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At least 1,261 records · Page 70

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NASA NTRS1987

Probabilistic SSME blades structural response under random pulse loading

The purpose is to develop models of random impacts on a Space Shuttle Main Engine (SSME) turbopump blade and to predict the probabilistic structural response of the blade to these impacts. The random loading is caused by the impact of debris. The probabilistic structural response is characterized by distribution functions for stress and displacements as functions of the loading parameters which determine the random pulse model. These parameters include pulse arrival, amplitude, and location. The analysis can be extended to predict level crossing rates. This requires knowledge of the joint distribution of the response and its derivative. The model of random impacts chosen allows the pulse arrivals, pulse amplitudes, and pulse locations to be random. Specifically, the pulse arrivals are assumed to be governed by a Poisson process, which is characterized by a mean arrival rate. The pulse intensity is modelled as a normally distributed random variable with a zero mean chosen independently at each arrival. The standard deviation of the distribution is a measure of pulse intensity. Several different models were used for the pulse locations. For example, three points near the blade tip were chosen at which pulses were allowed to arrive with equal probability. Again, the locations were chosen independently at each arrival. The structural response was analyzed both by direct Monte Carlo simulation and by a semi-analytical method.

Shiao, Michael↗

NASA NTRS1990

Finite element analysis of thermal distortion effects on optical performance of solar dynamic concentrator for Space Station Freedom

An analysis was performed to predict the thermal distortion of the solar dynamic concentrator for Space Station Freedom in low earth orbit and to evaluate the effects of that thermal distortion on concentrator on-orbit performance. The analysis required substructural finite element modeling of critical concentrator structural subsystems, structural finite element modeling of the concentrator, mapping of thermal loading onto the structural finite element model, and the creation of specialized postprocessors to assist in interpreting results. Concentrator temperature distributions and thermally induced displacements and slope errors and the resulting receiver flux distribution profiles are discussed. Results determined for a typical orbit indicate that concentrator facet rotations are less than 0.2 mrad and that the change in facet radius due to thermal flattening is less than 5 percent. The predicted power loss due to thermal distortion effects is less than 0.3 percent. As a consequence the thermal distortions of the solar dynamic concentrator in low earth orbit will have a negligible effect on the flux distribution profiles within the receiver.

Doherty, Michael P.↗

NASA NTRS1984

Fracture temperature and flaw growth in nitronic 40 at cryogenic temperatures

The fracture resistance and fatigue response of Armco Nitronic 40 austenitic stainless steel were evaluated under cryogenic conditions. Tensile, fracture toughness and fatigue crack growth properties were measured at -275 F. The tensile yield strength was approximately 120 ksi and the fracture toughness was estimated to be 350 ksi-in /2 on the basis of fracture toughness measurements. Testing was conducted to evaluate the behavior of a simulated section of the wing of the Pathfinder 1 model subject to a load and temperature history typical of that for testing in the National Transonic Facility. The wing section model incorporated a proposed brazing technique for pressure-transducer attachment. The simulated wing section performed satisfactorily at stress levels of nearly 60 percent of the material yield strength. The brazing technique proved to be an effective method of transducer attachment under conditions of high stress levels and large temperature excursions.

Domack, M. S.↗

NASA NTRSDate not supplied

Application of the MAT 213 Composite Impact Model to NASA Problems of Interest

A material model has been developed which incorporates several key capabilities which have been identified as lacking in currently available composite impact models. The material model utilizes experimentally based tabulated input to define the evolution of plasticity and damage as opposed to specifying discrete input parameters (such as modulus and strength). The material model has been implemented into LS-DYNA® as MAT 213. The model can simulate the nonlinear deformation, damage and failure that takes place in a composite under dynamic loading conditions. The deformation model utilizes an orthotropic plasticity formulation. For the damage model, the nonlinear unloading response that is observed prior to the point where the peak stress is reached can be simulated, as well as the stress degradation response that occurs after the peak stress is reached. A variety of failure models, including a generalized tabulated failure model which facilitates the utilization of general failure surfaces, have been implemented into MAT 213. Recent studies at NASA have concentrated on using MAT 213 to analyze both the impact and crush response of a variety of laminated and textile architectures. Several of these studies will be discussed in the presented paper. For example, a woven carbon/Kevlar composite is currently being examined for use in an energy absorber system for rotorcraft structures. MAT 213 analyses have been conducted to examine the ability of the model to accurately simulate the dynamic crush response of this material. Studies are also being conducted to examine the ability of MAT 213 to simulate the ballistic impact response of representative laminated and woven thermoplastic and thermoset matrix composites. NASA efforts are also concentrated on developing methods and processes for improving characterization methods and developing “best practices” for using MAT 213, a summary of which will be discussed in the paper.

Polymer Matrix Composites↗

DOE OSTI2026

OC7 Project Phase II: Code Comparison and Experimental Validation of Hydroelastic Effects and Member-Level Loads in Floating Structures

This paper presents results from Phase II of the OC7 project, focusing on hydroelastic modeling and member-level load prediction for a flexible floating offshore structure. Numerical predictions from 11 academic and industrial partners are validated against experimental measurements obtained from a 1:70-scale test of the VolturnUS-S semisubmersible platform. A comprehensive set of verification and validation cases is examined. The results demonstrate that hydrodynamic added mass has a significant impact on predicted elastic natural frequencies. Under regular wave excitation, the numerical models reproduce platform motions and mooring line tensions with good accuracy. Member-level loads are also predicted with reasonable accuracy. Some discrepancies are observed for potential-flow models not accounting for higher-order effects associated with the instantaneous wetted surface.

17 WIND ENERGY↗

NASA NTRS1985

The Structural Finite Element Model of the C-5A

A substructured NASTRAN model of the C-5A was analyzed for several different load conditions. The size of the model and the number of load cases used presented special problems in computer file and space management. This resulted in revisions to the in-house NASTRAN code. Despite the problems encountered the analyses were completed with excellent results.

Mcclellan, G. W.↗

DOE OSTI2023

BuildingsBench: A Benchmark for Universal Building Load Forecasting [SWR-23-51]

The residential and commercial building stock in the United States is responsible for a significant percentage of energy consumption and greenhouse gas emissions. Electrification of end-uses, as well as decarbonizing the electrical grid through renewable energy sources such as solar and wind, constitutes the pathway to zero-emission buildings. Forecasting day-ahead building energy consumption is an integral part of this solution. Currently, specialized forecasting models are hand-made for each individual building, which is time-consuming, expensive, and leads to duplicated efforts. BuildingsBench is a Python software framework for training and comparing generalized machine learning models for universal building load forecasting. This challenge tasks a single foundational model to generalize its forecasts for a wide variety of buildings, across geographic regions, building types, weather patterns, and more. This software provide code for pre-training such models and subsequently evaluating their performance on a suite of hundreds of diverse real and synthetic buildings. BuildingsBench is a platform for: - Large-scale pretraining with the synthetic Buildings-900K dataset for short-term load forecasting (STLF). Buildings-900K is statistically representative of the entire U.S. building stock and is extracted from the NREL End-Use Load Profiles database. - Benchmarking on two tasks evaluating generalization: zero-shot STLF and transfer learning for STLF. We provide an index-based PyTorch Dataset for large-scale pretraining, easy data loading for multiple real building energy consumption datasets as PyTorch Tensors or Pandas DataFrames, simple (persistence) to advanced (transformer) baselines, metrics management, and more.

Emami, Patrick↗

NASA NTRS2007

Flow Separation Side Loads Excitation of Rocket Nozzle FEM

Modern rocket nozzles are designed to operate over a wide range of altitudes, and are also built with large aspect ratios to enable high efficiencies. Nozzles designed to operate over specific regions of a trajectory are being replaced in modern launch vehicles by those that are designed to operate from earth to orbit. This is happening in parallel with modern manufacturing and wall cooling techniques allowing for larger aspect ratio nozzles to be produced. Such nozzles, though operating over a large range of altitudes and ambient pressures, are typically designed for one specific altitude. Above that altitude the nozzle flow is 'underexpanded' and below that altitude, the nozzle flow is 'overexpanded'. In both conditions the nozzle produces less than the maximum possible thrust at that altitude. Usually the nozzle design altitude is well above sea level, leaving the nozzle flow in an overexpanded state for its start up as well as for its ground testing where, if it is a reusable nozzle such as the Space Shuttle Main Engine (SSME), the nozzle will operate for the majority of its life. Overexpansion in a rocket nozzle presents the critical, and sometimes design driving, problem of flow separation induced side loads. To increase their understanding of nozzle side loads, engineers at MSFC began an investigation in 2000 into the phenomenon through a task entitled "Characterization and Accurate Modeling of Rocket Engine Nozzle Side Loads", led by A. Brown. The stated objective of this study was to develop a methodology to accurately predict the character and magnitude of nozzle side loads. The study included further hot-fire testing of the MC-l engine, cold flow testing of subscale nozzles, CFD analyses of both hot-fire and cold flow nozzle testing, and finite element (fe.) analysis of the MC-1 engine and cold flow tested nozzles. A follow on task included an effort to formulate a simplified methodology for modeling a side load during a two nodal diameter fluid/structure interaction for a single moment in time.

Smalley, Kurt B.↗

NASA NTRS1974

The Vortex Lattice Method for the Rotor-Vortex Interaction Problem

The rotor blade-vortex interaction problem and the resulting impulsive airloads which generate undesirable noise levels are discussed. A numerical lifting surface method to predict unsteady aerodynamic forces induced on a finite aspect ratio rectangular wing by a straight, free vortex placed at an arbitrary angle in a subsonic incompressible free stream is developed first. Using a rigid wake assumption, the wake vortices are assumed to move downsteam with the free steam velocity. Unsteady load distributions are obtained which compare favorably with the results of planar lifting surface theory. The vortex lattice method has been extended to a single bladed rotor operating at high advance ratios and encountering a free vortex from a fixed wing upstream of the rotor. The predicted unsteady load distributions on the model rotor blade are generally in agreement with the experimental results. This method has also been extended to full scale rotor flight cases in which vortex induced loads near the tip of a rotor blade were indicated. In both the model and the full scale rotor blade airload calculations a flat planar wake was assumed which is a good approximation at large advance ratios because the downwash is small in comparison to the free stream at large advance ratios. The large fluctuations in the measured airloads near the tip of the rotor blade on the advance side is predicted closely by the vortex lattice method.

Padakannaya, R.↗

DOE OSTI2023

Communication-Constrained Robust Control and Learning of Grid-Connected

The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Next Generation System Analysis Model: Recently Added Features and Future Plans

To better enable informed decision-making regarding the back-end of the nuclear fuel cycle, the Integrated Waste Management System (IWMS) program within the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) has been sponsoring the development and application of system analysis tools capable of analyzing various system options for the management of spent nuclear fuel (SNF) and high-level radioactive waste (HLW).With these tools, IWMS architecture analyses are being conducted to support the future deployment of a comprehensive nuclear waste management system that considers all major back-end aspects of the nuclear fuel cycle (i.e., transportation, storage, and disposal). The Next Generation System Analysis Model (NGSAM) is an agent-based simulation software tool expressly designed to be capable of modeling features within various IWMS architectures. NGSAM imports data from Oak Ridge National Laboratory (ORNL)’s unified database (e.g., historic assembly information, thermal profiles for assembly heat, and at-reactor dry storage loadings) to ensure that each simulation initializes with a realistic representation of the state of commercial SNF in the U.S. Recent major enhancements implemented into NGSAM in the period since NGSAM was last presented at the WM2019 conference include: • Tracking of railroad escort car acquisition and buffer car acquisition • The addition of heavy haul truck (HHT) and barge routes for some sites, as well as support for user-defined inter-modal routes • Updates to the logic that checks the transportation cask thermal limit maps prior to package transport • An allocation method that predicts when reactor sites would pack assemblies from their spent fuel pools for dry storage, and prioritizes shipments directly from the pools of those reactor sites in the preceding periods (before the predicted loadings to dry storage), thus reducing the number of casks loaded into dry storage at reactor sites • The addition of “reactor site family” operational limits to restrict the number of loads of SNF taken from the pool and from dry storage at a given reactor site each year • Added support for multiple canister loading map options and packages with multiple compatible transportation overpacks • Updates to the handling of non-commercial SNF, including a new database that contains data to support the updates • Updates to allow analysis of hypothetical scenarios which include repackaging at reactor sites, e.g., for possible comparative analysis with other scenarios • Implementation of additional output reports, or modification of existing ones • The ability to generate and implement user edits via the NGSAM website • The ability to model loading SNF from pool storage at an interim storage facility (ISF) into dry storage at the ISF • The ability to model consolidating SNF from different existing storage containers at a DOE site into the same DOE standard canister • The ability to model transferring SNF casks from one transportation mode to another, e.g., from HHT to rail, referred to as transloading. These new features have improved NGSAM capabilities and users’ experience with the model. Preliminary NGSAM requirements for modeling advanced reactor fuels, reprocessing, treatment, and conditioning were considered, and this paper describes them at a high level. Other nuclear fuel cycle system analysis tools developed under sponsorship of DOE-NE, like the VISION code developed at Idaho National Laboratory, might be better suited for initial high-level analysis of those technologies and advanced fuel cycles. As technologies are developed and system concepts evolve, NGSAM could provide value by providing more detailed modeling of transport, storage, and disposal of spent fuel and wastes from advanced reactors and advanced fuel cycles at the fuel element and waste container level.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2015

Ultrasonic Measurement and Monitoring of Loads in Bolts used in Structural Joints

The paper is an overview of work by the author in measuring and monitoring loads in bolts using an ultrasonic extensometer. A number of cases of bolted joints are covered. These include, a clamped joint with clearance fit between the bolt and hole, a clamped joint with the bolt in an interference fit with the hole, a flanged joint which allows the flange and bolt to bend; and a shear joint in a clevis and tang configuration. These applications were initially developed for measuring and monitoring preload in the NASA Space Shuttle Orbiter critical joints but are also applicable for monitoring loads in other critical bolted joints of structures such as transportation bridges and other aerospace structures. The paper explains how to set‐up a model to estimate the load factor and accuracy for the ultrasonic preload application in a clamped joint with clearance fit. The ultrasonic preload application for clamped joint with bolt in an interference fit can also be used to measure diametrical interference between the bolt shank and hole; and interference pressure on the bolt shank. Model and experimental data are given to demonstrate use of ultrasonic measurements in a shear joint. A bolt in a flanged joint experiences both tensile and bending loads. This application involves measurement of bending and tensile preload in a bolt. The ultrasonic beam bends due to the bending load on the bolt. A numerical technique to compute the trace of ultrasonic ray is presented.

Koshti, Ajay↗

DOE OSTI2024

Side-by-Side Comparison of Subhourly Clipping Models

Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to subhourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of these approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating the Allen and Walker correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons were performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The two models predict annual clipping loss more accurately than simple hourly power limit clipping, with the Allen method typically being slightly more accurate at typical ILR values and the Walker method often being slightly more accurate at high ILR values The models can improve accuracy over the status quo clipping approach up to 3 percentage points in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.

accuracy↗

DOE OSTI2024

Challenges in Rotor Aerodynamic Modeling for Non-Uniform Inflow Conditions

Within an international collaboration framework, the accuracy of rotor aerodynamic models used for design load calculations of wind turbines is being assessed. Where the use of high-fidelity computation fluid dynamics (CFD) and mid-fidelity free-vortex wake (FVW) models has become commonplace within the wind energy community, these still fail to meet the requirements in terms of execution time and computational cost needed for design load calculations. The fast but engineering fidelity blade-element/momentum (BEM) method can therefore still be considered the industry workhorse for design load simulations. At the same time, upscaling of wind turbine rotors makes inflow non-uniformities (e.g. shear, veer, turbulence) more important. The objective of this work is to assess model accuracy in non-uniform inflow conditions, which violate several BEM assumptions. Thereto a comparison in turbulent inflow has been executed including a wide variety of codes, focusing on the DanAero field measurements, where a 2.3-MW turbine was equipped with, among other sensors, a pressure measurement apparatus. The results indicate that, although average load patterns are in good agreement, this does not hold for the unsteady loads that drive fatigue damage and aero-elastic stability. A simplified comparison round in vertical shear was initiated to investigate the observed differences in a more controlled manner. A consistent offset in load amplitude was observed between CFD and free-vortex codes on the one hand and BEM-type codes on the other hand. To shed more light on the observations, dedicated efforts are ongoing to pinpoint the cause for these differences, in the end leading to guidelines for an improved BEM implementation.

17 WIND ENERGY↗

NASA NTRS2017

The Substorm Cycle as Reproduced by Global MHD Models

Recently, Gordeev et al. (2015) suggested a method to test global MHD models against statistical empirical data. They showed that four community-available global MHD models supported by the Community Coordinated Modeling Center (CCMC) produce a reasonable agreement with reality for those key parameters (the magnetospheric size, magnetic field, and pressure) that are directly related to the large-scale equilibria in the outer magnetosphere. Based on the same set of simulation runs, here we investigate how the models reproduce the global loading-unloading cycle. We found that in terms of global magnetic flux transport, three examined CCMC models display systematically different response to idealized2 h north then 2 h south interplanetary magnetic field (IMF) Bz variation. The LFM model shows a depressed return convection and high loading rate during the growth phase as well as enhanced return convection and high unloading rate during the expansion phase, with the amount of loaded unloaded magnetotail flux and the growth phase duration being the closest to their observed empirical values during isolated substorms. Two other models exhibit drastically different behavior. In the BATS-R-US model the plasma sheet convection shows a smooth transition to the steady convection regime after the IMF southward turning. In the Open GGCM a weak plasma sheet convection has comparable intensities during both the growth phase and the following slow unloading phase. We also demonstrate potential technical problem in the publicly available simulations which is related to post processing interpolation and could affect the accuracy of magnetic field tracing and of other related procedures.

Gordeev, E.↗

DOE OSTI2026

OC6 Phase Ia - Nonlinear hydrodynamic loading validation dataset

Two validation campaigns were examined within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) Phase 1 project to examine the modeling tools' underprediction of loads and motion of a floating wind semisubmersible (semi) at their surge and pitch natural frequencies. These campaigns were performed at the Maritime Research Institute Netherlands (MARIN) in 2017 and 2018. The load cases (LC) considered include: LC1 – Load measurements across semi under current loading; LC2 - Load measurements across semi under forced surge oscillation; LC3 – Load measurements across semi under wave loading, while held fixed; LC4 – Free-decay motion measurements in surge, pitch, and heave; and LC5 – Motion measurements under wave loading. Details on the results from the OC6 Phase Ia project can be found in the reference, “OC6 Phase 1: Investigating the underprediction of low-frequency hydrodynamic loads and responses of floating wind turbines”, J Phys: Conf Series 1618 032033.

17 WIND ENERGY↗

DOE OSTI2020

Thermodynamic Consistent Neural Networks for Learning Material Interfacial Mechanics

For multilayer materials in thin substrate systems, interfacial failure is one of the most challenges. The traction-separation relations (TSR) quantitatively describe the mechanical behavior of a material interface undergoing openings, which is critical to understand and predict interfacial failures under complex loadings. However, existing theoretical models have limitations on enough complexity and flexibility to well learn the real-world TSR from experimental observations. A neural network can fit well along with the loading paths but often fails to obey the laws of physics, due to a lack of experimental data and understanding of the hidden physical mechanism. In this paper, we propose a thermodynamic consistent neural network (TCNN) approach to build a data-driven model of the TSR with sparse experimental data. The TCNN leverages recent advances in physics-informed neural networks (PINN) that encode prior physical information into the loss function and efficiently train the neural networks using automatic differentiation. We investigate three thermodynamic consistent principles, i.e., positive energy dissipation, steepest energy dissipation gradient, and energy conservative loading path. All of them are mathematically formulated and embedded into a neural network model with a novel defined loss function. A real-world experiment demonstrates the superior performance of TCNN, and we find that TCNN provides an accurate prediction of the whole TSR surface and significantly reduces the violated prediction against the laws of physics.

Zhang, Jiaxin↗

DOE OSTI2021

Pipeline Structural Stability Under Nuclear Blast Pressure Loading

This report documents a set of simplified models to predict pipeline collapse under nuclear pressure loading. After a review of pipeline design literature, a set of simple expressions have been selected to represent an approximation of the threshold pressure for failure from cross- sectional yielding, cross-section buckling, and longitudinal buckling. These expressions provide a first-order approximation on load levels needed to achieve collapse. As a demonstration, the collapse pressure for a set of representative pipelines are calculated. Estimated pressure fields are also computed for a set of nuclear detonations, providing estimates of the ground range limit for pipeline collapse.

42 ENGINEERING↗