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At least 379 records · Page 21

Final Report for Project 13-4791: New Mechanistic Models of Creep-Fatigue Crack Growth Interactions for Advanced High Temperature Reactor Components

This project developed and validated a novel, multi-scale, mechanism-based model to quantitatively predict creep-fatigue crack growth and failure for Ni-based Alloy 617 at 800°C. Alloy 617 is a target material for intermediate heat exchangers in Generation IV very high temperature reactor designs, and it is envisioned that this model will aid in the design of safe, long lasting nuclear power plants. The technical effectiveness of the model was shown by demonstrating that experimentally observed crack growth rates can be predicted under both steady state and overload crack growth conditions. Feasibility was considered by incorporating our model into a commercially available finite element method code, ABAQUS, that is commonly used by design engineers. While the focus of the project was specifically on an alloy targeted for Generation IV nuclear reactors, the benefits to the public are expected to be wide reaching. Indeed, creep-fatigue failure is a design consideration for a wide range of high temperature mechanical systems that rely on Ni-based alloys, including industrial gas power turbines, advanced ultra-super critical steam turbines, and aerospace turbine engines. It is envisioned that this new model can be adapted to a wide range of engineering applications.

36 MATERIALS SCIENCE↗

Numerical Modeling of the Global Atmosphere

Under this grant, we continued development and evaluation of the updraft downdraft model for cumulus parameterization. The model includes the mass, rainwater and vertical momentum budget equations for both updrafts and downdrafts. The rainwater generated in an updraft falls partly inside and partly outside the updraft. Two types of stationary solutions are identified for the coupled rainwater budget and vertical momentum equations: (1) solutions for small tilting angles, which are unstable; (2) solutions for large tilting angles, which are stable. In practical applications, we select the smallest stable tilting angle as an optimum value. The model has been incorporated into the Arakawa-Schubert (A-S) cumulus parameterization. The results of semi-prognostic and single-column prognostic tests of the revised A-S parameterization show drastic improvement in predicting the humidity field. Cheng and Arakawa presents the rationale and basic design of the updraft-downdraft model, together with these test results. Cheng and Arakawa, on the other hand gives technical details of the model as implemented in current version of the UCLA GCM.

Arakawa, Akio↗

Techno-Economic Viability of Flexible Dispatch of Unconventional Geothermal Systems

Flexible geothermal operations could boost project returns through the allocation of improved power purchase agreements and/or exploitation of power price arbitrage opportunities. In this study, we investigated the techno-economic feasibility of variable flow rate control and time-of-day pricing in closed-loop geothermal systems. We considered U-shaped multilateral system configurations and modeled a variety of technical system parameters. These designs were simulated using a slender-body theory (SBT) model for transient heat transfer and fluid flow. This subsurface model was integrated into the flexible geothermal economic model (FGEM) tool to evaluate the overall flexible geothermal system techno-economics. Future hourly ambient temperature conditions were based on the Sup3rCC dataset. Published datasets were used for future hourly wholesale electricity prices. We analyzed four operating strategies: 1) baseload operation, 2) seasonal dispatch (high flow rate during summer and nominal flow rate during the rest of the year), 3) net generation maximization by varying flow rate to maximize net power output, and 4) revenue maximization by varying flow rate to maximize revenue. We ran all four scenarios for a multiloop configuration with 12 lateral passes, 7-km vertical depth and 87-km total drilling length. Furthermore, we assumed a 60 degrees C/km geothermal gradient and ambient temperature and wholesale electricity prices for New Mexico as a typical state location. The nominal flow rate was set to 80 kg/s. When considering drilling costs of $1,000/m and a discount rate of 7%, the generation maximization scenario resulted in the lowest levelized cost of electricity (LCOE) of ~$150/MWh. When considering project return on investment (ROI), defined as lifetime net income divided by upfront capital costs, all flexible operation scenarios performed better than the base case scenario. The highest ROI of 80% was obtained with the revenue maximization scenario. With drilling costs of $200/m and a discount rate of 5%, the generation maximization scenario resulted in LCOE of $49/MWh.

flexible geothermal↗

Verification and Validation of a Conceptual Model of the Auto-Rigging Payload Handling and Off-Loading System Using LEGO Technic System and Three-Dimensional Printed Parts

A conceptual model (CM) can be used to validate a concept in modeling and simulation life cycles. During the 2020-2022 Coronavirus disease 2019 (COVID-19) pandemic, for employee safety NASA implemented center closures and mandatory telework for the entire workforce. During this challenging time, engineers and researchers at NASA Langley Research Center (LaRC) looked for safe and innovative approaches and methods to continue the development of CMs for various projects. Engineers and researchers at LaRC researched Auto-Rigging Payload Handling and Off-Loading System (ARPHOLS) for payload handing and off-loading a system on an inclined lunar lander deck. In this paper, the development of a CM and the verification and validation of a conceptual idea for ARPHOLS using a LEGO Technic system and three-dimensional printed parts is presented.

Design↗

Packages of Distributed Energy Technologies Demonstrating Demand Flexibility at Community Scale

The combination of increased electric load growth across all sectors, deferred electrical infrastructure investment, and other factors resulting in variable electric power supply, has created technical challenges to maintaining a resilient and reliable grid. Many federal, regional, and local efforts are in play to modernize the electric grid, including advancing building technologies and distributed energy resources (DERs) that are utilizing smarter controls to become responsive to both occupant and grid needs. This report reviews ten pilot projects demonstrating how groups of buildings combined with behind-the-meter (BTM) DERs such as electric vehicle (EV) charging, battery storage, flexible HVAC and domestic hot water systems, and photovoltaic systems can reliably and cost effectively provide grid services. Each of the ten pilot projects aim to deliver both energy efficiency and demand flexibility (DF) while supporting load growth. The ten demonstration teams are piloting flexible DER packages across diverse communities of residential and commercial buildings to address a variety of regional grid needs. The outcomes of these pilot projects will be used to inform future scaling through utility program development. This paper characterizes the ten teams, showcasing the decision-making process used by each group to develop their packages (Section 2), the grid services they plan to deliver (Section 3), the types of DER packages selected for deployment within building sectors (Section 4) and trends between building sector, DER types, and grid services In order to achieve community scale benefits, the pilot projects must utilize aggregated control mechanisms for coordinating buildings and DERs together. Several types of coordinated control architectures have evolved amongst the teams, influenced by use type, existing market conditions, and integration type. Three coordinated controls architectures have been characterized, highlighting their use cases, benefits, challenges, and tradeoffs in their design. These insights can aid utilities, control vendors, and developers in scaling community-level energy systems (Paul, 2024). Ultimately, the technology packages selected by the ten teams will be coordinated to provide power system services, also known as grid services. Insights from these demonstrations will be useful for grid operators, regulators, aggregators and other stakeholders as they look to deploy demand flexible resources as grid services in the future. The grid services that each team is targeting for demonstration are described in Section 3 and Section 4. Methods for evaluating the grid services have been described in the paper Metrics for Evaluating Grid Service Provision from Communities of Grid-interactive and Efficient Buildings and other DER (MacDonald, 2023). To identify technology packages for demonstration, Section 2 shows that project teams used a range of analysis approaches, including building energy modeling, AMI data analysis, cost-benefit frameworks, and utility pilot data. Some teams emphasized technical modeling to quantify grid impacts and demand reduction potential, while others prioritized economic evaluations, stakeholder input, or exploratory pilots to inform deployment decisions. This diversity reflects the need to tailor selection methods to project goals, available data, and organizational context. Section 5 discusses trends between the DER technologies deployed and the grid service provisions from each team. Residential buildings (multifamily and single family) lean towards technologies that enhance energy efficiency (e.g. weatherization upgrades, smart thermostats) and onsite power generation integration (e.g. solar PV). Commercial building demonstrations prioritize technologies that ensure operational reliability (e.g. battery storage) and centralized energy management systems and optimization solutions. Teams that are deploying controllable storage-based technologies are more likely to provide grid services that require a near real-time response. Teams incorporating load shifting technologies like smart thermostats with HEMs are likely to include energy markets participation and customer bill management offerings. Campus demonstrations are adopting diverse sets of DERs to emphasize renewable generation, paired with centralized control. This section also describes technologies that were considered during project planning but ultimately excluded from final deployment. These demonstrations reveal that effective DER package design should be tailored to building type, customer segment, and construction vintage. Multifamily buildings benefit from centralized HVAC upgrades and supervisory controls, while single-family homes are well-suited for individualized technologies like solar, storage, and smart home energy monitors. Commercial and campus settings prioritize EMIS integration and load optimization. New construction enables cost-effective integration of DER-ready infrastructure, whereas retrofits require deployments aligned with owner and tenant value streams. For utility program planners, early coordination with developers and building owners, paired with segmented and modular program offerings, can improve adoption, scalability, and grid impact.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA/DOD Aerospace Knowledge Diffusion Research Project: The Technical Communications Practices of US Aerospace Engineers and Scientists: Results of the Phase 3 US Aerospace Engineering Educators Survey - Report 45

The U.S. government technical report is a primary means by which the results of federally funded research and development (R&D) are transferred to the U.S. aerospace industry. However, little is known about this information product in terms of its actual use, importance, and value in the transfer of federally funded R&D. Little is also known about the intermediary-based system that is used to transfer the results of federally funded R&D to the U.S. aerospace industry. To help establish a body of knowledge, the U.S. government technical report is being investigated as part of the NASA/DOD Aerospace Knowledge Diffusion Research Project. In this report, we summarize the literature on technical reports, present a model that depicts the transfer of federally funded aerospace R&D via the U.S. government technical report, and present the results of research that investigated aerospace knowledge diffusion vis-a-vis the technical communication practices of U.S. aerospace engineers and scientists who were members of the American Institute of Aeronautics and Astronautics (AIAA) and identified themselves as educators.

Pinelli, Thomas E.↗

Neptune Global Reference Atmospheric Model (Neptune-GRAM): User Guide

This Technical Memorandum (TM) presents the Neptune Global Reference Atmospheric Model (Neptune-GRAM) and its updated features. Neptune-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Neptune. This TM summarizes the atmospheric data model in Neptune-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Neptune-GRAM input and output files and how to interpret Neptune-GRAM results are also provided.

H L Justh↗

Uranus Global Reference Atmospheric Model (Uranus-GRAM): User Guide

This Technical Memorandum (TM) presents the Uranus Global Reference Atmospheric Model (Uranus-GRAM) and the updated features of the GRAMs. Uranus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Uranus. This TM summarizes the atmospheric data model in Uranus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Uranus-GRAM input and output files and how to interpret Uranus-GRAM results are also provided.

Uranus Global Reference Atmospheric Model↗

Jupiter Global Reference Atmospheric Model (Jupiter-GRAM): User Guide

This Technical Memorandum (TM) presents the Jupiter Global Reference Atmospheric Model (Jupiter-GRAM) and the updated features of the GRAMs. Jupiter-GRAM is an engineering-oriented atmospheric model that estimates mean values of atmospheric properties for Jupiter. This TM summarizes the atmospheric data model in Jupiter-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Jupiter-GRAM input and output files and how to interpret Jupiter-GRAM results are also provided.

atmospheric models↗

Earth Global Reference Atmospheric Model (Earth-GRAM): User Guide

This Technical Memorandum (TM) presents the Earth Global Reference Atmospheric Model (Earth-GRAM) and the updated features of the GRAMs. Earth-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Earth. This TM summarizes the atmospheric data model in Earth-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Earth-GRAM input and output files and how to interpret Earth-GRAM results are also provided.

Atmospheric Models↗

Venus Global Reference Atmospheric Model (Venus-GRAM): User Guide

This Technical Memorandum (TM) presents the Venus Global Reference Atmospheric Model (Venus-GRAM) and the updated features of the GRAMs. Venus-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Venus. This TM summarizes the atmospheric data model in Venus-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Venus-GRAM input and output files and how to interpret Venus-GRAM results are also provided.

atmospheric models↗

Mars Global Reference Atmospheric Model (Mars-GRAM): User Guide

This Technical Memorandum (TM) presents the Mars Global Reference Atmospheric Model (Mars-GRAM) and the updated features of the GRAMs. Mars-GRAM is an engineering-oriented atmospheric model that estimates mean values and statistical variations of atmospheric properties for Mars. This TM summarizes the atmospheric data model in Mars-GRAM and provides a guide for the user to obtain, set up, and run the code in various configurations. Additional details regarding the Mars-GRAM input and output files and how to interpret Mars-GRAM results are also provided.

atmospheric models↗

Understanding Adoption of a Key Soft Cost Reduction Strategy: Modeling Administrative Choices Regarding Streamlined Solar Permitting (Final Technical Report)

In the U.S., the process by which residential rooftop solar photovoltaic (PV) system installations are permitted and inspected by an “authority having jurisdiction” (AHJ) and interconnected to the grid varies across the country. As the U.S. has roughly 23,000 AHJs and 3,000 utilities with varying degrees of local autonomy, permitting, inspection, and interconnection (PI&I) heterogeneity represents a significant “soft cost” barrier to the growth of the residential solar PV market. Burkhardt et al. (2015), for example, finds that variations in local permitting procedures alone can lead to differences in average residential PV prices of approximately ${$}$0.14-${$}$0.18/W. When the authors considered jurisdictional variation in permitting plus regulatory procedures, that price differential grew to ${$}$0.64-${$}$0.93/W between the least-favorable and most-favorable jurisdictions. The objective of this project was to determine suites of PI&I reforms that fit the preferences of AHJs and utilities nationwide, as mediated through the preferences of PV installers, with the hoped-for impact of significantly improving the consistency of PI&I for solar PV across the U.S. To accomplish this objective, the project team set out to design and implement survey instruments with embedded discrete choice experiments (DCEs) that used individual PI&I reforms as attributes, with levels informed by a detailed understanding of the PI&I reforms. The analysis of the surveys was to include both defined and latent class analysis of the survey results, in order to identify different sets of AHJs and utilities that would prefer different “mass customized” SSP practice combinations. Note that this project would also have advanced the social science by applying well-established choice analysis techniques to the novel setting of public administration.

14 SOLAR ENERGY↗

Technical Report on Waveform Fit Metrics for Global Models

The new WAVEFORMS Initiative in the Ground-based Nuclear Detonation Detection (GNDD) program includes an increased emphasis on the development of Earth models and methods to predict entire seismic and acoustic waveforms more accurately. In general, this increased emphasis is predicated on the need to better characterize seismic events and provide improved model-based discrimination between event types including earthquakes and explosions. More specifically, while current moment tensor inversion methods tend to work well for larger events (M>~4) using tuned 1-D Earth models, the development of state-of-the-art 3-D models and methods is required for the prediction of shorter period waves over large areas for discrimination of smaller events. There is no standard metric for model-based waveform prediction accuracy used in the waveform modeling/inversion community. However, there are several popular waveform misfit definitions; and minimizing the corresponding objective functions is the goal of waveform inversion. Some example misfit definitions employed for adjoint waveform tomography include measures of simple travel time differences (e.g. Tape et al., 2010), cross-correlation travel time differences (e.g. Luo and Schuster, 1991), multi-taper frequency dependent methods (e.g. Lei et al., 2020), time-frequency phase misfit functions (e.g. Fichtner 2010; Rodgers et al., 2022), normalized cross-correlation methods (e.g. Tao et al., 2018), and others. In some cases, these misfit definitions also involve complicated weighting schemes and summations over multiple frequency bands making it difficult to duplicate the misfit measurement with alternative models and datasets. Although each of the misfit definitions mentioned above are useful for developing waveform models, the actual misfit values are not usually meaningful outside of a given project, model, and/or dataset. Therefore, it is difficult to understand and communicate model performance for predicting waveforms and comparing to other models and/or new model iterations with a different dataset. Therefore, there is a need for a generalized method for evaluating overall model performance that is independent from the specific misfit chosen to develop the waveform models that is also intuitive and meaningful. In this report, we describe a new metric we refer to as ‘Percent of Correlated Signal’. The following sections describe and demonstrate the metric with a case study event and a more rigorous test using a random selection of globally distributed events. While the focus here is on global tomography models, the metric is meant to applicable to regional ‘wiggle-for-wiggle’ waveform models/studies as well.

58 GEOSCIENCES↗

Technical note: Using long short-term memory models to fill data gaps in hydrological monitoring networks

Abstract. Quantifying the spatiotemporal dynamics in subsurface hydrological flows over a long time window usually employs a network of monitoring wells. However, such observations are often spatially sparse with potential temporal gaps due to poor quality or instrument failure. In this study, we explore the ability of recurrent neural networks to fill gaps in a spatially distributed time-series dataset. We use a well network that monitors the dynamic and heterogeneous hydrologic exchanges between the Columbia River and its adjacent groundwater aquifer at the U.S. Department of Energy's Hanford site. This 10-year-long dataset contains hourly temperature, specific conductance, and groundwater table elevation measurements from 42 wells with gaps of various lengths. We employ a long short-term memory (LSTM) model to capture the temporal variations in the observed system behaviors needed for gap filling. The performance of the LSTM-based gap-filling method was evaluated against a traditional autoregressive integrated moving average (ARIMA) method in terms of error statistics and accuracy in capturing the temporal patterns of river corridor wells with various dynamics signatures. Our study demonstrates that the ARIMA models yield better average error statistics, although they tend to have larger errors during time windows with abrupt changes or high-frequency (daily and subdaily) variations. The LSTM-based models excel in capturing both high-frequency and low-frequency (monthly and seasonal) dynamics. However, the inclusion of high-frequency fluctuations may also lead to overly dynamic predictions in time windows that lack such fluctuations. The LSTM can take advantage of the spatial information from neighboring wells to improve the gap-filling accuracy, especially for long gaps in system states that vary at subdaily scales. While LSTM models require substantial training data and have limited extrapolation power beyond the conditions represented in the training data, they afford great flexibility to account for the spatial correlations, temporal correlations, and nonlinearity in data without a priori assumptions. Thus, LSTMs provide effective alternatives to fill in data gaps in spatially distributed time-series observations characterized by multiple dominant frequencies of variability, which are essential for advancing our understanding of dynamic complex systems.

54 ENVIRONMENTAL SCIENCES↗

Verification and Validation of a Conceptual Model of the Auto-Rigging Payload Handling and Off-Loading System Using LEGO Technic System and Three-Dimensional Printed Parts

A conceptual model (CM) can be used to validate a concept in modeling and simulation life cycles. During the 2020-2022 Coronavirus disease 2019 (COVID-19) pandemic, for employee safety NASA implemented center closures and mandatory telework for the entire workforce. During this challenging time, engineers and researchers at NASA Langley Research Center (LaRC) looked for safe and innovative approaches and methods to continue the development of CMs for various projects. Engineers and researchers at LaRC researched Auto-Rigging Payload Handling and Off-Loading System (ARPHOLS) for payload handing and off-loading a system on an inclined lunar lander deck. In this paper, the development of a CM and the verification and validation of a conceptual idea for ARPHOLS using a LEGO Technic system and three-dimensional printed parts is presented.

Payload offloading↗

fmdtools Tutorial: Intro to Resilience Modelling, Simulation, and Visualization in Python With fmdtools

This workshop will cover the basics of using the fmdtools package for the simulation of hazardous scenarios for resilience simulation. The fmdtools simulation package is an open-source python toolkit for simulating the dynamic response of a system to internal and externally-driven hazardous scenarios, including faults and environmental conditions, that can be used to analyze the risks related to these hazards. Prior to the development of fmdtools, researchers had to either adapt an (often limited) propriety toolkit or develop their own design/simulation/analysis codes to develop their models of hazardous events, a significant technical burden to both (1) leveraging resilience modeling methodologies and (2) extending these methodologies with their own contributions. The fmdtools package provides a number of model constructs and simulation and analysis methods to enable the designer to focus to solely on their modeling case-study while still enabling a significant degree of model expressiveness and adaptability via Python-based model definition. This tutorial will present the setup of fmdtools and a high-level overview of its use, as well as some simple examples for understanding how to leverage its modelling, simulation, and analysis capabilities. Familiarity with jupyter notebook and basic python will be assumed.

Daniel Hulse↗