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Research and development at NLR supports the U.S. Department of Energy's Vehicle Technologies Office in advancing low-cost, abundant, and secure energy technologies to accelerate a more affordable, reliable, efficient, and globally competitive U.S. transportation system.
The Microscopy and Characterization Suite (MaCS) laboratory at the Critical Materials and Energy Systems Innovation Center (CMESIC), formerly the Center for Advanced Energy Studies (CAES) and the National Synchrotron Light Source-II (NSLS-II) at Brookhaven National Laboratory (BNL) partner with the Nuclear Science User Facilities (NSUF). These partnerships provide funding that allows researchers to access these facilities at no cost for studying irradiation effects on nuclear fuels and materials. Through NSUF, both MaCS and NSLS-II support post-irradiation examination (PIE) and irradiation activities for NSUF Rapid Turnaround Experiments (RTE) and NSUF Consolidated Innovative Nuclear Research (CINR) awards.
Advanced Research on Integrated Energy Systems (ARIES) at the National Laboratory of the Rockies (NLR) is the U.S. Department of Energy's (DOE's) test bed for energy system demonstration and de-risking. ARIES comprises the largest collection of physical and digital assets in the DOE laboratory complex, supporting flexible configuration across a broad range of energy scenarios. In Fiscal Year 2025, ARIES provided a platform for system-level research to anticipate and address future energy needs in energy security, system reliability, and technology deployment.
Timing is critical for species that migrate seasonally, as timing mismatches can lead to reduced reproductive success and population declines. We investigated the effect of breeding latitude on the migration timing of a long-distance migratory songbird (Purple Martin, Progne subis subis) by using light-level geolocators deployed across breeding sites between 26° and 53° latitude (n = 329). We used nesting data (1st egg dates; n=28,165) to explore latitudinal patterns in the timing of breeding. Using generalized linear mixed models (GLMMs) we found that breeding latitude was highly associated with timing around the calendar, explaining population-level timing across both spring and fall migration. Populations breeding at more northern latitudes migrated later in fall (mean days/degree latitude =2), in spring (mean days/degree latitude =3), and nested later (days/degree latitude = 3) than populations breeding at more southern latitudes. Generalized additive mixed models (GAMMs) revealed significant non-linearity between breeding latitude and spring and fall migration timing, and the timing of nesting. In spring, the most northern breeders (> 40 degrees N) were more synchronous in their timing, departing their nonbreeding sites and arriving earlier at their breeding sites relative to their breeding latitude. These most northern breeders also had similar nest timing and fall migration departure timing. Breeding latitude was also associated with seasonal partitioning of migratory and sedentary periods. The most northern breeders spent 10% more time on fall migration, 2% more at wintering grounds, 1% more on spring migration, and 13% less time at their breeding sites. Our results support the notion that selection for timing at breeding latitudes can have year-round effects on the timing of seasonal events in long-distance migratory songbirds. Future studies should examine whether these timing patterns associated with latitude limit phenotypic responses to climate change.
While the primary role of window attachments is often to moderate glare and solar heat gains, they are also able to provide additional daylight to interior spaces. For this purpose, a variety of daylight-redirecting window systems have been developed over the past 150 years. Fixed reflective systems (slats/light shelves) or prismatic systems that rely on total internal reflection work well under specific solar conditions, but generally sacrifice performance over a much wider range of incident solar angles and sky conditions. Dynamic systems - typically reflective slats - are more responsive to sun angles but have not been able to achieve optimal performance for glare and daylight redirection efficiency. A previous investigation into an adjustable, reflective blind concept first conceived of in the late 1970s showed promise but was not reduced to practice due to lack of adequate simulation and analysis tools. In this paper, this concept is further developed and its energy and visual comfort performance evaluated for four mid-latitude, temperate climates using ray-tracing simulation techniques. Overall, results indicate significant potential lighting energy savings when compared with conventional automated reflective blinds (2.1–4.9 kWh/(m 2 ·a), or 14%–42%, depending on climate and orientation) or, especially, manually-operated matte white venetian blinds (1.4–7.9 kWh/(m 2 ·a), or 9%–54%, depending on climate and orientation), while maintaining acceptable or better visual comfort conditions throughout the interior space.
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The Microtops II ozonometer has been deployed to continuously measure the total column ozone (TCO), pre-cipitable water content (PWC) and aerosol optical thickness (AOT) at Atigre village (16.74° N, 74.37° E, 604 m above sea level, masl) located on the southeastern slope of Indian western Ghats. The Microtops II ozonometer measurements during the period from September 2017 to June 2018 were analyzed along with the retrieved products of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellites and also the ERA-interim reanalysis model. We found that the TCO (or PWC) data from the OMI (or MODIS) and the ERA reanalysis model data products are in good agreement. The mea-surements showed strong seasonal variability such that TCO was lowest in the winter season but increased in the summer season, and both PWC and AOT were lowest in the post-monsoon season and increased in the summer season. In continuous ERA-interim reanalysis TCO observations, we found the three types of periodicities in the daily mean TCO as well as PWC (i) The weekly (7 days), (ii) quasi-biweekly (14 to 16 days), (iii) Madden Julian Oscillations (MJO) (30–60 days) oscillations. These oscillations depend on the periodic weather changes in the troposphere. We also observe that the average day to day variability in daily mean TCO observations in the observational period is about 1.4%, 1.1%, 2.62% in the Microtops II ozonometer, ERA-interim reanalysis, and OMI data respectively. We found the positive correlation between daily mean AOT and PWC in all seasons (except monsoon), which is maximum in the winter season, showing the hygroscopic nature of aerosols. The sources of water vapor and aerosol at our location are also studied using back-trajectory analysis.
Microclimate acts as a strong filter on species performance in restored and regenerating forests, particularly in seasonally dry tropical forests (SDTF). Yet few studies have measured microclimate patterns across succession in SDTF. Furthermore, although dynamic vegetation models simulate microclimate, evaluation of these simulated variables with field observations has been relatively uncommon. Here, we investigated the seasonal patterns of soil temperature and soil water in naturally regenerated and planted successional vegetation in SDTF in Costa Rica and Puerto Rico, using complementary approaches of intensive field observations and simulation modeling with the Ecosystem Demography model. We found that plots representing later successional stages were wetter on average, but only during the dry season. During the wet season, mean soil water did not differ across vegetation types, but open, early successional vegetation experienced more frequent extreme wet and dry conditions than older forest and plantations. Soil temperature tended to decline with forest structure, and later successional vegetation also experienced less extreme daily temperature fluctuations. Basal area and leaf area index were the best predictors of differences in soil water and temperature across plots. Model simulations were consistent with observations of wet season soil temperature and soil water, but the model failed to reproduce dry season soil moisture dynamics, suggesting that further work is needed to reduce model biases in microclimate variables. Collectively, our results imply that common assumptions about how microclimates influence successional processes in SDTF should be revisited.
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Solar power for electricity production comes from either photovoltaics or concentrating solar power plants. The former has seen rapid growth and expansion due to the rapid fall in global prices, while the latter has seen moderate growth due to ability to cheaply store thermal energy for later use. Hybridization, or combining photovoltaics with concentrating solar power represents a potential way for lowering cost while enabling long term storage. Over 5 GW of capacity exist worldwide using parabolic trough style technology for concentrating solar power which presents a unique option for optimization in the form of a photovoltaic retrofit. While it is possible to analyze the performance with detailed physics models, it is necessary to create a model that can handle simulating the plant level performance to fully understand the potential performance. Here, the first utility scale plant level model of a hybrid photovoltaic-concentrating solar power plant is developed. The model is applied to existing concentrating solar power plants around the world utilizing RP-3 mirrors without thermal energy storage to understand the impact on electricity production. Model results indicate that the photovoltaic retrofit can increase yearly electricity production by up to 30% for plants with solar multiples exceeding 1.5, and that increasing the fraction of solar energy reflected further increases the yield. The increased electrical production declines as the plant solar multiple is decreased. The minimum LCOE observed was $0.07/kWh for plants with larger solar multiple and fraction of solar energy reflected to the PV is 50% of the total aperture.