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At least 703 records · Page 39

Thermomechanical Real-Time Hybrid Simulation: Conceptual Framework and Control Requirements

Real-time hybrid simulation (RTHS) is an enabling technology that has transformed engineering experimentation and helped researchers expand modeling capabilities. However, breakthroughs are necessary to expand the range of hybrid simulation methods and, thus, enable experiments with loading conditions representing multiple hazards. This paper discusses the development of a new thermomechanical RTHS framework and a systematic approach to determining RTHS control requirements. First, the framework is established using a representative finite element model of a layered structural system subjected to thermal loading. A complete two-layer system model serves as the reference system, and it is then partitioned into a numerical layer and an experimental layer that share interface conditions. Next, a thermal actuator is introduced to impose dynamic thermal loading on the experimental subsystem, serving as a transfer system. Finally, control and performance metrics are defined to evaluate the realization of interface boundary conditions and map this to the RTHS execution. Through an illustrative example considering the influence of temperature on a lunar habitat, we demonstrate how to establish controller requirements for RTHS and demonstrate that this approach can be used to conduct RTHS on structures with thermomechanical loading.

Herta Montoya↗

Numerical modeling of multidimensional flow in seals and bearings used in rotating machinery

The rotordynamic behavior of turbomachinery is critically dependent on fluid dynamic rotor forces developed by various types of seals and bearings. The occurrence of self-excited vibrations often depends on the rotor speed and load. Misalignment and rotor wobbling motion associated with differential clearance were often attributed to stability problems. In general, the rotative character of the flowfield is a complex three dimensional system with secondary flow patterns that significantly alter the average fluid circumferential velocity. A multidimensional, nonorthogonal, body-fitted-grid fluid flow model is presented that describes the fluid dynamic forces and the secondary flow pattern development in seals and bearings. Several numerical experiments were carried out to demonstrate the characteristics of this complex flowfield. Analyses were performed by solving a conservation form of the three dimensional Navier-Stokes equations transformed to those for a rotating observer and using the general-purpose computer code PHOENICS with the assumptions that the rotor orbit is circular and that static eccentricity is zero. These assumptions have enabled a precise steady-state analysis to be used. Fluid injection from ports near the seal or bearing center increased fluid-film direct dynamic stiffness and, in some cases, significantly increased quadrature dynamic stiffness. Injection angle and velocity could be used for active rotordynamic control; for example, injection, when compared with no injection, increased direct dynamic stiffness, which is an important factor for hydrostatic bearings.

Hendricks, R. C.↗

Correlation Results for a Mass Loaded Vehicle Panel Test Article Finite Element Models and Modal Survey Tests

High-fidelity Finite Element Models (FEMs) were developed to support a recent test program at Marshall Space Flight Center (MSFC). The FEMs correspond to test articles used for a series of acoustic tests. Modal survey tests were used to validate the FEMs for five acoustic tests (a bare panel and four different mass-loaded panel configurations). An additional modal survey test was performed on the empty test fixture (orthogrid panel mounting fixture, between the reverb and anechoic chambers). Modal survey tests were used to test-validate the dynamic characteristics of FEMs used for acoustic test excitation. Modal survey testing and subsequent model correlation has validated the natural frequencies and mode shapes of the FEMs. The modal survey test results provide a basis for the analysis models used for acoustic loading response test and analysis comparisons

Maasha, Rumaasha↗

Validation of a Two-Phase CFD Model for Predicting Tank Self-Pressurization in the Ground-Based K-Site Experiment

A two-phase CFD model for self-pressurization of a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for modeling two-phase flow, as well as interfacial heat, mass and momentum transfer between the liquid and the vapor regions. The CFD model is validated against self-pressurization experiment performed using the K-site flightweight hydrogen storage tank at NASA Glenn Research Center1. Laminar and turbulent simulations are performed together with conjugated heat transfer analysis. Effects of turbulence, the value of accommodation coefficient used for predicting phase change rates, as well as tank wall geometry are presented and discussed. Predicted tank pressures, fluid and wall temperatures are compared with the experimental data at 49% fill level and two different heat loads for validating this CFD model.

Computational Fluid Dynamics↗

Validation of a Two-Phase CFD Model for Predicting Tank Self-Pressurization in the Ground-Based K-Site Experiment

A two-phase CFD model for self-pressurization of a cryogenic storage tank partially filled with liquid hydrogen is presented using the Volume-Of-Fluid approach for modeling two-phase flow, as well as interfacial heat, mass and momentum transfer between the liquid and vapor regions. The CFD model is validated against self-pressurization experiment performed using the K-site flightweight hydrogen storage tank at NASA Glenn Research Center 1 . Laminar and turbulent simulations are performed together with conjugate heat transfer analysis. Effects of turbulence, the value of accommodation coefficient used for predicting phase change rates, as well as tank wall geometry are presented and discussed. Predicted tank pressures, fluid and wall temperatures are compared with the experimental data at 49% fill level and two different heat loads for validating this CFD model.

Computational Fluid Dynamics↗

Probability Bounds Analysis Applied to Multi-Purpose Crew Vehicle Nonlinearity

The Multi-Purpose Crew Vehicle (MPCV) Program Orion vehicle finite element model (FEM) was updated based on a modal test performed by Lockheed Martin. Due to nonlinearity observed in the test results, linear low force level (LL) and high force level (HL) FEMs were developed for use during various Space Launch System (SLS) flight regimes depending on expected forcing levels. Uncertainty models were derived for the combined MPCV and MPCV Stage Adaptor LL and HL Hurty/Craig-Bampton (HCB) components based on the MPCV structural test article Configuration 4 modal test-analysis correlation results. Subsequently, system-level uncertainty quantification analyses were performed using both models for various SLS flight configurations to determine the impact of the nonlinearity on important system metrics. The system metrics included both transfer functions associated with attitude control and dynamic loads associated with aerodynamic buffeting during ascent. In each case, an independent Monte Carlo (MC) analysis was performed, and no attempt was made to combine the results. The Hybrid Parametric Variation (HPV) method was used to develop the LL and HL MPCV HCB uncertainty models. The HPV method provides both parametric and non-parametric components of uncertainty. The non-parametric uncertainty accounts for the difference in model-form between the linearized analytical model and the corresponding linearized component test results in the form of mode shapes and frequencies at that force level. This linear model-form uncertainty is implemented in the HPV method using random matrix theory. However, the HPV uncertainty models developed for the linear LL and HL MPCV components do not account for the nonlinearity in the MPCV. With respect to the linearized models, this nonlinearity is also an uncertainty in model form, but in this case, it must be treated independently as an epistemic uncertainty. It represents a lack of knowledge, in contrast to an aleatory uncertainty due to the randomness of a variable. In the case of an epistemic variable, the true value is unknown, only the interval within which it lies is known. Epistemic uncertainty can be reduced with increased knowledge, while in general, aleatory uncertainty cannot. This work combines the epistemic uncertainty due to the MPCV nonlinearity with the parametric and non-parametric uncertainty within the HPV method using a second order propagation approach. The LL and HL test data is augmented with surrogate test data derived from a nonlinear MPCV representation. The impact of the MPCV nonlinearity on system response statistics is determined using a series of cumulative distribution functions in the form of a horsetail plot, or p-box. This results in an interval of probabilities for a specific response value, or an interval of response values at a specific probability.

Daniel C Kammer↗

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗

Impact of Open Communication Networks on Load Frequency Control with Plug-In Electric Vehicles by Cyber-Physical Dynamic Co-Simulation

With the increasing electrification of the transportation sector to achieve the carbon neutrality objective, despite the challenges of charging electric vehicles (EV), there are also opportunities through smart charging EVs to improve system frequency stability; however, EV control technologies might require nontraditional communication support. This paper investigates the impacts of communication variations of EV on power system load frequency control through a cyber-physical dynamic system (CPDS) co-simulation. Here, the CPDS is built upon our previously developed transmission-and-distribution dynamic co-simulation model with the added communication variation functions (i.e., delay and packet loss). The case studies consider multiple communication variation scenarios when the system experiences an N-1 generation trip contingency. The scenarios include communication delays and packet loss using both homogeneous and heterogeneous assumptions. The outcomes of this work can help improve EV frequency regulation services and provide robust and effective tests for different load frequency control algorithms of the future power systems.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Uncertainty Due to Unsteady Fluid/Structure Interaction for the Ares I Vehicle Traversing the Transonic Regime

Rapid reduced-order numerical models are being investigated as candidates to simulate the dynamics of a flexible launch vehicle during atmospheric ascent. There has also been the extension of these new approaches to include gust response. These methods are used to perform aeroelastic and gust response analyses at isolated Mach numbers. Such models require a method to time march through a succession of ascent Mach numbers. An approach is presented for interpolating reduced-order models of the unsteady aerodynamics at successive Mach numbers. The transonic Mach number range is considered here since launch vehicles can suffer the highest dynamic loads through this range. Realistic simulations of the flexible vehicle behavior as it traverses this Mach number range are presented. The response of the vehicle due to gusts is computed. Uncertainties in root mean square and maximum bending moment and crew module accelerations are presented due to assumed probability distributions in design parameters, ascent flight conditions, gusts. The primary focus is on the uncertainty introduced by modeling fidelity. It is found that an unsteady reduced order model produces larger excursions in the root mean square loading and accelerations than does a quasi-steady reduced order model.

Bartels, Robert E.↗

Step-loaded creep testing of Zircaloy-4 cladding at higher temperatures in the α-phase

A refined understanding of zirconium-based cladding thermomechanical performance during rapid transients is essential for enhancing the safety and operation of light-water reactors. Traditional models for zirconium alloys under accident conditions generally assume that creep dominates fuel cladding performance. Here, these historic models have largely remained unchanged and serve as the basis for safety criteria development. As the U.S. nuclear industry pursues higher burnup levels, the increased release of fission gases during transients raises the risk of cladding failure in the low-temperature hcp α-phase, making the fidelity of these models of greater importance. Creep testing was conducted from 550–700°C with 25–120 MPa applied hoop stresses to investigate Zircaloy-4 deformation at accident-relevant temperatures in the α-phase. Step-loading was employed to capture creep behavior across a wide stress range from a single sample. The stress-strain rate data at higher temperatures (650 and 700°C) were well-described by isotropic versions of the Erbacher and Kaddour models, while the lower temperature data (550 and 600°C) were underpredicted by both anisotropic and isotropic model variants. Greater strain rates during the initial loading step at 650 and 700°C were attributed to recrystallization and grain growth of sub-micron crystallites. Yet, texture analysis revealed the basal split texture remained after testing. These observations produced results suggesting Zircaloy-4 claddings experience higher creep rates across the α-phase than previously thought, possibly related to dynamic anisotropy due to temperature dependent activation of deformation mechanisms, effects of biaxial loading, and variation in material condition between the current testing used in previous model development.

36 MATERIALS SCIENCE↗

Optimal operation of multi-plant steam district heating systems for enhanced efficiency and sustainability

Despite their crucial role in supplying heat and power to universities, industries, and healthcare facilities, many steam-based district heating systems rely on outdated control methods. Among these, multi-central plant districts are particularly challenging due to the complexities of coordinating multiple plants, optimizing load distributions, and managing system downtime. In response, new operational strategies are developed to enhance the efficiency and sustainability of steam districts while utilizing existing resources. These strategies include reducing plant operational pressure without compromising the reliable supply to buildings and optimizing load allocation across multiple plants. The load allocation considers boiler part-load efficiency, runtime, network losses, and building pressure set points, and is compared with traditional multi-boiler controls. To support this exploration, new dynamic Modelica models are developed. In addition, methods to reduce modeling complexities are incorporated, enhancing their suitability for practical applications. A holistic district-wide analysis using a real university case study demonstrates a 4.7% fuel savings by lowering boiler operational pressure from 900 kPa to 600 kPa, along with a 13.3% reduction in condensation losses across the distribution network. Furthermore, the load allocation approach results in a 13.1% reduction in fuel consumption during peak winter periods and 15.3% during shoulder periods, with corresponding decreases in carbon emissions and fuel costs. This approach can also save maintenance costs by reducing the boiler runtime by 49.6%. In conclusion, this research underscores the benefits of retrofitting aging steam district heating systems, offering immediate operational improvements by enhancing efficiency, meeting regulatory compliance, and extending infrastructure lifespans while delaying costly overhauls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Validation of Combined Analytical Methods to Predict Slip in Cylindrical Roller Bearings

This paper presents a combination of models that together calculate the cage and roller speeds of a cylindrical roller bearing. The models consider elastohydrodynamic lubrication and contact elasticity between the roller and raceway, roller centrifugal forces, hydrodynamic lubrication at the cage pocket, and frictional forces. Using these models, the predicted cage and roller speeds and the extent of slip are compared to measurements acquired on cylindrical roller bearings in a commercial gearbox in steady-state and transient operating conditions of a wind turbine. In steady-state conditions at low wind speeds and low lubricant temperatures, cage and roller slip up to 60% occur in the loaded zone of the bearing. In the unloaded zone, up to 80% roller slip occurs. Cage and roller slip then decrease as the lubricant temperature and wind speed increases. In general, the analytical model results match experimental measurements within 10% for lubricant temperatures above 40 degrees C and wind speeds over 10 meters per second. The analytical model is further evaluated during a transient start-up event and highly dynamic emergency stop event and also used to examine changes in the bearing design or lubricant properties. Furthermore, roller and cage slip in cylindrical bearings is a combined effect of the bearing design, applied load, shaft speed, and lubricant properties and temperature, and can be quickly evaluated with the combined analytical models.

17 WIND ENERGY↗

Google/Makani Energy Kite Modeling (CRADA CRD-18-00569 Final Report)

In support of Makani’s energy kite development program, Makani engaged with NREL to develop, verify, and document a multiphysics engineering model of a megawatt-scale tethered energy kite (named KiteFAST). After the original development of KiteFAST was completed, Makani further engaged NREL to develop a software enhancement of KiteFAST to enable the dynamics modeling of an energy kite tethered to a floating offshore platform (named KiteFAST-OS). Before this project, the capability to model the aero-hydro-servo-elastic dynamics of an airborne wind energy (AWE) system with electricity generation on the flying device (fly gen) and crosswind flight operation did not exist. Such physics-based modeling capability is needed for loads analysis, structural design, and certification of energy kites. Throughout the project, an exclusive license kept KiteFAST and KiteFAST-OS available only to Makani, NREL, and its counterparts. With the ending of Makani, the KiteFAST and KiteFAST-OS software were merged into a single code base (named KiteFAST), the exclusive license was terminated, and the source code, documentation, and example models were released publicly.

17 WIND ENERGY↗

Development of a Dynamic, End-to-End Free Piston Stirling Convertor Model

A dynamic model for a free-piston Stirling convertor is being developed at the NASA Glenn Research Center. The model is an end-to-end system model that includes the cycle thermodynamics, the dynamics, and electrical aspects of the system. The subsystems of interest are the heat source, the springs, the moving masses, the linear alternator, the controller, and the end-user load. The envisioned use of the model will be in evaluating how changes in a subsystem could affect the operation of the convertor. The model under development will speed the evaluation of improvements to a subsystem and aid in determining areas in which most significant improvements may be found. One of the first uses of the end-toend model will be in the development of controller architectures. Another related area is in evaluating changes to details in the linear alternator.

Regan, Timothy F.↗

Co-Simulation Model for Optimal Wind-Hydro Coordination Using Wind Farm Control Dynamics

The growing share of Variable Renewable Energy sources (VRES) in power systems presents challenges for regula- tors, grid operators and energy producers. The VRES’ operation has limited flexibility in their operations, as they are highly dependent on ambient environments. To address these challenges, decision-makers must consider multiple objectives, among these are revenue, power system services and mechanical load on wind turbines. Coordinated operation of power plants and different wind farm control strategies are examples of measures that can benefit these objectives. This study proposes a Multi-Objective Linear Programming (MOLP) model to simulate the optimum operation of wind and hydropower plants that share limited transmission capacity. Further, wind farm control dynamics are included to obtain realistic output power and accumulated damage. From this, a case study based on a relevant location in Norway is presented to analyze the improved effect of wind- hydro coordination and wind farm control in achieving the objectives of accumulated wind turbine damage and total revenue of the hybrid power system. In addition, the study considers the potential advantages of adding a variable-speed pump to the hydropower plant. The results demonstrate that by considering multiple objectives in the optimization, one may achieve better overall performance of the objectives. By utilizing the flexibility of hydro storage, the decision maker may adjust to obtain the most desired outcome. Moreover, the added flexibility of utilizing a pump for hydro storage shows great improvements for the combined revenue of the power plants and reduced curtailment of the wind farm. However, less impact is observed from using a variable speed pump compared to a fixed speed pump.

13 HYDRO ENERGY↗

A practical extension of the recursive multi-fidelity model for the emulation of hole closure experiments

We report in regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three-dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi-fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi-fidelity model to employ low-fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization.

36 MATERIALS SCIENCE↗

Modal Testing of a Flexible Wing on a Dynamically Active Test Fixture Using the Fixed Base Correction Method

In modal testing and finite element model correlation, analysts desire modal results using free-free or rigid boundary conditions to ease comparisons of test versus analytical data. It is often expensive both in cost and schedule to build and test with boundary conditions that replicate the free-free or rigid boundaries. Static test fixtures for load testing are often large, heavy, and unyielding, and not provide adequate boundaries for modal tests because they are dynamically too flexible and often contain natural frequencies within the test article frequency range of interest. The dynamic coupling between the test article and test fixture complicates the model updating process because significant effort needs to be spent on modeling the test fixture and boundary conditions in addition to the test article. If the modal results could be corrected for fixture coupling, then setups used for other structural testing could be adequate for modal testing and would allow significant schedule and cost savings by eliminating a unique setup for only modal testing. To simplify future modal tests, this report describes a Fixed Base Correction method that was investigated during modal testing of a full-scale, half-span, flexible wing cantilevered from a static test fixture. The results of this Fixed Base Correction approach look very promising. The method aided in producing similar wing modal characteristics for two different physical boundary configurations of a dynamically active test fixture.

Natalie D Spivey↗

Role of dislocations on martensitic transformation temperatures and microstructure: A molecular dynamics study

Microstructure and defects strongly affect martensitic transformations in metallic alloys. Significant progress has been made in understanding the atomic-level processes that control the role of grain boundaries and precipitates in these solid-to-solid phase transformations. Yet, the role of dislocations and their structures on martensitic transformation temperature and the resulting microstructure remains unclear. Therefore, we used large-scale molecular dynamics simulations to study the forward and reverse transformation of a martensitic material modeled after Ni63Al37 under cyclic thermal loading. The simulations reveal that dislocations in the austenite phase act as one-dimensional seeds for the martensite phase, which is present at temperatures significantly above the martensite start value. We find a reduction in the dislocation density during cyclic thermal loading, which results in the increase in martensite and austenite transition temperatures, in agreement with experiments. Importantly, we extracted a critical martensitic nuclei size for developing stable domains and found that relatively low dislocation densities are needed to grow independent martensitic variants resulting in a multi-domain structure.

Physics↗