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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Study the Cyclic Plasticity Behavior of 508 LAS under Constant, Variable and Grid-Load-Following Loading Cycles for Fatigue Evaluation of PWR Components

This report provides an update of an earlier assessment of environmentally assisted fatigue for components in light water reactors. This report is a deliverable in September 2016 under the work package for environmentally assisted fatigue under DOE’s Light Water Reactor Sustainability program. In an April 2016 report, we presented a detailed thermal-mechanical stress analysis model for simulating the stress-strain state of a reactor pressure vessel and its nozzles under grid-load-following conditions. In this report, we provide stress-controlled fatigue test data for 508 LAS base metal alloy under different loading amplitudes (constant, variable, and random grid-load-following) and environmental conditions (in air or pressurized water reactor coolant water at 300°C). Also presented is a cyclic plasticity-based analytical model that can simultaneously capture the amplitude and time dependency of the component behavior under fatigue loading. Results related to both amplitude-dependent and amplitude-independent parameters are presented. The validation results for the analytical/mechanistic model are discussed. This report provides guidance for estimating time-dependent, amplitude-independent parameters related to material behavior under different service conditions. The developed mechanistic models and the reported material parameters can be used to conduct more accurate fatigue and ratcheting evaluation of reactor components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

FAST.Farm Development and Validation of Structural Load Prediction Against Large Eddy Simulations

FAST.Farm is a mid-fidelity engineering tool developed by the National Renewable Energy Laboratory targeted at accurately and efficiently predicting wind turbine power production and structural loading in wind farm settings, including wake interactions between turbines. FAST.Farm is based on several principles of the dynamic wake meandering (DWM) model, but also addresses limitations of previous DWM implementations. Previous FAST.Farm studies have shown the similarities and differences between FAST.Farm and large eddy simulations for rigid turbine cases. The objective of this work is to quantify the ability of FAST.Farm to accurately predict turbine structural response in a small wind farm. This is done by comparing FAST.Farm structural response to SOWFA-OpenFAST results for three laterally-aligned turbines. The purpose of this study is to characterize the similarities and differences between FAST.Farm and a higher fidelity model for predicting turbine structural response in a wind farm for differing atmospheric inflows. Strong statistical agreement was found between FAST.Farm and SOWFA-OpenFAST structural response for the non-waked upstream turbine, and good agreement was found for the downstream turbines for most structural quantities. Higher differences were seen for downstream turbines with low ambient turbulence intensity or yawed turbines, suggesting areas for FAST.Farm wake dynamics modeling improvements. For all cases and turbines, small statistical differences were seen between blade deflections and bending moments, with larger differences for tower-top and tower-base bending moments. Overall, the results establish confidence for applying FAST.Farm to wind farm power and loads analyses and identify areas where further model validations and model improvements should be targeted.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2017

Predicting Deformation Limits of Dual-Phase Steels Under Complex Loading Paths

The deformation limits of various DP980 steels are examined in this study with deformation instability theory. Under uniaxial tension, overall stress-strain curves of the material are estimated based on simple rule of mixture (ROM) with both iso-strain and iso-stress assumptions. Under complex loading paths, actual microstructure-based finite element (FE) method is used to explicitly resolve the deformation incompatibilities between the soft ferrite and hard martensite phases. The results show that, for uniaxial tension, the deformation instability theory with iso-strain-based ROM can be used to provide the lower bound estimate of the uniform elongation (UE) for the various DP980 considered. Under complex loading paths, the deformation instability theory with microstructure-based FE method can be used in examining the effects of various microstructural features on the deformation limits of DP980 steels.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Crystalline Loading of Lipophilic Coenzyme Q10 Pharmaceuticals within Conjugated Carbon Aerogel Derivatives

Low-density aerogel materials currently are being considered for applications in controlling the rate of release for small-molecule pharmaceuticals in vivo. In particular, silica (SiO2) aerogels are an intriguing platform for controlling both the absolute amount of drug loading, but also the crystalline state of small molecule pharmaceuticals has been shown to affect drug release kinetics. To date, loading silica aerogel materials with crystalline pharmaceuticals typically require dissolving small molecules in a supercritical solvent (i.e., CO2) before drying to recover the aerogel/drug composite. Here we demonstrate a simple and low-cost method for controlling the crystallinity of the model drug coenzyme Q10 (CoQ10) within carbon aerogel materials by rationally controlling the chemical microstructure of the aerogel to exhibit ?-conjugated (sp2) chemical bonding. In particular, both pyrolyzed graphene and nanodiamond aerogels exhibit enhanced intrinsic drug loading capacity and CoQ10 crystallinity over a broad range of sp2 surface-curvature. In contrast, amorphous carbon aerogel materials are observed to load CoQ10 pharmaceuticals with strictly amorphous microstructure.

Lim, Mathew↗
DOE OSTI2017

Quenching measurements and modeling of a boron-loaded organic liquid scintillator

Organic liquid scintillators are used in a wide variety of applications in experimental nuclear and particle physics. Boron-loaded scintillators are particularly useful for detecting neutron captures, due to the high thermal neutron capture cross section of 10 B. These scintillators are commonly used in neutron detectors, including the DarkSide-50 neutron veto, where the neutron may produce a signal when it scatters o protons in the scintillator or when it captures on 10 B. Reconstructing the energy of these recoils is complicated by scintillation quenching. Understanding how nuclear recoils are quenched in these scintillators is an important and dicult problem. In this article, we present a set of measurements of neutron-induced proton recoils in a boron-loaded organic liquid scintillator at recoil energies ranging from 57-467 keV, and we compare these measurements to predictions from different quenching models. We and that a modified Birks' model whose denominator is quadratic in dE=dx best describes the measurements, with χ 2 /NDF = 1:6. This result will help model nuclear recoil scintillation in similar detectors and can be used to improve their neutron tagging efficiency.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Improving Frequency Stability and Minimizing Load Shedding Events by Adopting Grid-Scale Energy Storage with Grid Forming Inverters

The upward adoption trend of renewable generation not only means cleaner energy integrated into modern power grids, but also that most new generation sources are based on front-end inverter bridges, used as interfaces to most wind generation and all the solar PV. It is well known that due to their power electronics-based construction rather than rotational shafts, these sources do not provide inertia inherently, nor substantial amounts of short-circuit currents. However, stable energy such as what can be stored in energy storage systems, although interfaced via inverters, can be controlled to respond to system disturbances in a manner that emulates inertial behavior. This paper focuses on the application of such energy storage systems to augment inertia in the island of Puerto Rico. To do so, a user defined inverter model that contains grid forming capabilities and fast frequency response is modeled and integrated into the real transmission system in power flow and dynamics software. Energy storage is then connected to two selected areas so that it not only provides frequency regulation to avoid widespread load shedding events, but also other tangible benefits. The simulated cases suggest that even relatively small energy storage systems can avert load shedding events if adequately placed in the transmission network.

Grid-forming inverters, IBR, Inertia↗
DOE OSTI2023

Interpretable Data-Driven Probabilistic Power System Load Margin Assessment with Uncertain Renewable Energy and Loads

The increasing uncertainties caused by the high-penetration of stochastic renewable generation resources poses a significant threat to the power system voltage stability. To address this issue, this paper proposes a probabilistic deep kernel learning enabled surrogate model to extract the hidden relationship between uncertain sources, i.e., wind power and loads, and load margin for probabilistic load margin assessment (PLMA). Unlike other deep learning approaches, a kernel SHAP provides the sensitivity analysis as well as interpretability of the inputs to outputs influences. This allows identifying the critical factors that affect load margin so that corrective control can be initiated for stability enhancement. Numerical results carried out on the IEEE 118-bus power system demonstrate the accuracy and efficiency of the proposed data-driven PLMA scheme.

deep kernel learning↗
DOE OSTI2023

A Modified Sequence-to-point HVAC Load Disaggregation Algorithm

This paper presents a modified sequence-to-point (S2P) algorithm for disaggregating the heat, ventilation, and air conditioning (HVAC) load from the total building electricity consumption. The original S2P model is convolutional neural network (CNN) based, which uses load profiles as inputs. We propose three modifications. First, the input convolution layer is changed from 1D to 2D so that normalized temperature profiles are also used inputs to the S2P model. Second, a drop-out layer is added to improve adaptability and generalizability so that the model trained in one area can be transferred to other geographical areas without labelled HVAC data. Third, a fine-tuning process is proposed for areas with a small amount of labelled HVAC data so that the pre-trained S2P model can be fine-tuned to achieve higher disaggregation accuracy (i.e., better transferability) in other areas. The model is first trained and tested using smart meter and sub-metered HVAC data collected in Austin, Texas. Then, the trained model is tested on two other areas: Boulder, Colorado and San Diego, California. Simulation results show that the proposed modified S2P algorithm outperforms the original S2P model and the support-vector machine based approach in accuracy, adaptability, and transferability.

Ye, Kai↗
DOE OSTI2019

DGs for Service Restoration to Critical Loads in a Secondary Network

During a major outage in a secondary network distribution system, distributed generators (DGs) connected to the primary feeders as well as the secondary network can be used to serve critical loads. This paper proposed a resilience-oriented method to determine restoration strategies for secondary network distribution systems after a major disaster. Technical issues associated with the restoration process are analyzed, including the operation of network protectors, inrush currents caused by the energization of network transformers, synchronization of DGs to the network, and circulating currents among DGs. A look-ahead load restoration framework is proposed, incorporating technical issues associated with secondary networks, limits on DG capacity and generation resources, dynamic constraints, and operational limits. The entire outage duration is divided into a sequence of periods. Restoration strategies can be adjusted at the beginning of each period using the latest information. Numerical simulation of the modified IEEE 342-node low voltage networked test system is performed to validate the effectiveness of the proposed method.

Xu, Yin (ORCID:0000000209459024)↗
DOE OSTI2021

Operating a commercial building HVAC load as a virtual battery through airflow control

Virtual battery (VB) is an innovative method to model flexibility of building loads and effectively coordinate them with other resources at a system level. Unlike a real battery with a dedicated power conversion system for charging control, methods are required for operating building loads to deviate from the baseline to respond to grid signals. This paper presents a VB control for a commercial heating, ventilation, and air conditioning (HVAC) system to follow the desired power consumption in real-time by adjusting zonal airflow rates. The proposed method consists of two parts. At the system level, a mixed feedforward and feedback control is used to estimate the desired total airflow rate. At the zone level, two priority-based algorithms are then proposed to distribute the total airflow rate to individual zones. In particular, a zonal airflow limit estimation method is proposed using machine-learning techniques, in contrast to physics-based thermal models in existing studies, to more accurately capture zonal thermal dynamics and improve temperature control performance. An office building on the Pacific Northwest National Laboratory campus is implemented in EnergyPlus, and used to illustrate and validate the proposed control.

Wang, Jiyu↗
DOE OSTI2018

Methodology for Stress-Controlled Fatigue Test Under In-Air and Pressurized Water Reactor Coolant Water Condition and to Evaluate the Effect of Pressurized Water Reactor Water and Loading Rate on Ratcheting [Methodology for Stress-Controlled Fatigue Test Under In-Air and PWR Coolant Water Condition and to Evaluate the Effect of PWR Water and Loading Rate on Ratcheting]

Here, this work investigates the behavior of 316 stainless steel (SS) under stress-controlled low cycle fatigue loading. Several fatigue experiments are conducted under different environment such as in air at 300°C and primary loop water conditions for a pressurized water reactor (PWR). Two different loading conditions are also employed to examine the effect of stress rate on material hardening and ratcheting. During PWR water test, actuator position measurements are used to determine the strain of the specimen. Under PWR environment, 316 SS is found to ratchet to a significantly greater degree compared with in air. At slow stress rate, higher amount of cyclic hardening is observed in 316 SS, and slow stress rate increases the rate of ratcheting. Results also indicate that 316 SS exhibits asymptotic strain response at higher stress loading which can cause material to behave very differently under same stress cyclic loading.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Gaining Insights in Loading Events for Wind Turbine Drivetrain Prognostics

Wind energy is one of the largest sources of renewable energy in the world. To further reduce the operations and maintenance (O&M) costs of wind farms, it is essential to be able to accurately pinpoint the root causes of different failure modes of interest. An example of such a failure mode that is not yet fully understood is white etching cracks (WEC). This can cause the bearing lifetime to be reduced to 5–10% of its design value. Multiple hypotheses are available in literature concerning its cause. To be able to validate or disprove these hypotheses, it is essential to have historic high-frequency measurement data (e.g., load and vibration levels) available. In time, this will allow linking to the history of the turbine operating data with failure data. This paper discusses the dynamic loading on the turbine during certain events (e.g., emergency stops, run-ups, and during normal operating conditions). By combining the number of specific events that each turbine has seen with the severity of each event, it becomes possible to assess which turbines are most likely to show signs of damage.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
DOE OSTI2017

User-Preference-Driven Model Predictive Control of Residential Building Loads and Battery Storage for Demand Response: Preprint

This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility and reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1978

Load and dynamic assessment of B-52B-008 carrier aircraft for finned configuration 1 space shuttle solid rocket booster decelerator subsystem drop test vehicle. Volume 2: Airplane flutter and load analysis results

The airplane flutter and maneuver-gust load analysis results obtained during B-52B drop test vehicle configuration (with fins) evaluation are presented. These data are presented as supplementary data to that given in Volume 1 of this document. A brief mathematical description of airspeed notation and gust load factor criteria are provided as a help to the user. References are defined which provide mathematical description of the airplane flutter and load analysis techniques. Air-speed-load factor diagrams are provided for the airplane weight configurations reanalyzed for finned drop test vehicle configuration.

Quade, D. A.↗
NASA NTRS1978

Load and dynamic assessment of B-52B-008 carrier aircraft for finned configuration 1 space shuttle solid rocket booster decelerator subsystem drop test vehicle. Volume 3: Pylon load data method 1

The pylon loading at the drop test vehicle and wing interface attach points is presented. The loads shown are determined using a stiffness method, which assumes the side stiffness of the foreward hook guide to be one-fourth of the fore and aft stiffness of each drag pin. The net effect of this assumption is that the forward hook guide reacts approximately 85% of the drop test vehicle yawing moment. For a comparison of these loads to previous X-15 analysis design loadings, see Volume 1 of this document.

Quade, D. A.↗