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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

Constitutive modelling of evolving flow anisotropy including distortional hardening

The paper presents a new constitutive model for anisotropic metal plasticity that takes into account the expansion or contraction (isotropic hardening), translation (kinematic hardening) and change of shape (distortional hardening) of the yield surface. The experimentally observed region of high curvature ('nose') on the yield surface in the loading direction and flattened shape in the reverse loading direction are modelled here by means of the concept of directional distortional hardening. The modelling of directional distortional hardening is accomplished by means of an evolving fourth-order tensor. The applicability of the model is illustrated by fitting experimental subsequent yield surfaces at finite plastic deformation. Comparisons with test data for aluminium low and high work hardening alloys display a good agreement between the simulation results and the experimental data.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Accurate Load and Generation Scheduling for Linearized DC Models with Contingencies

The power restoration timeline suggested by the DC power flow and the Angle Constrained DC power flow is shown. Unfortunately, the suggested generator dispatch does not always lead to feasible AC power flow solutions. Even when the AC solution is feasible, the inaccuracies of the DC power flow can lead to significant line overloads.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Difference in load predictions obtained with effective turbulence vs. a dynamic wake meandering modeling approach

Abstract. According to the international standard for wind turbine design, the effects of wind turbine wakes on structural loads can be considered in two ways: (1) by augmenting the ambient turbulence levels with the effective turbulence model (EFF) and then calculating the resulting loads and (2) by performing dynamic wake meandering (DWM) simulations, which compute wake effects and loads for all turbines on a farm at once. There is no definitive answer in scientific literature as to the consequences of choosing one model over the other, but the two approaches are unarguably very different. The work presented here expounds on these differences and investigates to what extent they affect the simulated structural loads. We consider an idealized 4×4 rectangular array of National Renewable Energy Laboratory 5 MW wind turbines with a spacing of 5 by 8 rotor diameters and three wind speed scenarios at high ambient turbulence. Load simulations are performed in OpenFAST with EFF and in FAST.Farm with the DWM implementation. We compare ambient turbulence, wind farm turbulence, and loads between both approaches. When omnidirectional results are compared, EFF wind farm turbulence intensity is consistently higher by 0.2 % (above-rated wind speed) to 2.7 % (below-rated wind speed). However, for certain wind directions, the EFF turbulence can be lower than FAST.Farm by almost 9 %. Wind speeds within the farm were found to differ by up to 3 m s−1 due to the lack of wake deficits in the EFF approach, leading to longer tails toward low values in the FAST.Farm mean load distributions. Consistent with the turbulence results, the median EFF load standard deviations are also consistently higher, by a maximum of 20 % and 17 % for blade-root out-of-plane and tower-base fore-aft moments, respectively.

17 WIND ENERGY↗
DOE OSTI2014

Modeling Framework and Validation of a Smart Grid and Demand Response System for Wind Power Integration

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

Demand Response↗
DOE OSTI2023

Piezoelectric Energy Harvesting Gyroscopes: Comparative Modeling and Effectiveness

Given its versatility in drawing power from many sources in the natural world, piezoelectric energy harvesting (PEH) has become increasingly popular. However, its energy harvesting capacities could be enhanced further. Here, a mathematical model that accurately simulates the dynamic behavior and energy harvested can facilitate further improvements in the performance of piezoelectric devices. One of the goals of this study is to create a dependable reduced-order model of a multi-purpose gyroscope. This model will make it possible to compute the harvested voltage and electrical power in a semi-analytical manner. The harvested voltage is often modeled as an average value across the whole electrode surface in piezoelectric devices. We propose a model which provides practical insights toward optimizing the performance of the system by considering a spatially varying electric field across the electrode surface length. Our framework allows investigation of the limits of applicability of the modeling assumptions across a range of load resistances. The differential quadrature method (DQM) provides the basis for the suggested numerical solution. The model is also employed to examine energy harvesting under various resistance loads. The newly developed spatially varying model is evaluated for open- and closed-circuit conditions and is proved to be accurate for various values of load resistance that have not previously been considered. The results show that using a spatially varying model is more versatile when modeling the performance of the piezoelectric multifunctional energy harvester. The performance may be accurately captured by the model for load resistances ranging between 103 Ω and 108 Ω. At optimum load resistance and near 65 KHz, the maximum power output predicted by the spatially varying (SV) model is 1.3 mV, 1.5 mV for the open-circuit (OC) model, and 2.1 mV for the closed circuit (CE) model. At a high-load resistance, the SV and OC models all predict the maximum power output to be 1.9 mV while the CE model predicted the maximum voltage to be 3 mV.

42 ENGINEERING↗
DOE OSTI2025

PBE-HIL (Powering the Blue Economy Hardware-in-the-Loop models) [SWR-25-37]

Powering the Blue Economy Hardware-in-the-Loop models (PBE-HIL) is a repository of Power Hardware-in-the-loop models developed for typical Powering the Blue Economy market loads and power requirements. The HIL models were developed to be as generic and functional as possible, meaning that the user can easily configure these models to represent their unique PBE design. These PBE load and power requirement HIL models can then be used to inform marine energy converter (MEC) and power electronics design, as well as be used in laboratory testing using HIL equipment, leading to improved understanding of MEC performance and lower risk prior to open-water MEC deployment.

Labuschagne, Hannes [National Renewable Energy Lab↗
DOE OSTI2017

Shielding Analysis Capability of UNF-ST&DARDS

The Used Nuclear Fuel Storage, Transportation and Disposal Analysis Resource and Data System (UNF-ST&DARDS) is used to perform dose rate calculations for spent nuclear fuel (SNF) transportation packages based on the actual physical and nuclear characteristics (i.e., assembly design, burnup, initial enrichment, and cooling time) of the as-loaded SNF. Nuclear fuel data, transportation package model templates, and SNF canister loading map information residing within the tool facilitate automated generation of SCALE input files for radiation source term and dose rate calculations. Transportation package specific models developed for UNF-ST&DARDS dose rate analyses are described in detail. UNF-ST&DARDS dose rate analyses were performed in this paper for over 400 SNF canisters from 16 sites in their designated transportation casks. For simplicity, representative dose rate calculation results are presented as a function of time (i.e., selected calendar years between 2020 and 2100) for 73 SNF canisters in dry storage at four sites. For these canisters, the projected maximum dose rate values at 2 m from the lateral surfaces of the vehicle under normal conditions of transport (NCT) would vary between 1.9 and 11.5 mrem/h in 2020. Five SNF canisters will exceed the regulatory dose rate limit of 10 mrem/h at 2 m in 2020, and the analyzed SNF canisters will comply with regulatory dose rate limits by 2030. An analysis of the impact on the dose rate of fuel failure and reconfiguration during transportation indicated that the maximum dose rate for hypothetical accident conditions will be unaffected, and the NCT maximum dose rate at 2 m would have a maximum increase by a factor of 1.7 for a representative pressurized water reactor package and by a factor of 2.6 for a representative boiling water reactor package relative to intact fuel. Finally, analysis of the actual heat loading and the dose rate at 2 m from the lateral surface of the vehicle for the five SNF canisters exceeding the NCT regulatory dose rate limit of 10 mrem/h in 2020 showed that the dose rate could be more limiting with respect to regulatory requirements than the heat loading; i.e., the canister transportability date may be evaluated based on the transportation package’s external dose rate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Dynamic Behavior of Sand: Annual Report FY 11

Currently, design of earth-penetrating munitions relies heavily on empirical relationships to estimate behavior, making it difficult to design novel munitions or address novel target situations without expensive and time-consuming full-scale testing with relevant system and target characteristics. Enhancing design through numerical studies and modeling could help reduce the extent and duration of full-scale testing if the models have enough fidelity to capture all of the relevant parameters. This can be separated into three distinct problems: that of the penetrator structural and component response, that of the target response, and that of the coupling between the two. This project focuses on enhancing understanding of the target response, specifically granular geomaterials, where the temporal and spatial multi-scale nature of the material controls its response. As part of the overarching goal of developing computational capabilities to predict the performance of conventional earth-penetrating weapons, this project focuses specifically on developing new models and numerical capabilities for modeling sand response in ALE3D. There is general recognition that granular materials behave in a manner that defies conventional continuum approaches which rely on response locality and which degrade in the presence of strong response nonlinearities, localization, and phase gradients. There are many numerical tools available to address parts of the problem. However, to enhance modeling capability, this project is pursuing a bottom-up approach of building constitutive models from higher fidelity, smaller spatial scale simulations (rather than from macro-scale observations of physical behavior as is traditionally employed) that are being augmented to address the unique challenges of mesoscale modeling of dynamically loaded granular materials. Through understanding response and sensitivity at the grain-scale, it is expected that better reduced order representations of response can be formulated at the continuum scale as illustrated in Figure 1 and Figure 2. The final result of this project is to implement such reduced order models in the ALE3D material library for general use.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗