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

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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Spatiotemporal Modeling of Real World Backsheets Field Survey Data: Hierarchical (Multilevel) Generalized Additive Models: Preprint

Assessing photovoltaic module backsheet durability is critical to increasing module lifetime. Lab based accelerating testing has recently failed to predict large scale failures of widely adopted polymeric materials. Field surveyed data is critical to assess the performance of component lifetime. Using a documented field survey protocol, 13 field surveys where conducted. Each measurement is encoded with it's spatial location in respect to the other modules. By combining field survey data on degradation predictors with real time satellite weather data, data-driven predictive models of backsheet degradation were trained. LOESS models were constructed to investigate the spatial dependence of measurements. It was found that micro-climatic effects like treelines, ground surface changes, and elevation changes effected the magnitude and variance of the measurements. A GAM model was created to predict the value of degradation based on measured predictors. The model includes variables on the climate of the system and the location of each measurement in the PV mounting structure. The model performed well with an adj:R2 of 0:95 for yellowness index prediction. The model was cross-validated using k-folds.

backsheet↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
DOE OSTI2023

Enhanced material shock using spatiotemporal laser pulse formatting

The present disclosure relates to a laser based system for laser peening a workpiece. The system has a pulse laser configured to generate laser pulses and a controller for controlling operation of the pulse laser. The controller is further configured to control the pulse laser to cause the pulse laser to generate at least one of the laser pulses with a spatio-temporally varying laser fluence over a duration of the at least one of the laser pulses.

Matthews, Manyalibo Joseph↗
DOE OSTI2023

21-Year Modeled Spatiotemporal Low-Level Jet Climatology Along the U.S. Mid-Atlantic Coast

Offshore wind farms are influenced by a variety of meteorological phenomena, ranging in spatial and temporal extent. One of these phenomena, the low-level jet (LLJ), is defined as a local maximum in wind speed with height in the planetary boundary layer, exhibiting a "nose-like" structure usually in the lowest few hundred meters above the surface. This vertical extent of LLJs may coincide with the rotor-swept area of a wind turbine, thus having implications for potential power production and mechanical loading. Previous studies in this area based on observations have confirmed the prevalence of LLJs here, with implications on power generation, wind turbine loads, and wake recovery depending on the LLJ characteristics, such as nose height and what part of the wind turbine power curve is being impacted.

LLJ↗
DOE OSTI2022

Spatiotemporal Structure in Intense THz Pulsed Beams

Optically generated terahertz radiation, with gigavolt per meter (GV/m) electric fields accessible in tabletop experiments, provides a promising source of accelerating gradients for future particle accelerator applications. Manipulation and characterization of radiation is essential for efficiently producing high fields and effectively delivering them to an accelerating structure or interaction region. The talk will cover a method of generating and characterizing high quality and structured terahertz pulsed laser beams for compact particle acceleration.

Hine, George↗