent direction, along which the incipient crack propagated, were measured quantitatively using the high-speed X-ray images and the latter was found dependent on the osteon direction significantly. The crack propagation velocities were dependent on crack extension over the entire crack path significantly for all the three directions while the initial velocity for in-plane longitudinal direction was lower than the other two directions. Straight-through crack paths were observed for in-plane longitudinal specimens while the cracks were deflected and twisted in the in-plane transverse direction. For out-of-plane transverse direction, the cracks follow paths with tortuosity fall in between the other two directions, showing a mixed mode of fractures of the former two extreme cases. The toughening mechanisms, visualized by the high-speed X-ray images, and the corresponding fracture toughness, evaluated in terms of fracture initiation toughness and crack growth resistance curve (R-curve), were also found significantly different among the three osteon directions, suggesting an overall transition from brittle to ductile-like fracture behaviors at the dynamic displacement rate (5.4 m/s) as the osteon orientation varies from in-plane longitudinal to out-of-plane transverse, and to in-plane transverse eventually.

42 ENGINEERING↗
DOE OSTI2023

A parallel p ‐adaptive discontinuous Galerkin method for the Euler equations with dynamic load‐balancing on tetrahedral grids

Abstract A novel p ‐adaptive discontinuous Galerkin (DG) method has been developed to solve the Euler equations on three‐dimensional tetrahedral grids. Hierarchical orthogonal basis functions are adopted for the DG spatial discretization while a third order TVD Runge‐Kutta method is used for the time integration. A vertex‐based limiter is applied to the numerical solution in order to eliminate oscillations in the high order method. An error indicator constructed from the solution of order and is used to adapt degrees of freedom in each computational element, which remarkably reduces the computational cost while still maintaining an accurate solution. The developed method is implemented with under the Charm++ parallel computing framework. Charm++ is a parallel computing framework that includes various load‐balancing strategies. Implementing the numerical solver under Charm++ system provides us with access to a suite of dynamic load balancing strategies. This can be efficiently used to alleviate the load imbalances created by p ‐adaptation. A number of numerical experiments are performed to demonstrate both the numerical accuracy and parallel performance of the developed p ‐adaptive DG method. It is observed that the unbalanced load distribution caused by the parallel p ‐adaptive DG method can be alleviated by the dynamic load balancing from Charm++ system. Due to this, high performance gain can be achieved. For the testcases studied in the current work, the parallel performance gain ranged from 1.5× to 3.7×. Therefore, the developed p ‐adaptive DG method can significantly reduce the total simulation time in comparison to the standard DG method without p ‐adaptation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Investigation of Mode I Notch Toughness of Zr{sub 41.2}Ti{sub 13.8}Cu{sub 10}Ni{sub 12.5}Be{sub 22.5} Metallic Glass under Dynamic Loading Conditions

Based on dynamic three-point bending tests, the dynamic notch toughness (K{sub Q}{sup d}) of Zr{sub 41.2}Ti{sub 13.8}Cu{sub 10}Ni{sub 12.5}Be{sub 22.5} (Vit 1) bulk metallic glass (BMG) was found to be sensitive to stress intensity factor rate ( K-dot {sub Q}{sup d}), which varied from 5.21 to 31.90 MPa m{sup 1/2}. The number of shear bands (N{sub s}) in the notch tip plastic zone was quantitatively analyzed. The phenomenon wherein N{sub s} decreased with increasing loading rate was explained based on the theory of the shear transformation zone and the softening mechanism. Then, power law relationships were established among N{sub s}, K{sub Q}{sup d} and K-dot {sub Q}{sup d}. The results showed that shear bands can affect K{sub Q}{sup d} and K-dot {sub Q}{sup d} and act as a bridge connecting K{sub Q}{sup d} and K-dot {sub Q}{sup d}. The sensitivity of K{sub Q}{sup d} to K-dot {sub Q}{sup d} in BMGs can be well explained by the variation of N{sub s} with loading rate.

36 MATERIALS SCIENCE↗
DOE OSTI2021

PV and Dynamic Load Modeling Update

This report documents the PV and dynamic load modeling update for transient stability, EMT, harmonics, and short circuit analyses during budget period one of the DOE PV-MOD research.

14 SOLAR ENERGY↗
DOE OSTI2018

Correction of Rolling Mill Mechatronic System to Limit Dynamic Loads

Regulation in the mechatronic system of a DUO-300 rolling mill is investigated. The dynamics of an electric drive with a predictive PI controller in the current loop is analyzed. Methods are proposed for damping of self-oscillation and decrease in dynamic loads within the mechatronic system.

42 ENGINEERING↗
DOE OSTI2020

Sequential Bayesian Parameter Estimation of Stochastic Dynamic Load Models

In this paper we focus on the parameter estimation of dynamic load models with stochastic terms-in particular, load models where protection settings are uncertain, such as in aggregated air conditioning units. We show how the uncertainty in the aggregated protection characteristics can be formulated as a stochastic differential equation with process noise. We cast the parameter inversion within a Bayesian parameter estimation framework, and we present methods to include process noise. We demonstrate the benefits of considering stochasticity in the parameter estimation and the risks of ignoring it.

Bayesian Statistics↗