Search NASA⌕ Search

SEARCH · Search NASA

Results for “development studies”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44

Pairing Directional Solar Inputs From Ray Tracing to Solar Receiver/Reactor Heat Transfer Models on Unstructured Meshes: Development and Case Studies

A novel method for pairing surface irradiation and volumetric absorption from Monte Carlo ray tracing to computational heat transfer models is presented. The method is well-suited to directionally and spatially complex concentrated radiative inputs (e.g., solar receivers and reactors). The method employs a generalized algorithm for directly mapping absorbed rays from a Monte Carlo ray tracing model to boundary or volumetric source terms in the computational mesh. The algorithm is compatible with unstructured, two and three-dimensional meshes with varying element shapes. Four case studies were performed on a directly irradiated, windowed solar thermochemical reactor model to validate the method. The method was shown to conserve energy and preserve spatial variation when mapping rays from a Monte Carlo ray tracing model to a computational heat transfer model in ansys fluent.

14 SOLAR ENERGY↗

Study of the development of relativistic plasma bunches in a long mirror trap by optical and X-ray imaging and numerical simulations

The work presents experimental results demonstrating the feasibility of autoresonance acceleration of electrons in a long mirror trap with a reverse magnetic field. It is shown that gyromagnetic autoresonance results in the formation of a plasma bunch with average electron energy of several hundred keV, which is confined for a long time in the trap. The results of computer simulations of the regime of reverse gyromagnetic autoresonance agree well with the experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Final Report on Community Solar Design Models for Consumer, Industry, & Utility Success

Since the inception of the first community solar program in 2006, a number of different utility, solar industry and consumer driven community solar program models have emerged across the country with varying regulatory and solar market frameworks behind them. There is little consistency in how programs are administered, participant benefits are assigned, and customers are charged for participation. Further, while it is regularly speculated that community solar programs meet the needs of customers, no such consumer research has been completed against different community solar program models. This collaborative research effort addressed three primary issues: Program design models are numerous and evolving, with varying degrees of applicability across different state policy, utility regulatory, and solar market types. The agents, transaction methods, and accruing costs and benefits are highly variable and largely built on anecdotally successful model evolution. ‘Community solar’ (shared/group solar, solar gardens, etc.) has become a catch-all concept that means different things to different stakeholders, limiting constructive program development and growth. Everything from green pricing programs to remote net metering to metering aggregation has been framed as community solar. Consumer research on individual concepts and program models has been done, but no comprehensive and comparative market research on the broader design models and attributes has been performed. SEPA’s collaborative research effort on Community Solar Design Models for Consumer, Industry, & Utility Success is premised on the principle that greater standardization of community solar models and better understanding of consumer interests are key underpinnings of increased community solar deployment. Utilizing a cross-sectional multi-stakeholder working group, as well as focus groups and surveys, webinars, targeted outreach, and other tools, this project aims to expand the community solar knowledge base, facilitate information exchange, identify opportunities for standardization and improvement, determine what consumers’ interests are and how best to message to them, promote the research results within the solar and utility industries, and advance key opportunities for strategic deployment plans for community solar. A summary of these key takeaways/lessons learned during the grant period include: Siting of system should be evaluated up-front in the process Engage stakeholders collaboratively and early to help ensure the best chance for a successful program IT/billing departments must have a seat at the design table Establish upfront target objectives with respect to residential and commercial program access levels helps ensure program success Balance trade-offs to manage utility and developer risk with customer participation carefully to optimize pricing and sizing the program offering Over the course of the 42 month grant period, SEPA and its project team conducted a series of activities all designed to accelerate the number and size of community solar programs across the country. These activities included: Community Solar Program Design Models (2 reports) – SEPA, in collaboration with its projects team, the Coalition for Community Solar Access, and over 60 administrators of actual community solar programs, developed two reports providing hard data on the developments of community solar. These reports touched on program performance, quantity and type of programs, and program design steps, among other aspects. The reports collectively received over 2000 unique downloads. Market Research Report – SEPA, in collaboration with The Shelton Group, conducted a series of national surveys and focus groups to identify what customers were looking for in a community solar offering. The resulting report, “What the Community Solar Customer Wants”, received over 1,000 unique downloads. Technical Assistance Projects – SEPA supported 8 organizations who were pursuing community solar programs. Based on this support, over 5.7 MWs of new solar capacity have been developed. Technical Assistance Case Studies – SEPA developed two case studies detailing the technical assistance work in Fremont, NE Department of Utilities and the public power arm of Minster Ohio. These two reports have received 1,002 unique downloads. Webinar – SEPA hosted two webinars on community solar which collectively received 743 participants. The webinars focused on disseminating the findings of the research conducted under this project, as well as the research conducted in separate solar market pathways projects. Community Solar Design Workshops – 120 registrants learned about the trends in community solar and participated a business case exercise to design their own programs.

14 SOLAR ENERGY↗

Sludge Batch 10 Frit Development and Variability Study Matrix Design

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26H, and Alternate Feed Stock-2 (AFS-2). H-Canyon also had a need to discard Sodium Reactor Experiment (SRE) material that was stored in Tanks 16.3 and 16.4. Savannah River Remediation (SRR) added a portion of the SRE material to Sludge Batch 9 (SB9) in Tank 40 and the remainder was added to SB10 that is currently being prepared in Tank 51. In support of sludge batch preparation and qualification efforts, SRR requested that the Savannah River National Laboratory (SRNL) complete the following tasks based on the SB10 projections provided by the SRR System Planning group.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of Material Studies at the LANL UCN Facility Focusing on Actinide Hydriding and Fission Damage

The aging of as-built actinide surfaces in static and dynamic environments is a complex problem of high importance to LANL’s core mission. Many standard material science tools used to study this problem are ideal for highly controlled, lab-made samples. The goal of this work is to use ultracold neutrons to bridge the gap between lab made and as-built surface aging studies. This capability is unique to LANL and will support our core mission.

36 MATERIALS SCIENCE↗

KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N<sub>2</sub>O emission using data from mesocosm experiments

Abstract. Agricultural nitrous oxide (N2O) emission accounts for a non-trivial fraction of global greenhouse gas (GHG) budget. To date, estimating N2O fluxes from cropland remains a challenging task because the related microbial processes (e.g., nitrification and denitrification) are controlled by complex interactions among climate, soil, plant and human activities. Existing approaches such as process-based (PB) models have well-known limitations due to insufficient representations of the processes or uncertainties of model parameters, and due to leverage recent advances in machine learning (ML) a new method is needed to unlock the “black box” to overcome its limitations such as low interpretability, out-of-sample failure and massive data demand. In this study, we developed a first-of-its-kind knowledge-guided machine learning model for agroecosystems (KGML-ag) by incorporating biogeophysical and chemical domain knowledge from an advanced PB model, ecosys, and tested it by comparing simulating daily N2O fluxes with real observed data from mesocosm experiments. The gated recurrent unit (GRU) was used as the basis to build the model structure. To optimize the model performance, we have investigated a range of ideas, including (1) using initial values of intermediate variables (IMVs) instead of time series as model input to reduce data demand; (2) building hierarchical structures to explicitly estimate IMVs for further N2O prediction; (3) using multi-task learning to balance the simultaneous training on multiple variables; and (4) pre-training with millions of synthetic data generated from ecosys and fine-tuning with mesocosm observations. Six other pure ML models were developed using the same mesocosm data to serve as the benchmark for the KGML-ag model. Results show that KGML-ag did an excellent job in reproducing the mesocosm N2O fluxes (overall r2=0.81, and RMSE=3.6 mgNm-2d-1 from cross validation). Importantly, KGML-ag always outperforms the PB model and ML models in predicting N2O fluxes, especially for complex temporal dynamics and emission peaks. Besides, KGML-ag goes beyond the pure ML models by providing more interpretable predictions as well as pinpointing desired new knowledge and data to further empower the current KGML-ag. We believe the KGML-ag development in this study will stimulate a new body of research on interpretable ML for biogeochemistry and other related geoscience processes.

54 ENVIRONMENTAL SCIENCES↗