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DOE OSTI2023

Convolutional Neural Network–Aided Temperature Field Reconstruction: An Innovative Method for Advanced Reactor Monitoring

In this study, the capabilities of a physics-informed convolutional neural network (CNN) for reconstructing the temperature field from a limited set of measurements taken at the boundaries of internal flows are demonstrated. Such an approach enables the development of less invasive monitoring methods for real-time plant diagnostics. As a test case, a Molten Salt Fast Reactor (MSFR) design was selected. This circulating fuel reactor has received interest from both scientific and industrial communities due to its intrinsic safety and sustainability. Molten salt flows in such reactors, however, can present highly localized temperature peaks that can induce significant thermal stresses onto the vessel walls. At these local maxima, the salt temperature may exceed a thousand kelvins, which makes a direct measurement challenging or even unfeasible. The proposed CNN algorithm allows one to detect indirectly such discontinuities through an accurate, albeit indirect, temperature measurement method during reactor operation. The datasets employed to train and test the machine learning models in the present work were generated with Nek5000, a computational fluid dynamics (CFD) code developed at Argonne National Laboratory. The CNN algorithm is trained with CFD results that span a set of MSFR operational power and flow ranges. Here, to demonstrate the efficacy of the algorithm, predictions are made for test cases contained within the training range but for which the CFD data were not used when training. Results demonstrate that the proposed technique properly characterizes temperature peaks and distributions within the domain for a broad range of scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1995

Real time acousto-ultrasonic NDE technique for monitoring damage in ceramic composites under dynamic loads

Research effort was directed towards developing a near real-time, acousto-ultrasonic (AU), nondestructive evaluation (NDE) tool to study the failure mechanisms of ceramic composites. Progression of damage is monitored in real-time by observing the changes in the received AU signal during the actual test. During the real-time AU test, the AU signals are generated and received by the AU transducers attached to the specimen while it is being subjected to increasing quasi-static loads or cyclic loads (10 Hz, R = 1.0). The received AU signals for 64 successive pulses were gated in the time domain (T = 40.96 micro sec) and then averaged every second over ten load cycles and stored in a computer file during fatigue tests. These averaged gated signals are representative of the damage state of the specimen at that point of its fatigue life. This is also the first major attempt in the development and application of real-time AU for continuously monitoring damage accumulation during fatigue without interrupting the test. The present work has verified the capability of the AU technique to assess the damage state in silicon carbide/calcium aluminosilicate (SiC/CAS) and silicon carbide/ magnesium aluminosilicate (SiC/MAS) ceramic composites. Continuous monitoring of damage initiation and progression under quasi-static ramp loading in tension to failure of unidirectional and cross-ply SiC/CAS and quasi-isotropic SiC/MAS ceramic composite specimens at room temperature was accomplished using near real-time AU parameters. The AU technique was shown to be able to detect the stress levels for the onset and saturation of matrix cracks, respectively. The critical cracking stress level is used as a design stress for brittle matrix composites operating at elevated temperatures. The AU technique has found that the critical cracking stress level is 10-15% below the level presently obtained for design purposes from analytical models. An acousto-ultrasonic stress-strain response (AUSSR) model for unidirectional and cross-ply ceramic composites was formulated. The AUSSR model predicts the strain response to increasing stress levels using real-time AU data and classical laminated plate theory. The Weibull parameters of the AUSSR model are used to calculate the design stress for thermo-structural applications. Real-time AU together with the AUSSR model was used to study the failure mechanisms of SiC/CAS ceramic composites under static and fatigue loading. An S-N curve was generated for a cross-ply SiC/CAS ceramic composite material. The AU results are corroborated and complemented by other NDE techniques, namely, in-situ optical microscope video recordings and edge replication.

Tiwari, Anil↗

DOE OSTI2022

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗

DOE OSTI2020

Development of an In-Situ Method for Cable Condition Monitoring in Nuclear Power Plants (SBIR Phase IIB Final Report)

This is the final report of a Small Business Innovation Research (SBIR) project that Analysis and Measurement Services Corporation (AMS) has conducted for the U.S. Department of Energy (DOE) over a seven-and-a-half year period (February 2013 through April 2020 with the awards of Phase I, Phase II and Phase IIB projects). The goal of the project was to design, develop, validate, and demonstrate a technique for in-situ testing of cable insulation polymers that will identify, locate, and provide the degree of aging for cables commonly used in nuclear power plants. During the Phase I project, AMS established that the frequency domain reflectometry (FDR) technique can successfully identify and measure cable insulation degradation that can be trended with aging. In Phase II, AMS performed extensive cable aging studies to correlate FDR measurements with other laboratory condition monitoring techniques and developed aging condition categories to quantify the severity of insulation degradation. In Phase IIB, the project expanded the research to include a wider variety of cable polymers that are used in the commercial nuclear power industry. This work also involved developing acceptance criteria to objectively assess age-related cable degradation while sharing the results of this research with industry, academia, and national laboratories to advance the state of the art in cable aging management technologies. The products developed under this research project provide the nuclear industry with an effective condition monitoring tool to support safe and long-term plant operation. Throughout the project, collaborations and support were received from a variety of industry organizations and individuals including DOE National Laboratories as well as nuclear plant utilities and several other industry experts and cable manufacturers. Contributions from these organizations included the donation of new cables, naturally aged cables, and research collaboration. The validation and commercialization of the products of this project were achieved through opportunities to test and demonstrate the technologies’ capabilities on-site at nuclear power generation and research facilities as well as in the laboratory alongside industry peers and cable testing service companies. The research resulted in a technology that can be used to identify, locate, and quantify age-related degradation in several types of cable polymers. This included developing software and hardware as well as the methodology for using the FDR technique to assess age-related degradation of installed cables. The technology developed under this project can provide nuclear plant management, engineers, and technicians with an in-situ electrical test method to determine if in-service cables need to be replaced, monitored on a periodic basis, or show no evidence of significant age-related degradation that may require action. Near the end of this Phase IIB project, the FDR product was sold to a nuclear power utility in South Korea. This sale of a dedicated aging assessment tool is the beginning of a comprehensive contract with the expectation of twelve (12) units sold to that country. Additionally, the FDR technology has been sold to several industry organizations including a nuclear research institute and the Diablo Canyon nuclear power plant. This technology is also being leased by other nuclear industry service companies for incorporation into aging management programs. The cable testing technology that was developed under this project was also integrated into a comprehensive cable aging assessment service that is being offered to the nuclear industry at the request of U.S. nuclear utilities and is currently part of onsite testing services provided by AMS.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRSDate not supplied

Performance Risk Model Validation with Operationally Relevant Tasks

Human Research Program aims to develop methods to support astronauts’ health and productivity during spaceflight. The Crew Health and Performance Probabilistic Risk Assessment (CHP-PRA) team uses powerful computational methods to predict mission risk in both domains: medical and performance. Here, we show how CHP-PRA uses the Performance Risk Model (PRisM) to quantify the performance risk and show an application of the model on operationally relevant tasks. There are various metrics adopted across performance researchers that PRisM can accommodate. For data analysis, interpretation, and integration, we use a method of unifying data from multiple sources by converting each to a single metric. We consult subject matter experts prior to integrating the converted data into PRisM. The method we use is inspired by the Cooper-Harper rating scale [1]. Using this unified metric, we can easily combine data from various tests and lab groups. We explain our conversion method in detail and show how it pertains to the process of testing and validation of PRisM on operational tasks. We conducted an initial validation in collaboration with the Behavioral Health and Performance (BHP) lab. We test PRisM using data on their operationally relevant task ROBoT-r, a track-and-capture task for grappling incoming resupply vehicles [2]. Several other labs at NASA Johnson Space Center worked together to design 7 Functional Task Tests (FTTs) in pursuit of simulating the tasks required after landing on a planetary surface and after return to Earth [3]. Here we use the results from both ROBoT-r and the 7 FTTs and compare their experiment data to PRisM’s computational output to demonstrate how PRisM can support operations by predicting crew performance on future missions.

performance modeling↗

DOE OSTI2022

Effect of Thermal Expansion Coefficient, Viscosity and Melting Range in Simulation of PCM Embedded Heat Exchangers With and Without Fins

Phase change material heat exchangers (PCMHX) have an important role in integrating renewable energy systems. PCMHX can offer high storage density at various temperatures of interest and can be used for grid load shifting purposes. Numerical models enable engineers to estimate PCMHX performance for different design parameters and operating conditions. Modeling phase change phenomena is challenging due to the complex time-dependent nature of the process. The accuracy of models is highly sensitive to PCM thermo-physical properties. Thermal expansion coefficient (β), viscosity (μ) and melting temperature range (MR) of a PCM are important properties, especially when natural convection is not negligible. In PCMHX modeling, using less than accurate values for these properties can have significant impact on the simulation outcomes. These properties and discussions thereof are not readily available in the literature. This paper presents a brief review of the literature and a numerical study investigating the model sensitivity to the above-mentioned properties for PCMHX with and without fins. CFD is used to evaluate the charging (melting) phenomena. The study quantifies the impact of uncertainty in these properties on the melting rate and temperature profile. Constant wall temperature was considered as heat source with no heat loss to ambient. Here, the results show that β and μ has significant effect on the melting rate and evolution of the melting front. For a non-finned domain when comparing results for different published values of β and μ, the deviation in melting time can be up to 12.9% and 57.6% respectively. For high wall temperatures, change in melting range did not impact melting time. But when the wall temperature is reduced, up to 9.8% deviation in melting time is observed.

CFD↗

NASA NTRS2017

Design and Principles Enabling the Space Reference FOM

A first complete draft of the Simulation Interoperability Standards Organization (SISO) Space Reference Federation Object Model (FOM) has now been produced. This paper provides some insights into its capabilities and discusses the opportunity for reuse in other domains. The focus of this first version of the standard is execution control, time management and coordinate systems, well-known reference frames, as well as some basic support for physical entities. The biggest part of the execution control is the coordinated start-up process. This process contains a number of steps, including checking of required federates, handling of early versus late joiners, sharing of federation wide configuration data and multi-phase initialization. An additional part of Execution Control is the coordinated and synchronized transition between Run mode, Freeze mode and Shutdown. For time management, several time lines are defined, including real-time, scenario time, High Level Architecture (HLA) logical time and physical time. A strategy for mixing simulations that use different time steps is introduced, as well as an approach for finding common boundaries for fully synchronized freeze. For describing spatial information, a mechanism with a set of reference frames is specified. Each reference frame has a position and orientation related to a parent reference frame. This makes it possible for federates to perform calculations in reference frames that are convenient to them. An operation on the Moon can be performed using lunar coordinates whereas an operation on Earth can be performed using Earth coordinates. At the same time, coordinates in one reference frame have an unambiguous relationship to a coordinate in another reference frame. While the Space Reference FOM is originally being developed for Space operations, the authors believe that many parts of it can be reused for any simulation that has a focus on physical processes with one or more coordinate systems, and require high fidelity and repeatability.

Moeller, Bjoern↗

DOE OSTI2025

Multiscale Thermal-hydraulic analysis of the MARVEL microreactor using a coupled SAM and SCM simulation. (PPTX)

This is .pptx document presenting a summary of the paper of the same name that has been submitted and accepted to NURETH-21: MARVEL is a natural-convection-cooled sodium-potassium microreactor that is anticipated to generate 85 kilowatts of thermal energy. It will operate within Idaho National Laboratory Transient Reactor Test Facility and is being developed by the DOE Microreactor Program. MARVEL will be used to test microreactor applications, evaluate systems for remote monitoring, and develop autonomous control technologies. A thermal-hydraulic computational model of this facility is a valuable tool to study important transients and calculate the safety limits of the micro-reactor design. For this purpose, the authors have chosen to use a multiscale coupled simulation: SCM for modeling the reactor core and SAM for the reactor's primary cooling system. SCM is MOOSE physics module for subchannel analysis, which was designed to model single-phase flows through liquid-metal cooled, wire-wrapped fuel pin sub-assemblies, ordered in a triangular lattice. The SCM code was modified to be able to model MARVEL?s unique geometry. SAM is a systems analysis module based on the MOOSE framework. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for various advanced reactor types. The coupling between the two SCM and SAM for MARVEL modeling is done implementing a domain over-lapping approach. The resulting coupled simulation can model transients such as reactor startup/shutdown and provide an intermediate fidelity picture of the temperature field and other variables, in the core. Results for the steady-state simulations are presented in the article as well as flow blockage transient.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

DOE OSTI2025

Multiscale Thermal-hydraulic analysis of the MARVEL micro-reactor using coupled MOOSE Subchannel (SCM) and SAM

MARVEL is a natural-convection-cooled sodium-potassium microreactor that is anticipated to generate 85 kilowatts of thermal energy. It will operate within Idaho National Laboratory’s Transient Reactor Test Facility and is being developed by the DOE Microreactor Program. MARVEL will be used to test microreactor applications, evaluate systems for remote monitoring, and develop autonomous control technologies. A thermal-hydraulic computational model of this facility is a valuable tool to study important transients and calculate the safety limits of the micro-reactor design. For this purpose, the authors have chosen to use a multiscale coupled simulation: SCM for modeling the reactor core and SAM for the reactor’s primary cooling system. SCM is MOOSE physics module for subchannel analysis, which was designed to model single-phase flows through liquid-metal cooled, wire-wrapped fuel pin sub-assemblies, ordered in a triangular lattice. The SCM code was modified to be able to model MARVEL’s unique geometry. SAM is a systems analysis module based on the MOOSE framework. It aims to provide fast-running, whole-plant transient analyses capability with improved-fidelity for various advanced reactor types. The coupling between the two SCM and SAM for MARVEL modeling is done implementing a domain over-lapping approach. The resulting coupled simulation can model transients such as reactor startup/shutdown and provide an intermediate fidelity picture of the temperature field and other variables, in the core. Results for the steady-state simulations are presented in the article as well as flow blockage transient.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Evaluation of HVAC & refrigeration system fault behaviors and impacts: A systematic review

Achieving the goals of green buildings critically depends on the fault-free operation of heating, ventilation and air conditioning and refrigeration (HVAC&R) systems. However, faults frequently occur in these systems, causing a range of negative consequences, including increased energy consumption, diminished operational performance, compromised indoor environmental quality, higher operational costs, and shortened system lifespan. The evaluation of fault behaviors and impacts plays a critical role in revealing fault characteristics and consequently supports many research areas, including the design of the high-performance equipment, development of fault detection and diagnostics (FDD) and robust control approaches, as well as the enhancement of maintenance decision-making activities. This paper systematically reviews 112 research publications that reported the analysis and evaluation of fault behaviors and impacts in HVAC&R systems over the past thirty years. Here, we designed a review approach to address five crucial research questions, namely: 1) the objectives of analysis and evaluation of fault behaviors and impacts, 2) data sources, 3) equipment/system types and fault types, 4) evaluation methods including evaluation measures and associated metrics, and 5) challenges and future directions in the research on evaluating of fault behaviors and impacts. In-depth discussions on these questions help bridge the gap between the evaluation of fault behaviors and impacts and their practical applications, such as the development of high-performance systems, fault models, FDD methods, and maintenance decision-making tools within the HVAC&R FDD domain.

Chen, Yimin [Oak Ridge National Laboratory (ORNL),↗

NASA NTRS1988

MOORE: A prototype expert system for diagnosing spacecraft problems

MOORE is a rule-based, prototype expert system that assists in diagnosing operational Tracking and Data Relay Satellite (TDRS) problems. It is intended to assist spacecraft engineers at the TDRS ground terminal in trouble shooting problems that are not readily solved with routine procedures, and without expert counsel. An additional goal of the prototype system is to develop in-house expert system and knowledge engineering skills. The prototype system diagnoses antenna pointing and earth pointing problems that may occur within the TDRS Attitude Control System (ACS). Plans include expansion to fault isolation of problems in the most critical subsystems of the TDRS spacecraft. Long term benefits are anticipated with use of an expert system during future TDRS programs with increased mission support time, reduced problem solving time, and retained expert knowledge and experience. Phase 2 of the project is intended to provide NASA the necessary expertise and capability to define requirements, evaluate proposals, and monitor the development progress of a highly competent expert system for NASA's Tracking Data Relay Satellite. Phase 2 also envisions addressing two unexplored applications for expert systems, spacecraft integration and tests (I and T) and support to launch activities. The concept, goals, domain, tools, knowledge acquisition, developmental approach, and design of the expert system. It will explain how NASA obtained the knowledge and capability to develop the system in-house without assistance from outside consultants. Future plans will also be presented.

Howlin, Katherine↗

DOE OSTI2021

High-Level Synthesis of Parallel Specifications Coupling Static and Dynamic Controllers

The increased need for efficient ways to implement domain-specific accelerators is driving design methodologies towards the use of abstractions higher than the Register Transfer Level (RTL). In this scenario, High Level Synthesis (HLS) plays a significant role by enabling the automatic generation of custom hardware accelerators starting from high level descriptions (e.g., C code). Conventional HLS tools exploit parallelism mostly at the Instruction Level (ILP). They statically schedule the input specifications, and build centralized Finite State Machine (FSM) controllers. However, aggressive exploitation of ILP in many applications has diminishing returns and, usually, centralized approaches do not efficiently exploit coarser parallelism because FSMs are inherently serial. In this paper we present a HLS framework able to synthesize applications that, beside ILP, also expose Task Level Parallelism (TLP). An application can expose TLP through annotations that identify the parallel functions (i.e., tasks). To generate accelerators that efficiently execute concur- rent tasks, we need to solve several issues: devise a mechanism to support concurrent execution flows, exploit memory parallelism, and manage synchronization. To support concurrent execution flows, we introduce a novel adaptive controller. The adaptive controller is composed of a set of interacting control elements that independently manage the execution of a single operation or function call. These control elements check dependencies and resource constraints at runtime, enabling as soon as possible execution. To support parallel access to shared memories and synchronization, we introduce a novel Hierarchical Memory Interface (HMI). With respect to previous solutions, the proposed interface supports multi-ported memories and atomic memory operations, which commonly occur in parallel programming. Our framework can generate the hardware implementation of C functions by employing two different approaches, depending on its characteristics. If a function exposes TLP, then the framework generates hardware implementations based on the adaptive controller. Otherwise, the framework implements the function by exploiting a more conventional FSM approach, which is optimized for ILP exploitation. We evaluate our framework on a set of parallel applications, and show substantial performance improvements (average speedup of 4.7) with limited area over- heads (average area increase of 5.48 times).

Castellana, Vito G.↗

DOE OSTI2021

High-Level Synthesis of Parallel Specifications Coupling Static and Dynamic Controllers

Castellana, Vito G.↗

DOE OSTI2021

New Fracture Diagnostic Tool for Unconventionals: High-Resolution Distributed Strain Sensing via Rayleigh Frequency Shift during Production in Hydraulic Fracture Test 2

Fiber Optic monitoring in unconventional reservoirs has proven to be an invaluable diagnostic tool for assessing both near-wellbore stimulation effectiveness and to help describe the far-field frac geometries created by hydraulic fracture stimulation. Unfortunately, gaining any detailed qualitative and quantitative understanding of the near-wellbore frac geometry or cluster/stage productivity during production via Fiber Optic (FO) has proven to be more difficult, particularly in wells producing liquids. A new FO diagnostic method, Distributed Strain Sensing based on Rayleigh Frequency Shift (DSS-RFS), first demonstrated for oil and gas applications in the Hydraulic Test Site 2 (HFTS2) provides new insights about the characteristics of near-wellbore-region (NWR) during production. DSS-RFS is different from other FO strain measurements because it relies on accurate measurement of frequency shifts of Rayleigh backscattered spectrum obtained by scanning the fiber with a coherent optical time-domain reflectometer with a range of laser frequencies using a tunable-wavelength laser system. Changes in strain are measured with an extremely high spatial resolution of 20 cm and with high signal-to-noise ratios over long distances. In HFTS2, strain changes for the entire wellbore have been measured twice during scheduled shut-in and reopening operations (February 2020 and September 2020). After removing temperature effects, consistent strain changes have been observed at the location of most perforation clusters. These are caused by near wellbore fracture aperture changes due to pressure increases during shut-in within the near-wellbore fracture network. The strain-change patterns from the DSS-RFS during shut-in correlate very well with the location of clusters and allow for the definition of extending intervals with positive strain signals at each cluster and slightly compressing intervals with negative strain signals between the clusters and in the non stimulated intervals. The locations of the measured positive strain peaks also show good correspondence to DAS acoustic intensity measurements acquired during the stimulation. The geometry and magnitude of the strain changes differ significantly between the two tested completion designs in the same well. During shut in and reopening each cluster exhibit its own strain-change / pressure path. In addition, the September 2020 dataset also revealed the existence of small but measurable strain changes as consequence of pressure decline during production. These strain changes also correlate well with the presence of producing clusters, but the strain-rate signals are opposite to that obtained during shut-in and reopening operations. Although Downloaded from http://onepetro.org/URTECONF/proceedings-pdf/21URTC/2-21URTC/D021S031R002/2477551/urtec-2021-5408-ms.pdf/1 by Carol Worster on 28 February 2022 URTeC 5408 2 we are still in the early stages of exploring the potential of this novel FO technique, we believe that the highly detailed information contained in the measurement of strain changes using DSS-RFS during production can significantly improve our understanding of near-wellbore hydraulic fracture characteristics and the relationships between stimulation and production from unconventional oil and gas wells.

04 OIL SHALES AND TAR SANDS↗

NASA NTRS2006

Implementing Access to Data Distributed on Many Processors

A reference architecture is defined for an object-oriented implementation of domains, arrays, and distributions written in the programming language Chapel. This technology primarily addresses domains that contain arrays that have regular index sets with the low-level implementation details being beyond the scope of this discussion. What is defined is a complete set of object-oriented operators that allows one to perform data distributions for domain arrays involving regular arithmetic index sets. What is unique is that these operators allow for the arbitrary regions of the arrays to be fragmented and distributed across multiple processors with a single point of access giving the programmer the illusion that all the elements are collocated on a single processor. Today's massively parallel High Productivity Computing Systems (HPCS) are characterized by a modular structure, with a large number of processing and memory units connected by a high-speed network. Locality of access as well as load balancing are primary concerns in these systems that are typically used for high-performance scientific computation. Data distributions address these issues by providing a range of methods for spreading large data sets across the components of a system. Over the past two decades, many languages, systems, tools, and libraries have been developed for the support of distributions. Since the performance of data parallel applications is directly influenced by the distribution strategy, users often resort to low-level programming models that allow fine-tuning of the distribution aspects affecting performance, but, at the same time, are tedious and error-prone. This technology presents a reusable design of a data-distribution framework for data parallel high-performance applications. Distributions are a means to express locality in systems composed of large numbers of processor and memory components connected by a network. Since distributions have a great effect on the performance of applications, it is important that the distribution strategy is flexible, so its behavior can change depending on the needs of the application. At the same time, high productivity concerns require that the user be shielded from error-prone, tedious details such as communication and synchronization.

James, Mark↗

DOE OSTI2025

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

NASA NTRS1987

Lewis inverse design code (LINDES): Users manual

The method of complex characteristics and hodograph transformation for the design of shockless airfoils was introduced by Bauer, Garabedian, and Korn and has been extended by the author to design subcritical and supercritical cascades with high solidities and large inlet angles. This new capability was achieved by introducing a new conformal mapping of the hodograph domain onto an ellipse and expanding the solution in terms of Chebyshev polynomials. A new computer code, the NASA Lewis inverse design code, was developed based on this idea. This new design code is an efficient method for the design of airfoils in cascade. In particular, the design of subcritical cascades of airfoils is a very fast, robust, and versatile process. The inverse design code can be made to interact with a turbulent boundary layer calculation to obtain airfoils with no separated flows at the design condition. This report is intended to serve as a users manual for this design code. Material previously reported by the author is included here for completeness and quick access to the user. The manual contains a description of the method followed by a discussion of the design procedure and examples. The input parameters necessary to run the code are then described and their default values given. Output listings corresponding to six different blade shapes designed with the code are given, as well as the necessary input data to reproduce the computer runs. The examples have been chosen to show that a wide range of applications can be covered with the code, ranging from supercritical propeller sections to wind tunnel turning vanes that can operate with a large inlet flow angle range.

Sanz, Jose M.↗

NASA NTRS2005

Global Survey and Statistics of Radio-Frequency Interference in AMSR-E Land Observations

Radio-frequency interference (RFI) is an increasingly serious problem for passive and active microwave sensing of the Earth. To satisfy their measurement objectives, many spaceborne passive sensors must operate in unprotected bands, and future sensors may also need to operate in unprotected bands. Data from these sensors are likely to be increasingly contaminated by RFI as the spectrum becomes more crowded. In a previous paper we reported on a preliminary investigation of RFI observed over the United States in the 6.9-GHz channels of the Advanced Microwave Scanning Radiometer (AMSR-E) on the Earth Observing System Aqua satellite. Here, we extend the analysis to an investigation of RFI in the 6.9- and 10.7-GHz AMSR-E channels over the global land domain and for a one-year observation period. The spatial and temporal characteristics of the RFI are examined by the use of spectral indices. The observed RFI at 6.9 GHz is most densely concentrated in the United States, Japan, and the Middle East, and is sparser in Europe, while at 10.7 GHz the RFI is concentrated mostly in England, Italy, and Japan. Classification of RFI using means and standard deviations of the spectral indices is effective in identifying strong RFI. In many cases, however, it is difficult, using these indices, to distinguish weak RFI from natural geophysical variability. Geophysical retrievals using RFI-filtered data may therefore contain residual errors due to weak RFI. More robust radiometer designs and continued efforts to protect spectrum allocations will be needed in future to ensure the viability of spaceborne passive microwave sensing.

microwave remote sensing↗