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At least 271 records · Page 15

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DOE OSTI2024

Phase-Field Modeling of Thermally-Grown Oxide and the Induced Damage Evolution in Environmental Barrier Coatings

The advent of next-generation hydrogen-based engines necessitates materials capable of withstanding temperatures beyond the reach of current superalloys. SiC-based ceramic matrix composites, augmented with environmental barrier coatings (EBCs), present a promising materials solution. Given the active search for effective and durable EBCs, there is a pressing need for modeling tools to understand and predict damage evolution in these materials to help accelerate their development. This study introduces a phase-field model (PFM) designed to simulate the critical role of thermally grown oxides (TGO) in the degradation and failure of EBCs. The model accounts for the severe volume expansion due to oxidation, alongside phase transformations and microstructural evolution during thermal cycling, offering a comprehensive view of the damage processes. Simulation results are validated against experimental findings reported in the literature, establishing the model's potential as a significant tool for understanding and improving the resilience of EBCs in cyclic oxidative environments.

Cheng, Tianle↗

DOE OSTI2025

Phase Field Modeling of Chemical Reaction Related Damage Evolution in Environmental Barrier Coatings

The advent of next-generation engines necessitates materials capable of withstanding temperatures beyond the reach of current superalloys. SiC-based ceramic matrix composites, augmented with environmental barrier coatings (EBCs), present a promising materials solution. Given the active search for effective and durable EBCs, there is a pressing need for modeling tools to understand and predict damage evolution in these materials to help accelerate their development. This study introduces a phase-field model (PFM) designed to simulate the thermally grown oxides (TGO) and phase transformation in the degradation and failure of EBCs. The model accounts for the severe volume expansion due to oxidation, alongside phase transformations and porosity evolution during thermal cycling, offering a comprehensive view of the damage processes. Simulation results are validated against experimental findings reported in the literature, establishing the model's potential as a significant tool for understanding and improving the resilience of EBCs in cyclic oxidative environments.

fast-diffusion path↗

NASA NTRS1995

Probabilistic simulation of long term behavior in polymer matrix composites

A methodology to compute cumulative probability distribution functions (CDF) of fatigue life for different ratios, r of applied stress to the laminate strength based on first ply failure criteria has been developed and demonstrated. Degradation effects due to long term environmental exposure and mechanical cyclic loads are considered in the simulation process. A unified time-stress dependent multi-factor interaction equation model developed at NASA Lewis Research Center has been used to account for the degradation/aging of material properties due to cyclic loads. Fast probability integration method is used to perform probabilistic simulation of uncertainties. Sensitivity of fatigue life reliability to uncertainties in the primitive random variables are computed and their significance in the reliability based design for maximum life is discussed. The results show that the graphite/epoxy (0/+45/90) deg laminate with ply thickness 0.125 in. has 500,000 cycles life for applied stress to laminate strength ratio of 0.6 and a reliability of 0.999. Also, the fatigue life reliability has been found to be most sensitive to the ply thickness and matrix tensile strength. Tighter quality controls must therefore be enforced on ply thickness and matrix strength in order to achieve high reliability of the structure.

Shah, A. R.↗

NASA NTRS1998

Performance Testing of a Trace Contaminant Control Subassembly for the International Space Station

As part of the International Space Station (ISS) Trace Contaminant Control Subassembly (TCCS) development, a performance test has been conducted to provide reference data for flight verification analyses. This test, which used the U.S. Habitation Module (U.S. Hab) TCCS as the test article, was designed to add to the existing database on TCCS performance. Included in this database are results obtained during ISS development testing; testing of functionally similar TCCS prototype units; and bench scale testing of activated charcoal, oxidation catalyst, and granular lithium hydroxide (LiOH). The present database has served as the basis for the development and validation of a computerized TCCS process simulation model. This model serves as the primary means for verifying the ISS TCCS performance. In order to mitigate risk associated with this verification approach, the U.S. Hab TCCS performance test provides an additional set of data which serve to anchor both the process model and previously-obtained development test data to flight hardware performance. The following discussion provides relevant background followed by a summary of the test hardware, objectives, requirements, and facilities. Facility and test article performance during the test is summarized, test results are presented, and the TCCS's performance relative to past test experience is discussed. Performance predictions made with the TCCS process model are compared with the U.S. Hab TCCS test results to demonstrate its validation.

Perry, J. L.↗

DOE OSTI2023

Design, modeling and simulation of nuclear-powered integrated energy systems with cascaded heating applications

Nuclear-renewable integrated energy systems (IES) consist of a variety of energy generation and conversion technologies and can be used to meet heterogeneous end uses (e.g., electricity, heat, and cooling demands). In addition to supply-demand balance, end-use heat demands usually require heat supply of certain temperature ranges. The effective and efficient utilization of heat produced within an IES is, therefore, a critical challenge. Here, this paper examines design options of an IES that includes heating processes of multiple temperature grades. We investigate a cascaded design configuration, where the remaining residual heat after high-grade heating processes [e.g., hydrogen production through high-temperature steam electrolysis (HTSE)] is recovered to meet the low-grade heating needs [e.g., district heating (DH)]. Additionally, a thermal energy storage system is integrated into the DH system to address the imbalance between heat supply and demand. This paper primarily focuses on the design and modeling of the proposed system and evaluates its operation with a 24-h transient process simulation using a DH demand profile with hourly resolution. The results indicate that the residual heat from the HTSE exhaust is insufficient for the DH demand, and additional topping heat directly from the reactor process steam is needed. Furthermore, the inclusion of thermal energy storage within the DH system provides the necessary balance between thermal generation and demand, thereby ensuring a consistent rated temperature of the DH supply water. This approach helps minimize the control actions needed on the reactor side.

08 HYDROGEN↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2007

A Project Management Approach to Using Simulation for Cost Estimation on Large, Complex Software Development Projects

It is very difficult for project managers to develop accurate cost and schedule estimates for large, complex software development projects. None of the approaches or tools available today can estimate the true cost of software with any high degree of accuracy early in a project. This paper provides an approach that utilizes a software development process simulation model that considers and conveys the level of uncertainty that exists when developing an initial estimate. A NASA project will be analyzed using simulation and data from the Software Engineering Laboratory to show the benefits of such an approach.

Mizell, Carolyn↗

DOE OSTI2022

Flexible FlueCO2

Carbon dioxide (CO2) emission reductions remain a significant challenge on the path to clean energy. There are increasing legislative, social, and environmental factors motivating CO2 emissions reduction from power plants with carbon capture and storage (CCS). CCS in natural gas combined cycle (NGCC) power plants is critical to achieve a net-zero carbon electricity grid. Enhanced 45Q tax credits provide new incentives, but currently available technologies are unable to profitably operate in grids with deep variable renewable penetration which require flexible NGCC operation. Luna Labs has developed the FlueCO2 membrane to enable a profitable NGCC-CCS process. The FlueCO2 membrane couples steam transport across the membrane to CO2 transport in the opposite direction, enabling high capture efficiencies and low energy costs even at low CO2 concentrations. The dual-phase membrane can operate in the range of typical flue gas temperatures and pressures and does not require temperature or pressure cycling. Luna Labs’ FlueCO2 technology enables flexible and profitable operation of NGCC plants with lower capital investment and impact on electricity prices. In this Phase 1 project, Luna Labs utilized experimental testing, modeling, process simulation, and standardized costing methodologies to evaluate the techno-economic value of a 650 MW greenfield NGCC plant with FlueCO2 (NGCC-FlueCO2). Key design requirements for operation were established and plant performance under load-leveling conditions was validated through computational fluid dynamics and process modeling. Luna Labs developed a dynamic modeling tool which modeled plant operational modes across a variety of tax structures and electricity pricing scenarios to project the overall Net Present Value (NPV) of the NGCC-FlueCO2. FlueCO2 minimizes the impact of CCS integration on plant operation by integrating directly into the NGCC heat recovery steam generator (HRSG). By tapping into the plant’s low-pressure (LP) steam, operators can divert LP steam to the greenfield NGCC and/or CCS process in response to dynamic markets. Since FlueCO2 will not significantly affect HRSG (or NGCC) operation, CCS only turns off during peak power demand (>$250/MWh). Under baseload conditions, FlueCO2 lowers the capital (37%), energy (36%) and carbon capture (<$40/tonne) costs and can increase the overall plant lifetime NPV by approximately ~$1B in comparison with NGCC solvent-based capture reference cases (NETL Case 31B). Luna Labs has shared its costing tools with several interested partners and customers, which follows a generalizable approach to costing analysis.

Kelly, Jesse↗

NASA NTRS2001

Overview of ICE Project: Integration of Computational Fluid Dynamics and Experiments

Researchers at the NASA Glenn Research Center have developed a prototype integrated environment for interactively exploring, analyzing, and validating information from computational fluid dynamics (CFD) computations and experiments. The Integrated CFD and Experiments (ICE) project is a first attempt at providing a researcher with a common user interface for control, manipulation, analysis, and data storage for both experiments and simulation. ICE can be used as a live, on-tine system that displays and archives data as they are gathered; as a postprocessing system for dataset manipulation and analysis; and as a control interface or "steering mechanism" for simulation codes while visualizing the results. Although the full capabilities of ICE have not been completely demonstrated, this report documents the current system. Various applications of ICE are discussed: a low-speed compressor, a supersonic inlet, real-time data visualization, and a parallel-processing simulation code interface. A detailed data model for the compressor application is included in the appendix.

Stegeman, James D.↗

DOE OSTI2022

A reference open-source controller for fixed and floating offshore wind turbines

Abstract. This paper describes the development of a new reference controller framework for fixed and floating offshore wind turbines that greatly facilitates controller tuning and represents standard industry practices. The reference wind turbine controllers that are most commonly cited in the literature have been developed to work with specific reference wind turbines. Although these controllers have provided standard control functionalities, they are often not easy to modify for use on other turbines, so it has been challenging for researchers to run representative, fully dynamic simulations of other wind turbine designs. The Reference Open-Source Controller (ROSCO) has been developed to provide a modular reference wind turbine controller that represents industry standards and performs comparably to or better than existing reference controllers. The formulation of the ROSCO controller logic and tuning processes is presented in this paper. Control capabilities such as tip speed ratio tracking generator torque control, minimum pitch saturation, wind speed estimation, and a smoothing algorithm at near-rated operation are included to provide modern controller features. A floating offshore wind turbine feedback module is also included to facilitate growing research in the floating offshore arena. All of the standard controller implementations and control modules are automatically tuned such that a non-controls engineer or automated optimization routine can easily improve the controller performance. This article provides the framework and theoretical basis for the ROSCO controller modules and generic tuning processes. Simulations of the National Renewable Energy Laboratory (NREL) 5 MW reference wind turbine and International Energy Agency 15 MW reference turbine on the University of Maine semisubmersible platform are analyzed to demonstrate the controller's performance in both fixed and floating configurations, respectively. The simulation results demonstrate ROSCO's peak shaving routine to reduce maximum rotor thrusts by over 10 % compared to the NREL 5 MW reference wind turbine controller on the land-based turbine and to reduce maximum platform pitch angles by nearly 30 % when using the platform feedback routine instead of a more traditional low-bandwidth controller.

17 WIND ENERGY↗

DOE OSTI2025

XFEM Development for Modeling Crack Growth in Prototypical Welded Components

Nuclear power plant components are subjected to harsh operating environments that can lead to multiple degradation mechanisms in which fracture can play a prominent role. Predicting crack growth is important for assessing the integrity of welded components. The extended finite element method (XFEM) is an important tool for modeling such crack growth, and XFEM capabilities have been developed within the MOOSE framework. This report documents work in the MOOSE XFEM module to model fractures in three-dimensional representations of components using a topologically two-dimensional mesh to define cutting planes. Crack growth algorithms have been implemented to evolve the cutting mesh based on equations for stress corrosion cracking. Additionally, several usability and robustness improvements have been developed to enable three-dimensional fracture simulations. The cutting algorithms were demonstrated on a three-dimensional model of a prototypical reactor component undergoing stress corrosion cracking driven by idealized weld residual stresses. This is an incremental step toward using this capability to model more complex components with residual stresses computed through welding process simulations.

42 - ENGINEERING↗

NASA NTRS2014

Wind-US Results for the AIAA 2nd Propulsion Aerodynamics Workshop

This presentation contains Wind-US results presented at the 2nd Propulsion Aerodynamics Workshop. The workshop was organized by the American Institute of Aeronautics and Astronautics, Air Breathing Propulsion Systems Integration Technical Committee with the purpose of assessing the accuracy of computational fluid dynamics for air breathing propulsion applications. Attendees included representatives from government, industry, academia, and commercial software companies. Participants were encouraged to explore and discuss all aspects of the simulation process including the effects of mesh type and refinement, solver numerical schemes, and turbulence modeling. The first set of challenge cases involved computing the thrust and discharge coefficients for a 25deg conical nozzle for a range of nozzle pressure ratios between 1.4 and 7.0. Participants were also asked to simulate two cases in which the 25deg conical nozzle was bifurcated by a solid plate, resulting in vortex shedding (NPR=1.6) and shifted plume shock (NPR=4.0). A second set of nozzle cases involved computing the discharge and thrust coefficients for a convergent dual stream nozzle for a range of subsonic nozzle pressure ratios. The workshop committee also compared the plume mixing of these cases across various codes and models. The final test case was a serpentine inlet diffuser with an outlet to inlet area ratio of 1.52 and an offset of 1.34 times the inlet diameter. Boundary layer profiles, wall static pressure, and total pressure at downstream rake locations were examined.

Wind-US↗

DOE OSTI2020

Accelerating Hanford Site Cleanup through Operations Research Modeling - 20238

The Hanford Site cleanup effort will require the integration of dozens of unique facilities and processes, many of which will be first-of-a-kind in implementation and design. Each facility will be governed by its own set of operating logic, configured with a unique array of unit operations, and subject to a set of constraints that will affect its behavior. The collection of facilities have multiple points of interface, making the operations of any one facility potentially significant to the operations of other up- or downstream processes. It is therefore highly desirable to accurately predict these operations, as it allows for Site officials to identify and preempt bottlenecks and vulnerabilities before they unexpectedly inhibit the cleanup mission. With the quantity and complexity of the processes that will be on Site, building a pen-and-paper or even a spreadsheet-assisted model of the cleanup mission quickly becomes overwhelming in scope and inaccurate in execution. The Engineering organization for the Site's Tank Operations Contract (TOC) has therefore implemented the use of operations research (OR) modeling to simulate and predict future operations of Site facilities. These models are created using a discrete event simulation tool that allows for the development of detailed, versatile, and robust models. Not only can these models account for complex logical behaviors, but they can also simulate process details down to the level of vessel sizing, labor utilization, equipment reliability, and resource availability. To date, the TOC has developed OR models for several facilities on Site, including for single-shell tank (SST) farms, double-shell tank (DST) farms, the Effluent Treatment Facility (ETF), and the waste transfer system. These models have focused on identifying bottlenecks and operational constraints, and have been used to quantify the effects of implementing process changes. This latter point is particularly valuable, as it allows for several alternatives to be studied in a virtual setting before committing resources to making a change in the field. The decision to develop OR models has gained tremendous support from the Site's stakeholders and the U.S. Department of Energy (DOE) management, and has prompted the use of the tool to support additional internal and external initiatives. Recently, an initiative was proposed to use the models to help identify and provide quantitative backing for risks and opportunities for the TOC. This application of OR could not only help inform how the TOC manages its risks (e.g. quantities and types of spare parts), but could also help drive process improvements whose benefits might otherwise be hard to quantify. The models have also been used to drive the TOC's cloud computing, artificial intelligence (AI), and machine learning (ML) initiatives. These initiatives will not only improve the ability of the TOC to more rapidly respond to the needs of its customers, but it will also aid in the ability of the TOC to analyze and improve the processes it studies. Partnership with two external software development and consulting companies (Lanner and Ynformed) has furthered not only the application of AI and ML within the TOC, but has also spurred the development of new/improved software tools and platforms used by the companies. These partnerships have proven to be mutually beneficial and productive, and have set a precedent for the types of gains that can be made by exploring such options. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2022

Simulation and Scaling of the Turbulent Vertical Heat Transport and Deep-Cycle Turbulence Across the Equatorial Pacific Cold Tongue

Microstructure observations in the Pacific cold tongue reveal that strong turbulence often penetrates into the thermocline producing hundreds of W/m2 of downward heat transport during nighttime and early morning. However, virtually all observations of this deep-cycle turbulence (DCT) are from 0◦N,140◦W. Here, a hierarchy of ocean process simulations including submesoscale-permitting regional models and turbulence-permitting large eddy simulations (LES) embedded in a regional model provide insight into DCT at and beyond 0◦N,140◦W. A regional hindcast quantifies the spatio-temporal variability of subsurface turbulent heat fluxes throughout the cold tongue from 1999-2016. Climatologically, the mean heat flux is strongest (∼100W/m2) within2◦ of the equator. The heat flux is slightly (∼10 W/m2) stronger in the northern than southern hemisphere throughout the cold tongue. The seasonal cycle of the heat flux, which is not everywhere aligned with the surface flux, ranges from 150 W/m2 near the equator to 30 W/m2 and 10 W/m2 at 4◦N and S respectively. Aseasonal variability of turbulent heat fluxes is logarithmically distributed and temporally uncorrelated with surface heat fluxes. The aseasonal variability of turbulence is highlighted in 34-day LES of Boreal autumn at 0◦N and 3◦N,140◦W. Intense DCT occurs frequently above the undercurrent at 0◦N and intermittently at 3◦N. Daily-mean heat fluxes scale with the bulk vertical shear and the wind stress, which together explain ∼90% of the daily variance across both LES. Observational validation of the scaling at 0◦N,140◦W is encouraging, but observations beyond 0◦N,140◦W can facilitate needed refinement of mixing parameterization in ocean models.

Simulation↗

NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗

DOE OSTI2021

Computational Fermi Level Engineering and Doping-Type Conversion of Ga2O3 Via Three-Step Processing

Ga2O3 is being actively explored for power electronics, deep-ultraviolet optoelectronics, and other applications due to its ultra-wide bandgap and low projected fabrication cost of large-size and high-quality crystals. N-type doping of Ga2O3 can be achieved and tuned, but p-type doping faces fundamental obstacles due to deep character of acceptor levels and polaron transport of resulting holes. However, successful engineering of Ga2O3 based devices requires critical control of doping density, Fermi level position, and free carrier concentration, providing opportunities for predictive process simulation. We use first-principles defect theory and defect equilibrium calculations to simulate a 3-step growth-annealing-quench protocol for hydrogen assisted Mg doping in Ga2O3, taking into account the hydrogen-oxygen-water gas phase equilibrium. We predict type conversion to a net p-type regime following O-rich annealing after growth under reducing conditions in the presence of H2. This process is similar to the Mg acceptor activation by H removal in GaN. We show that there is an optimal temperature that maximizes the net acceptor density during the equilibrium annealing step for a given Mg doping level. Quenching of non-equilibrium annealed samples then results in a Fermi level EF below mid-gap down to about EV +1.5 eV, creating a significant number of uncompensated neutral MgGa0 acceptors. The resulting free hole concentration in quenched samples is very low (109 – 1012 cm-3) due to deep energy level of these Mg acceptors, but this type converted Ga2O3 material can create a significant built-in field in a p-n junction with an adjoining n-type material. Additionally, the electron concentration is greatly suppressed in such acceptor-doped Ga2O3, which could enable the use as a current blocking layer to fabricate normally-off (enhancement-mode) vertical Ga2O3 based metal-oxide-semiconductor field effect transistors (MOSFETs), and as a guard ring for edge termination in MOSFETs and Schottky barrier diodes (SBDs) with increased breakdown voltage.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS,M↗

DOE OSTI2023

Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL) proved to be effective in optimizing the management of integrated energy systems in buildings, reducing energy costs and improving indoor comfort conditions when compared to traditional reactive controllers. However, the scalability and implementation of DRL controllers are still limited since they require a considerable amount of time before converging to a near-optimal solution. This issue is currently addressed in literature through the offline pre-training of the DRL agent. However this solution results in two main critical issues: (1) the need to develop a building surrogate model to perform the training task, and (2) the need to perform a fine-tuning process over several training episodes to obtain a near-optimal control policy. In this context, this paper introduces an Online Transfer Learning (OTL) strategy that exploits two knowledge-sharing techniques, weight-initialization and imitation learning, to transfer a DRL control policy from a source office building to various target buildings in a simulation environment coupling EnergyPlus and Python. A DRL controller based on discrete Soft Actor–Critic (SAC) is trained on the source building to manage the operation of a cooling system consisting of a chiller and a thermal storage. Several target buildings are defined to benchmark the performance of the OTL strategy with that of a Rule-Based Controller (RBC) and two DRL-based control strategies, deployed in offline and online fashion. The strategy adopted for OTL emulates the real world implementation with a simulation process by implementing the transferred DRL agent for a single episode in the target buildings. Target buildings have the same geometrical features and are served by the same energy system as the source building, but differ in terms of weather conditions, electricity price schedules, occupancy patterns, and building envelope efficiency levels. The results show that the OTL strategy can reduce the cumulated sum of temperature violations on average by 50% and 80% respectively when compared to RBC and online DRL while enhancing the energy system operation with electricity cost savings ranging between 20% and 40%. Furthermore, the OTL agent performs slightly worse than the offline DRL controller but it does not require any modeling effort and can be implemented directly on target buildings emulating a real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗