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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 1,261 records · Page 70

Space Launch System Core Stage Green Run Base Heating: Anomaly, Mitigation and Flight Redesign

The NASA Space Launch System (SLS) vehicle is composed of four RS-25 liquid oxygen and hydrogen rocket engines in the Core Stage (CS). The SLS Core Stage went through Green Run hot-fire testing at NASA Stennis Space Center’s B-2 test facility in 2021. The main goal of this testing was to confirm Core Stage tanking, propulsion and thrust vector control systems operations and performance to verify with predicted models. Two hot-fire (HF) test sequences were performed with the first one (HF1) in January for a test duration of 70 seconds and the second (HF2) testing completed in March for a test duration of 500 seconds. This paper focuses on the base heating anomalies observed during HF1 and HF2 where an extensive fire was observed along the Core Stage base heat shield during test operations. This environment was not anticipated and led to extensive unplanned damage to the thermal protection system which was augmented for flight. Green Run observations also led to a reassessment of flight environments for Artemis I. This paper discusses the potential cause of the anomalies, the flow physics, the reconstructed base environments, and mitigation plans for HF2 and flight.

aerothermodynamics↗

Space Launch System Core Stage Green Run Base Heating: Anomaly, Mitigation and Flight Redesign

The NASA Space Launch System (SLS) vehicle is composed of four RS-25 liquid oxygen and hydrogen rocket engines in the Core Stage (CS). The SLS Core Stage went through Green Run hotfire testing at NASA Stennis Space Center’s B-2 test facility in 2021. The main goal of this testing was to confirm Core Stage tanking, propulsion and thrust vector control systems operations and performance to verify with predicted models. Two hot-fire (HF) test sequences were performed with the first one (HF1) in January for a test duration of 70 seconds and the second (HF2) testing completed in March for a test duration of 500 seconds. This paper focuses on the base heating anomalies observed during HF1 and HF2 where an extensive fire was observed along the Core Stage base heat shield during test operations. This environment was not anticipated and led to extensive unplanned damage to the thermal protection system which was augmented for flight. Green Run observations also led to a reassessment of flight environments for Artemis I. This paper discusses the potential cause of the anomalies, the flow physics, the reconstructed base environments, and mitigation plans for HF2 and flight.

aerothermodynamics↗

Marin County Wildfires Ii: Improving Fire Suppression Modeling to Inform Fire Prevention and Suppression Decisions in Marin County, Ca

A future of increased wildfires requires greater integration of spatial analysis and local knowledge of emergency responders. We examine the application of a Potential Operational Delineations (PODs) framework for strategic pre-fire planning in Marin County. PODs are spatial units for wildfire management that combine predictive modeling and local firefighter expertise to identify potential control locations as unit boundaries and assess the difficulty of suppression within units. Additionally, this project explores the integration of road networks and social vulnerability to assess environmental justice in evacuation safety. This project constitutes a novel application of the PODs framework as it integrates expertise from Marin County senior firefighters with a Fireline Location Model (FLM) to achieve POD definition and uses a Suppression Difficulty Score (SDS) to rank each POD. The FLM uses network analysis and hydrologic modeling to identify key roads and ridgelines as boundaries and combines them with expert knowledge, in the form of workshops, to construct PODs. Once identified, PODs are classified using SDS, which includes processed inputs such as LiDAR-derived aboveground biomass, ECOSTRESS Evaporative Stress Index, land use cover type from Sentinel-2 Imagery, and a digital elevation model. Environmental justice for evacuation safety incorporated three key road metrics such as connectivity, travel area, and exit capacity, the Social Vulnerability Index from the Center for Disease Control, and cell coverage to determine a final Evacuation Difficulty Score. Results indicate a strong link between road networks as primary POD boundaries, with ridgelines and waterways as secondary and tertiary locations. Specifically, we find 78.5% of expertise-identified POD boundaries align with FLM-determined boundaries. More validation is needed to support this process; however, initial results signal a feasible framework to integrate expertise and spatial analysis in local level strategic fire planning

Wildfire modeling↗

LOWERING THE LEVELIZED COST OF ELECTRICITY OF A CONCENTRATING SOLAR POWER TOWER WITH A SUPERCRITICAL CARBON DIOXIDE POWER CYCLE

In order to maintain viability as a future power-generating technology, concentrating solar power (CSP) must reduce its levelized cost of electricity (LCOE). The cost of CSP is assessed with the System Advisor Model (SAM) from the National Renewable Energy Laboratory (NREL). The performance of an integrally geared compressor-expander recuperated recompression cycle with supercritical carbon dioxide (sCO2) as the working fluid is modeled. A comparison of the cycle model to the integrated SAM cycle performance is made. The cycle model incorporates innovative cycle control methods to improve the range of efficiency, including inventory control. The SAM model is modified to accommodate the predicted cycle performance. The ultimate goal of minimizing the LCOE is targeted through multiple approaches, including the cost of the power block, the impact of system scale, the sizing of the thermal system relative to the power block system, the operating approach for changes in ambient temperature and availability of sunlight. Through reduced power block cost and a detailed cycle model, the LCOE is modeled to be 5.98 ¢/kWh, achieving targeted techno-economic performance. The LCOE of the CSP system is compared to the cost of hybrid solar and fossil-fired systems. An analysis is made on the efficacy of a fossil backup system with CSP and how that relates to potential future costs of carbon dioxide emissions

schmitt, josh↗

Design, Optimization, and Control of Floating Offshore Wind Farms for Optimal Energy Production (Final report)

The uncertainty and irregularity of ocean waves and the ocean environment is a major factor in the development of commercial scale floating wind turbines as the operation of floating structures in such an environment can lead to irregular and unpredictable loading, fatigue, and ultimately a reduction in the operational life of the turbine system which affects energy production over the lifetime of the turbine. Control solutions that can limit float motions and mitigate stressful events on the structure become essential for extending lifetime and limiting the operational uncertainty of a floating wind turbine. Digital twins are computational replicas of physical systems that operate in parallel with the operation of the physical system. Given advanced knowledge of a systems input, digital twins have the ability to predict the behavior of a system in advance, which can be valuable in the control of that system. In this project, we developed and assessed potential digital twin models developed in house and openly available (OpenFast) for use in the real time control of the six degree of freedom response motions of a floating wind turbine in ocean waves. Coupling these models with near-field real time irregular sea surface (wve) measurement/sensings and prediction models, we used the digital twin to predict how the floating turbine will respond to the incoming waves. Applying this information to a motion control system of the float, one can limit and control float motions to prevent undesirable loading events/large angular motions, thus increasing system life and ultimately contributing to optimizing energy production. Due to the computational intensity of operating a digital twin in real time, we investigated the use of artificial intelligence techniques to speed-up the processes of the digital twin, as well as the wave reconstruction/prediction models. Model tank testing at the University of Rhode Island and University of Maine both validated and demonstrated the developed techniques on simple float geometries and a scale model of the NREL 15 MW reference turbine.

17 WIND ENERGY↗

Data-Driven Voltage Regulation of Distribution Grid Using Nonlinear Autoregressive Model with Exogenous Inputs (NARX)

This article proposes data-driven control via a nonlinear autoregressive model with exogenous inputs (NARX) for real-time voltage regulation of a modified feeder using reactive power sources. Traditional voltage control strategies rely on rule-based heuristics or optimization techniques, which often require detailed system models and extensive computational resources. The NARX-based controller learns system dynamics from historical data and predicts optimal reactive power dispatch in real-time for voltage correction. The proposed approach is evaluated on a power system feeder model under varying load and network conditions. Simulation results demonstrate that the NARX-based controller achieves improved voltage regulation, offering higher adaptability to system fluctuations. This study highlights the potential of data-driven control for enhancing the reliability of power distribution networks.

Donge, Vrushabh [ORNL] (ORCID:0000000306062803)↗

Chill Down Process of Hydrogen Transport Pipelines

A pseudo-steady model has been developed to predict the chilldown history of pipe wall temperature in the horizontal transport pipeline for cryogenic fluids. A new film boiling heat transfer model is developed by incorporating the stratified flow structure for cryogenic chilldown. A modified nucleate boiling heat transfer correlation for cryogenic chilldown process inside a horizontal pipe is proposed. The efficacy of the correlations is assessed by comparing the model predictions with measured values of wall temperature in several azimuthal positions in a well controlled experiment by Chung et al. (2004). The computed pipe wall temperature histories match well with the measured results. The present model captures important features of thermal interaction between the pipe wall and the cryogenic fluid, provides a simple and robust platform for predicting pipe wall chilldown history in long horizontal pipe at relatively low computational cost, and builds a foundation to incorporate the two-phase hydrodynamic interaction in the chilldown process.

Mei, Renwei↗

Effects of plasma squareness on RMP response in MAST-U

The effect of the squareness of the plasma boundary shape on the plasma response to the applied n = 2 (n is the toroidal mode number) resonant magnetic perturbation, and consequently on controlling the edge-localized mode (ELM) in MAST-U in the double-null configuration, is numerically systematically investigated. The modeling is performed utilizing three different plasma response models: the single-fluid model, the two-fluid model and the magnetohydrodynamic-kinetic hybrid model. The effect of the plasma squareness on ELM control is found to depend on the equilbrium kinetic profiles. Fixing the equilibrium radial profiles to that from a recent MAST-U discharge, the experimental plasma shape is found to be close to optimal for ELM control in terms of squareness. The optimal coil phasing does not significantly vary with varying plasma squareness. These findings robustly hold with (i) two figures of merit (FoMs) defined for predicting the ELM control feasibility, and (ii) three plasma response models employed for evaluating these FoMs.

MAST-U↗

Ignition of THKP and TKP Pyrotechnic Powders: Incorporating Reactive Chemical Processes into Predictive Models

We have conducted Simultaneous Thermogravimetric Modulated Beam Mass Spectrometry (STMBMS) experiments on igniter/actuator pyrotechnic powders to characterize the reactive processes controlling the ignition and combustion behavior of these materials. The experiments showed a complex, interactive reaction manifold involving over ten reaction pathways. A reduced dimensionality reaction manifold was developed from the detailed 10-step manifold and is being incorporated into existing predictive modeling codes to simulate the performance of pyrotechnic powders for NW component development. The results from development of the detailed reaction manifold and reduced manifold are presented. The reduced reaction manifold has been successfully used by SNL/NM modelers to predict thermal ignition events in small-scale testing, validating our approach and improving the capability of predictive models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prediction of Weather Impacts on Airport Arrival Meter Fix Capacity

This paper introduces a data driven model for predicting airport arrival capacity with a look-ahead time 2-8 hour forecast. The model is suitable for air traffic flow management by explicitly investigating the impact of convective weather on airport arrival meter fix throughput. Estimation of the arrival airport capacity under arrival meter fix flow constraints due to severe weather is an important part of Air Traffic Management (ATM). Airport arrival capacity can be reduced if one or more airport arrival meter fixes are partially or completely blocked by convective weather. When the predicted airport arrival demands exceed the predicted available airport's arrival capacity for a sustained period, Ground Delay Program (GDP) operations will be triggered by ATM system. Serious imbalances between demand and capacity occur most frequently when the airport capacity is severely degraded due to either bad airport terminal surface weather or inclement convective weather around airport arrival fixes. A model that predicts the weather-impacted airport arrival meter fix throughput may help ATM personnel to plan GDP operations more efficiently. This paper identifies the characteristics of air traffic flow across arrival meter fixes at Newark Liberty International Airport (EWR). The proposed approach, based on machine-learning methods, is developed to predict the weather impacted EWR arrival Meter Fix (MF) throughput. Sector forecast coverage is used to envision the weather impact on airport arrival MF flow, and the validation is accomplished by using Convective Weather Avoidance Model (CWAM) 0.5 to 2-hour and Collaborative Convective Forecast Product (CCFP) 4 to 8-hour look-ahead forecast data for the period of April-September in 2014. Furthermore, the regression tree ensemble learning of random forests approach for translating a sector forecast coverage model to an EWR arrival meter fix throughput model is examined. The results suggest that ATM decision makers in charge of MF flow control and GDP planning may benefit from adopting the airport arrival meter capacity prediction models to estimate the inclement weather impacts.

Wang, Yao X.↗

Transient Simulation of the Multi-SERTTA Experiment with MAMMOTH

This work details the MAMMOTH reactor physics simulations of the Static Environment Rodlet Transient Test Apparatus (SERTTA) conducted at Idaho National Laboratory in FY-2017. TREAT static-environment experiment vehicles are being developed to enable transient testing of Pressurized Water Reactor (PWR) type fuel specimens, including fuel concepts with enhanced accident tolerance (Accident Tolerant Fuels, ATF). The MAMMOTH simulations include point reactor kinetics as well as spatial dynamics for a temperature-limited transient. The strongly coupled multi-physics solutions of the neutron flux and temperature fields are second order accurate both in the spatial and temporal domains. MAMMOTH produces pellet stack powers that are within 1.5% of the Monte Carlo reference solutions. Some discrepancies between the MCNP model used in the design of the flux collars and the Serpent/MAMMOTH models lead to higher power and energy deposition values in Multi-SERTTA unit 1. The TREAT core results compare well with the safety case computed with point reactor kinetics in RELAP5-3D. The reactor period is 44 msec, which corresponds to a reactivity insertion of 2.685% delta k/k$. The peak core power in the spatial dynamics simulation is 431 MW, which the point kinetics model over-predicts by 12%. The pulse width at half the maximum power is 0.177 sec. Subtle transient effects are apparent at the beginning insertion in the experimental samples due to the control rod removal. Additional difference due to transient effects are observed in the sample powers and enthalpy. The time dependence of the power coupling factor (PCF) is calculated for the various fuel stacks of the Multi-SERTTA vehicle. Sample temperatures in excess of 3100 K, the melting point UO$_2$, are computed with the adiabatic heat transfer model. The planned shaped-transient might introduce additional effects that cannot be predicted with PRK models. Future modeling will be focused on the shaped-transient by improving the control rod models in MAMMOTH and adding the BISON thermo-elastic models and thermal-fluids heat transfer.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks

NASA Langley Research Center, Hampton, VA 23681 Under a joint research and development effort conducted by the National Aeronautics and Space Administration and The Boeing Company (formerly McDonnell Douglas) three neural-network based control systems were developed and tested. The control systems were experimentally evaluated using a transonic wind-tunnel model in the Langley Transonic Dynamics Tunnel. One system used a neural network to schedule flutter suppression control laws, another employed a neural network in a predictive control scheme, and the third employed a neural network in an inverse model control scheme. All three of these control schemes successfully suppressed flutter to or near the limits of the testing apparatus, and represent the first experimental applications of neural networks to flutter suppression. This paper will summarize the findings of this project.

Scott, Robert C.↗

IMPACTS OF SMALL COLUMN ION EXCHANGE STREAMS ON DWPF GLASS FORMULATION KT07-SERIES GLASS COMPOSITIONS

This report is the third in a series of studies of the impacts of the addition of Crystalline Silicotitanate (CST) and Monosodium Titanate (MST) from the Small Column Ion Exchange (SCIX) process on the Defense Waste Processing Facility (DWPF) glass waste form and the applicability of the DWPF process control models. MST from the Salt Waste Processing Facility is also considered in the study. The KT07-series glasses were selected to evaluate any potential impacts of noble metals on their properties and performance. The glasses characterized thus far for the SCIX study have not included noble metals since they are not typically tracked in sludge batch composition projections. However, noble metals can act as nucleation sites in glass melts, leading to enhanced crystallization. This crystallization can potentially influence the properties and performance of the glass, such as chemical durability, viscosity, and liquidus temperature. The noble metals Ag, Pd, Rh, and Ru were added to the KT07-series glasses in concentrations based on recent measurements of Sludge Batch 6, which was considered to contain a high concentration of noble metals. The KT04-series glasses were used as the baseline compositions. After fabrication, the glasses were characterized to determine their homogeneity, chemical composition, durability, and viscosity. Liquidus temperature measurements are also underway but were not complete at the time of this report. The liquidus temperature results for the KT07-series glasses, along with several of the earlier glasses in the SCIX study, will be documented separately. All of the KT07-series glasses, both quenched and slowly cooled, were found to be amorphous by X-ray diffraction. Chemical composition measurements showed that all of the glasses met their targeted compositions. The Product Consistency Test (PCT) results showed that all of the glasses had chemical durabilities that were far better than that of the Environmental Assessment benchmark glass. The measured PCT responses were well predicted by the current DWPF Product Composition Control System (PCCS) durability models. The measured viscosity values for each KT07-series glass were acceptable for DWPF processing and were well predicted by the current PCCS model. Overall, the results show that the inclusion of relatively high concentrations of noble metals (in terms of expected values for a DWPF sludge batch) had no significant impact on the properties and performance of these glass compositions. There were no significant differences in the measured properties when compared to those of the KT04-series glasses, which did not contain noble metals. Liquidus temperature measurements are still underway and there may be an impact of the noble metals on those measurements. However, no adverse effects were noted in terms of crystallization after slow cooling. At the completion of these studies, all of the data generated will be reviewed with regard to the applicability of the DWPF PCCS models and recommendations will be made as to whether the validation ranges of the current models can be extended, or whether some or all of the models need to be refit to allow for the incorporation of the SCIX streams. As changes are made to the projected sludge compositions and the volume of the SCIX material, additional evaluations should be performed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Object-oriented model-driven control

A monitoring and control subsystem architecture has been developed that capitalizes on the use of modeldriven monitoring and predictive control, knowledge-based data representation, and artificial reasoning in an operator support mode. We have developed an object-oriented model of a Controlled Ecological Life Support System (CELSS). The model based on the NASA Kennedy Space Center CELSS breadboard data, tracks carbon, hydrogen, and oxygen, carbodioxide, and water. It estimates and tracks resorce-related parameters such as mass, energy, and manpower measurements such as growing area required for balance. We are developing an interface with the breadboard systems that is compatible with artificial reasoning. Initial work is being done on use of expert systems and user interface development. This paper presents an approach to defining universally applicable CELSS monitor and control issues, and implementing appropriate monitor and control capability for a particular instance: the KSC CELSS Breadboard Facility.

Drysdale, A.↗

Numerical Investigation of Microgravity Tank Pressure Rise Due to Boiling

The ability to control self-pressurization in cryogenic storage tanks is essential for NASAs long-term space exploration missions. Predictions of the tank pressure rise in Space are needed in order to inform the microgravity design and optimization process. Due to the fact that natural convection is very weak in microgravity, heat leaks into the tank can create superheated regions in the liquid. The superheated regions can instigate microgravity boiling, giving rise to pressure spikes during self-pressurization. In this work, a CFD model is developed to predict the magnitude and duration of the microgravity pressure spikes. The model uses the Schrage equation to calculate the mass transfer, with a different accommodation coefficient for evaporation at the interface, condensation at the interface, and boiling in the bulk liquid. The implicit VOF model was used to account for the moving interface, with bounded second order time discretization. Validation of the models predictions was carried out using microgravity data from the Tank Pressure Control Experiment, which flew aboard the Space Shuttle Mission STS-52. Although this experiment was meant to study pressurization and pressure control, it underwent boiling during several tests. The pressure rise predicted by the CFD model compared well with the experimental data. The ZBOT microgravity experiment is scheduled to fly on February 2016 aboard the ISS. The CFD model was also used to perform simulations for setting parametric limits for the Zero-Boil-Off Tank (ZBOT) Experiments Test Matrix in an attempt to avoid boiling in the majority of the test runs that are aimed to study pressure increase rates during self-pressurization. *Supported in part by NASA ISS Physical Sciences Research Program, NASA HQ, USA

pressure rise↗

TU-F-17A-03: An Analytical Respiratory Perturbation Model for Lung Motion Prediction

Purpose: Breathing irregularity is common, causing unreliable prediction in tumor motion for correlation-based surrogates. Both tidal volume (TV) and breathing pattern (BP=ΔVthorax/TV, where TV=ΔVthorax+ΔVabdomen) affect lung motion in anterior-posterior and superior-inferior directions. We developed a novel respiratory motion perturbation (RMP) model in analytical form to account for changes in TV and BP in motion prediction from simulation to treatment. Methods: The RMP model is an analytical function of patient-specific anatomic and physiologic parameters. It contains a base-motion trajectory d(x,y,z) derived from a 4-dimensional computed tomography (4DCT) at simulation and a perturbation term Δd(ΔTV,ΔBP) accounting for deviation at treatment from simulation. The perturbation is dependent on tumor-specific location and patient-specific anatomy. Eleven patients with simulation and treatment 4DCT images were used to assess the RMP method in motion prediction from 4DCT1 to 4DCT2, and vice versa. For each patient, ten motion trajectories of corresponding points in the lower lobes were measured in both 4DCTs: one served as the base-motion trajectory and the other as the ground truth for comparison. In total, 220 motion trajectory predictions were assessed. The motion discrepancy between two 4DCTs for each patient served as a control. An established 5D motion model was used for comparison. Results: The average absolute error of RMP model prediction in superior-inferior direction is 1.6±1.8 mm, similar to 1.7±1.6 mm from the 5D model (p=0.98). Some uncertainty is associated with limited spatial resolution (2.5mm slice thickness) and temporal resolution (10-phases). Non-corrected motion discrepancy between two 4DCTs is 2.6±2.7mm, with the maximum of ±20mm, and correction is necessary (p=0.01). Conclusion: The analytical motion model predicts lung motion with accuracy similar to the 5D model. The analytical model is based on physical relationships, requires no training, and therefore is potentially more resilient to breathing irregularities. On-going investigation introduces airflow into the RMP model for improvement. This research is in part supported by NIH (U54CA137788/132378). AY would like to thank MSKCC summer medical student research program supported by National Cancer Institute and hosted by Department of Medical Physics at MSKCC.

60 APPLIED LIFE SCIENCES↗

Results From F-18B Stability and Control Parameter Estimation Flight Tests at High Dynamic Pressures

A maximum-likelihood output-error parameter estimation technique has been used to obtain stability and control derivatives for the NASA F-18B Systems Research Aircraft. This work has been performed to support flight testing of the active aeroelastic wing (AAW) F-18A project. The goal of this research is to obtain baseline F-18 stability and control derivatives that will form the foundation of the aerodynamic model for the AAW aircraft configuration. Flight data have been obtained at Mach numbers between 0.85 and 1.30 and at dynamic pressures ranging between 600 and 1500 lbf/sq ft. At each test condition, longitudinal and lateral-directional doublets have been performed using an automated onboard excitation system. The doublet maneuver consists of a series of single-surface inputs so that individual control-surface motions cannot be correlated with other control-surface motions. Flight test results have shown that several stability and control derivatives are significantly different than prescribed by the F-18B aerodynamic model. This report defines the parameter estimation technique used, presents stability and control derivative results, compares the results with predictions based on the current F-18B aerodynamic model, and shows improvements to the nonlinear simulation using updated derivatives from this research.

Moes, Timothy R.↗

Impact of resonant magnetic perturbations on nonlinearly driven modes in drift-wave turbulence

In this work, we study the effects of resonant magnetic perturbations (RMPs) on turbulence, flows, and confinement in the framework of resistive drift wave turbulence. We extend the Hasegawa-Wakatani model to include RMP fields. The effect of the RMPs is to induce a linear coupling between the zonal electric field and the zonal density gradient, which drives the system to a state of electron radial force balance for large ({delta}B{sub r}/B{sub 0}). Both the vorticity flux (Reynolds stress) and particle flux are modulated. We derive an extended predator prey model which couples zonal potential and density dynamics to the evolution of turbulence intensity. This model has both turbulence drive and RMP amplitude as control parameters and predicts a novel type of transport bifurcation in the presence of RMPs. We find states that are similar to the ZF-dominated state of the standard predator-prey model, but for which the power threshold is now a function of the RMP strength. For small RMP amplitude, the energy of zonal flows decreases and the turbulence energy increases with ({delta}B{sub r}/B{sub 0}), corresponding to a damping of zonal flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗