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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

PreSens Dissolved Oxygen and Temperature Data, Old Woman Creek National Estuarine Research Reserve, Huron, OH, 2022-07-06 to 2023-12-15

This dataset contains collected dissolved oxygen (DO) and temperature measurements of the air, surface water, and underlying soil of a wetland at Old Woman Creek Estuarine Research Reserve in Huron, OH. Dissolved oxygen and temperature measurements were made in the first few centimeters of wetland sediment to assess how oxygen profiles changed over time with hydrological events. Measurements taken outside of the sediment were taken as comparison. Measurements were taken by hand with a PreSens Fibox 4 transmitter, paired with an oxygen dipping probe and temperature sensor, at each field outing. Measurements were taken approximately every 2 weeks around 10 AM EST. The PreSens_DO_Temp_Datafile.csv contains the recorded measurements, and the PreSens_InstallationMethods.csv describes the deployment of the sensor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

miniDOT Logger Dissolved Oxygen and Temperature Data of Wetland Surface Water, Old Woman Creek NERR, Huron, OH, 2022-06-15 to 2023-12-15

This dataset contains timeseries data of dissolved oxygen (DO) and temperature measurements of the surface water in a wetland at Old Woman Creek Estuarine Research Reserve in Huron, OH. Dissolved oxygen and temperature measurements were made in the overlying water column of wetland to assess how oxygen changed over time with hydrological events. Measurements were collected by a miniDOT Logger. Data was collected over 1.5 years (June 2022 to December 2023). The miniDOT_DO_Temp_DataFile.csv contains the DO and temperature measurements that were collected every 10 minutes. The water levels of the site varied over-time as the wetland flooded and dried. So, sometimes the miniDOT logger would be out of the water column, resulting in high oxygen levels. Depth of the water column was recorded at every in-person site visit. The miniDOT_Depth_DataFile.csv contains the hand-measured surface water depth measurements for comparison to the logger-collected data. Information on the deployment and measurement methods can be found in the miniDOT_InstallationMethods.csv file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Soil Core Chemistry of Wetland, Old Woman Creek National Estuarine Research Reserve, Huron, OH, 2023-10-24 to 2024-05-20

This dataset contains the chemistry data of soil samples collected from a wetland, referred to as The Cove, at Old Woman Creek Estuarine Research Reserve in Huron, OH. Soil core extractions were performed to analyze what nutrient and/or metal constituents were present at different depths and what biogeochemical activity this could indicate. Three soil cores were collected at three locations within The Cove. The soil cores were removed from their core tubing and were cut into 4 segments down the length (or depth) of the core: top to 1-inch deep, from 1 inch to 5 inches, 5 inches to 7 inches, and 7 inches to the bottom of the core (approximately 10 inches). These soils segments were each homogenized and sub-sampled for various chemical analyses. Soil chemistry measurements are reported in the SoilChem_DataTable.csv file. Collection information about the samples can be found within the SoilChem_SampleMetdata.csv file. All files associated with this dataset are listed in the SoilChem_FLMD.csv file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Hyperspectral leaf reflectance of grasses varies with evolutionary lineage more than with site

Abstract To predict ecological responses at broad environmental scales, grass species are commonly grouped into two broad functional types based on photosynthetic pathway. However, closely related species may have distinctive anatomical and physiological attributes that influence ecological responses, beyond those related to photosynthetic pathway alone. Hyperspectral leaf reflectance can provide an integrated measure of covarying leaf traits that may result from phylogenetic trait conservatism and/or environmental conditions. Understanding whether spectra‐trait relationships are lineage specific or reflect environmental variation across sites is necessary for using hyperspectral reflectance to predict plant responses to environmental changes across spatial scales. We measured hyperspectral leaf reflectance (400–2400 nm) and 12 structural, biochemical, and physiological leaf traits from five grass‐dominated sites spanning the Great Plains of North America. We assessed if variation in leaf reflectance spectra among grass species is explained more by evolutionary lineage (as captured by tribes or subfamilies), photosynthetic pathway (C 3 or C 4 ), or site differences. We then determined whether leaf spectra can be used to predict leaf traits within and across lineages. Our results using redundancy analysis ordination (RDA) show that grass tribe identity explained more variation in leaf spectra (adjusted R 2 = 0.12) than photosynthetic pathway, which explained little variation in leaf spectra (adjusted R 2 = 0.00). Furthermore, leaf reflectance from the same tribe across multiple sites was more similar than leaf reflectance from the same site across tribes (adjusted R 2 = 0.12 and 0.08, respectively). Across all sites and species, trait predictions based on spectra ranged considerably in predictive accuracies ( R 2 = 0.65 to <0.01), but R 2 was >0.80 for certain lineages and sites. The relationship between Vc max , a measure of photosynthetic capacity, and spectra was particularly promising. Chloridoideae, a lineage more common at drier sites, appears to have distinct spectra‐trait relationships compared with other lineages. Overall, our results show that evolutionary relatedness explains more variation in grass leaf spectra than photosynthetic pathway or site, but consideration of lineage‐ and site‐specific trait relationships is needed to interpret spectral variation across large environmental gradients.

Pau, Stephanie [Department of Geography University↗
DOE OSTI2025

Impact of nutritional history, prey quality, and quantity on grazing and photophysiological responses in the mixoplanktonic dinoflagellate Karenia brevis

The mixotrophic toxic dinoflagellate Karenia brevis forms red tides almost annually along Florida's Gulf coast. We hypothesize that the nutritional status and abundance of its prey, the picocyanobacterium Synechococcus , will affect its feeding rates and growth responses, with implications for bloom dynamics. This study investigated how prey nutritional quality and quantity (absolute and relative) impact grazing rates by K. brevis initially exponentially growing and in nitrogen (N)-limited conditions, and how grazing, in turn, affects the photophysiological responses of predator and prey. Prey quality was manipulated by providing Synechococcus grown under different ratios of N : phosphorus (P). Synechococcus quality did not significantly affect ingestion rates (measured as prey death rate) but grazing rates increased with increasing prey : grazer ratios (R 2 = 0.7). Compared to control, the growth of exponentially growing grazers doubled when Synechococcus was provided, whereas there was no growth enhancement when Synechococcus of varying qualities was provided to N-limited, chemostat-seeded grazers. Despite this doubled growth, 15 N labeling of the prey and nanoscale secondary ion mass spectrometry (nanoSIMS) detected low Synechococcus -N transfer into grazer biomass after 3 d (< 1% on a cell basis). This suggests the potential of grazers benefiting from alternative N sources (e.g., microbiome-N) or other constituents (e.g., vitamins or metals) not measured in this study. Prey photosynthetic efficiency declined under grazing conditions, demonstrating that grazers can directly affect prey abundance through grazing and indirectly affect prey photophysiology, potentially via allelopathy, supporting previous findings of an inverse relationship between grazers and prey along the Florida Gulf Coast.

Ahn, So Hyun [Univ. of Maryland, Cambridge, MD (Un↗
DOE OSTI2025

Ecological acclimation: A framework to integrate fast and slow responses to climate change

Ecological responses to climate change occur across vastly different time-scales, from minutes for physiological plasticity to decades or centuries for community turnover and evolutionary adaptation. Accurately predicting the range of ecosystem trajectories will require models that incorporate both fast processes that may keep pace with climate change and slower ones likely to lag behind and generate disequilibrium dynamics. However, the knowledge necessary for this integration is currently fragmented across disciplines. We develop ‘ecological acclimation’ as a unifying framework to emphasize the similarity of dynamics driven by processes operating on dramatically different time-scales and levels of biological organization. The framework focuses on ecoclimate sensitivities, measured as the change in an ecological response variable per unit of climate change. Acclimation processes acting at different time-scales cause these sensitivities to shift in magnitude and even direction over time. We highlight shifting ecoclimate sensitivities in case studies from diverse ecosystems, including terrestrial plant communities, coral reefs and soil microbiomes. Models predicting future ecosystem states inevitably make assumptions about acclimation processes; these assumptions must be explicit for users to evaluate whether a model is appropriate for a given forecast horizon. Similarly, decision frameworks that clearly account for multiple acclimation processes and their distinct time-scales will help natural resource managers plan for ecological impacts of climate change from years to many decades into the future. We outline a synthetic research programme focused on the time-scales of ecological acclimation to reduce uncertainty in ecological forecasts.

climate adaptation↗
DOE OSTI2025

Habitat specialization and edge effects of soil microbial communities in a fragmented landscape

Abstract Soil microorganisms play outsized roles in nutrient cycling, plant health, and climate regulation. Despite their importance, we have a limited understanding of how soil microbes are affected by habitat fragmentation, including their responses to conditions at fragment edges, or “edge effects.” To understand the responses of soil communities to edge effects, we analyzed the distributions of soil bacteria, archaea, and fungi in an experimentally fragmented system of open patches embedded within a forest matrix. In addition, we identified taxa that consistently differed among patch, edge, or matrix habitats (“specialists”) and taxa that showed no habitat preference (“nonspecialists”). We hypothesized that microbial community turnover would be most pronounced at the edge between habitats. We also hypothesized that specialist fungi would be more likely to be mycorrhizal than nonspecialist fungi because mycorrhizae should be affected more by different plant hosts among habitats, whereas specialist prokaryotes would have smaller genomes (indicating reduced metabolic versatility) and be less likely to be able to sporulate than nonspecialist prokaryotes. Across all replicate sites, the matrix and patch soils harbored distinct microbial communities. However, sites where the contrasts in vegetation and pH between the patch and matrix were most pronounced exhibited larger differences between patch and matrix communities and tended to have edge communities that differed from those in the patch and forest. There were similar numbers of patch and matrix specialists, but very few edge specialist taxa. Acidobacteria and ectomycorrhizae were more likely to be forest specialists, while Chloroflexi, Ascomycota, and Glomeromycota (i.e., arbuscular mycorrhizae) were more likely to be patch specialists. Contrary to our hypotheses, nonspecialist bacteria were not more likely than specialist bacteria to have larger genomes or to be spore‐formers. We found partial support for our mycorrhizal hypothesis: arbuscular mycorrhizae, but not ectomycorrhizae, were more likely to be specialists. Overall, our results indicate that soil microbial communities are sensitive to edges, but not all taxa are equally affected, with arbuscular mycorrhizae in particular showing a strong response to habitat edges. In the context of increasing habitat fragmentation worldwide, our results can help inform efforts to maintain the structure and functioning of the soil microbiome.

Winfrey, Claire C. [Department of Ecology and Evol↗
DOE OSTI2024

Impacts of Legacy and Contemporary Nitrogen Inputs on N 2 O and CO 2 Emissions in Miscanthus and Maize Cultivated Soils

ABSTRACT Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteus (M×g) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N 2 O) and carbon dioxide (CO 2 ) emissions, as well as key N cycling genes in soils where M×g and maize were grown. A 150‐day soil incubation experiment was conducted using soils from a long‐term M×g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha −1 year −1 ) and a contemporary amendment (60 mg N kg −1 ) with negative control (0 mg N kg −1 ). We observed significant increases in cumulative N 2 O emissions in Mxg soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amo A gene abundance, which plays a significant role in nitrification in nutrient‐rich soils, also increased with higher legacy fertilization rates in M×g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N 2 O emissions, but cumulative CO 2 emissions and amo A gene abundance significantly increased. The abundances of nor B genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N 2 O emissions, particularly for perennial bioenergy crops.

09 BIOMASS FUELS↗
DOE OSTI2026

Science & Technology Review June 2026: Predicting Tsunamis

At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Characterizing Near-Surface Moisture Increase during the Clear-Sky Afternoon-to-Evening Transition Using a Single-Column Model

The afternoon-to-evening transition is the period when the atmospheric boundary layer transitions from convective to stable conditions. One noticeable feature during this transition period is the rapid increase in water vapor concentration near the surface. However, the mechanism behind the increase in water vapor remains poorly understood. This study investigated the processes contributing to the water vapor increase and the impacts of the land cover and horizontal advection on the water vapor increase using a single-column model for the clear-sky condition. Numerical experiments were conducted on three cases at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. Evapotranspiration was found to be the main moisture source to the water vapor increase, and that change of the near-surface vertical temperature gradient from negative to positive is the trigger for this increase during the afternoon-to-evening transition. This is because the near-surface turbulence divergence term decreases due to the change in the buoyancy profile caused by vertical temperature gradient change. The impact of horizontal advection on water vapor varies, and it can either lead to an increase or a decrease in water vapor, depending on the spatial horizontal water vapor gradient. This study also found that land cover can influence the timing of the water vapor increase since different land covers may have different Bowen ratios. Water vapor increases earlier under conditions with smaller Bowen ratios compared to those with larger values.

Atmosphere-land interaction↗
DOE OSTI2020

Aligned FTICR-MS, Respiration, and Biochemical Transformation Data from Columbia River Sediment Incubations Associated with: “Carbon Limitation Leads to Thermodynamic Regulation of Aerobic Metabolism”

Columbia River hyporheic zone sediments from the Hanford Site 300 Area in eastern Washington were incubated in a full factorial design with different organic matter (OM) amendments. The aim of the experiment was to test the influence of OM thermodynamics on aerobic respiration across different organic carbon pools and concentrations. This dataset is comprised of (1) a csv with high resolution characterization of dissolved organic matter via 12 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) analyzed through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory), (2) a csv with sample IDs, replicates, amendments, dissolved oxygen (DO) measurements, and sampling time points, (3) a csv with sample IDs, replicates, respiration rates, FTICR summary metrics, and relative abundance of chemical classes; and (4) a csv with the number of chemical transformations in each sample replicate (microcosm). The data are associated with the publication “Carbon Limitation Leads to Thermodynamic Regulation of Aerobic Metabolism” published in ES&T Letters (Garayburu-Caruso et al., 2020). Please use the data package’s DOI to cite the data package. We ask that you acknowledge the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Subsurface Biogeochemical Research (SBR) program when using the data. All data are free to be used for any purpose, such as for manuscripts, presentations, and grant proposals. There is no obligation to include data package authors as co-authors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Organic Matter Concentration and Composition in November 2021 and April 2022 from 12 Streams Impacted by the 2020 Holiday Farm Fire (v2)

This dataset represents results from a field study aiming to understand storm induced transport of pyrogenic materials to streams impacted by varying degrees of burn severity. Time series samples were collected at 5 sites within the McKenzie River Watershed (Oregon, USA) whose catchment were each completely engulfed by the 2020 Holiday Farm Fire. An additional 7 sites were sampled once during the storm. The samples were collected during storm events in November 2020, January 2021, November 2021, and April 2022. Samples were characterized for benezenepolycarboxylic acids (BPCA), ultra-high resolution mass spectrometry, dissolved organic carbon and optics (absorbance and fluorescence). Fourier-transform ion cyclotron resonance mass spectrometry (FTICR) and dissolved organic carbon data from the November 2020 (referred to as “EWEB_2020”) sampling can be found in a separate data package (doi: 10.15485/1869708). NOTE: The 2020 samples were run on FTICR-MS in two unique instances. The first run can be found in the previous data package (EWEB_2020). The second run is included in this data package. These samples were run for a second time so that the data were more directly interoperable with the other samples in this data package. We have not done any investigation into the differences/similarities between these datasets and the previously ran/published data in the other data package. This data package was originally published in November 2024. It was updated in April 2025 (v2; new and modified files). See the change history section below for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset contains (1) file-level metadata; (2) data dictionary; (3) data package readme; (4) metadata; (5) methods information; (6) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data; (7) excitation emission matrix (EEM) methods; and (8) a sub-folder with processed EEM data (9) benzene polycarboxylic acid (BPCA) concentration data; (10) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) methods; and (11) folder of high-resolution characterization of organic matter via 12 Tesla FTICR-MS generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The EEMs sub-folder contains two additional folders; the Absorbance and Fluorescence folders which contain the processed EEMs absorbance and fluorescence data respectively. This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Usage of Observing System Simulation Experiments and Reinforcement Learning to Optimize Experimental Design and Operation

Various organizations regularly conduct field campaigns across the globe designed to probe and improve atmospheric process understanding. However, these campaigns are mostly designed ad-hoc, and rely on anecdotes and knowledge of what was successful in previous campaigns. Such ad-hoc experiment design results in sub-optimal instrument siting and operation strategies. Inadequate targeted data collection of extreme weather is a major limitation to Earth and Environmental Systems Science Division (EESSD)’s goals of data model integration (4.5.3), which limits the knowledge gained through the collected observations, holding back significant advances in predictability. While advances in instrument design are always chipping away at these limitations, we are not optimally utilizing the instrumentation we currently possess.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Cloud Processing of Aerosol during SAIL Field Campaign Report

Globally, on average, the release rate of aerosols from clouds is estimated to be about 6,000 Tg/yr and an aerosol particle is estimated to experience about three cloud cycles. Cloud processing of aerosol produces aerosols that have dramatically different physicochemical properties compared to their original form. Cloud processing may transform particles to efficient cloud condensation nuclei (CCN) or ice nucleating particles (INP) that can further participate in cloud formation. We investigated cloud processing of aerosol during the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Surface Atmosphere Integrated Field Laboratory (SAIL) field campaign using multi-modal offline analysis techniques available at DOE’s Environmental Molecular Sciences Laboratory (EMSL). The main scientific aim of this project was to understand the processes that transform aerosols (chemically, and physically), and influence aerosol-cloud interactions. Aerosol particles undergo significant modifications due to warm (cloud droplets) and cold cloud (ice crystals) processing. Cloud processing of aerosol has important effects on the atmospheric aerosol number and mass concentration, size distribution, phase separation, and chemical composition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Bioenergy Technologies in Long-Run Climate Change Mitigation: Results from the EMF-33 Study

Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services.

bioenergy↗
DOE OSTI2023

Understanding and Predictability of Integrated Mountain Hydroclimate (Workshop Report)

Mountainous systems cover approximately 23% of Earth’s land and are distributed across all continents. They can capture and store atmospheric moisture that is then cycled through the terrestrial surface and subsurface system, released to downstream communities, and cycled back to the atmosphere. Mountain hydroclimate—characterized by steep gradients, geological, ecological, and biogeochemical diversity—is influenced by topographic forcing and elevated warming and susceptible to large subseasonal to multidecadal variability and rapid changes. Terrestrial hydrological and biogeochemical cycles also experience cascading effects from global warming impacts, such as multidecadal declines in mountain snowpack, longer growing seasons, and increased frequency and severity of extreme events like droughts and wildfires. However, little is known about the effects of these impacts and their feedbacks on climate systems and surface-subsurface compartments. Also unknown are the full implications of changing hydroclimate and extreme events on hydro biogeochemical cycles across atmosphere, terrestrial, and human systems in mountain regions and beyond. This knowledge gap is critical, given human reliance on mountain systems for stable water supply and quality. Mountain systems’ increasing vulnerability to climate change and human perturbations motivates the need to improve understanding of integrated mountain hydroclimate (IMHC) systems and their feedbacks and impacts on humans across scales. However, due to large heterogeneity and strong gradients, coupled natural-human processes in mountain regions present significant challenges for observations, modeling, predictions, and projections. Motivated by gaps in mountain hydroclimate understanding, observations, and modeling and the need for credible projections of future changes, the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program organized a virtual workshop on “Understanding and Predictability of Integrated Mountain Hydroclimate.” Sponsored by BER’s Earth and Environmental Systems Sciences Division (EESSD), the workshop aimed to inform and catalyze EESSD’s growing interests in enhancing predictive understanding of IMHC. Organizers structured the workshop to identify (1) knowledge gaps, (2) observational and modeling challenges, (3) short-term (1 to 3 years) and long-term (10 years and beyond) research opportunities, and (4) strategies for fostering collaboration and coordination. To address the outstanding challenges of IMHC, the workshop included two sessions organized by disciplinary, cross-disciplinary, and crosscutting science topics. The disciplinary and cross-disciplinary topics focused on essential IMHC elements: atmosphere, terrestrial, and human systems and their interactions. Breakout sessions on disciplinary and cross-disciplinary topics facilitated identification of crosscutting topics and central emerging themes. Session 1 focused on connecting existing DOE investments to accelerate progress related to scientific challenges in understanding mountain hydroclimate. In Session 2, participants further explored key Session 1 takeaways through the lens of multiagency collaborations and coordination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

CFD-Enhanced Calibration of a Multihole Probe for Small Uncrewed Aircraft Systems

A robust calibration method with a 9-hole probe (9HP) for inertial wind vector measurements from a small uncrewed aircraft system (sUAS) is presented. Calibration accuracy is improved by using computational fluid dynamics (CFD) to estimate corrections, such as those for test section blockage, that are generally applied in wind tunnel testing. A method for estimating experimental bias is presented to account for flow variations over the pressure taps as the 9HP is repositioned in the test section. Installation effects from flow over the airframe and upwash produced by the wings are estimated from CFD simulations of the entire airframe at the expected cruise speed. An initial CFD analysis has demonstrated a quantifiable linear relationship between the measured and actual angle of attack as measured from the relative wind frame. In conclusion, the objective of these additional steps is to increase the accuracy of 9HP calibration.

54 ENVIRONMENTAL SCIENCES↗