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DOE OSTI2020

Lower soil moisture and deep soil temperatures in thermokarst features increase old soil carbon loss after 10 years of experimental permafrost warming

Almost half of the global terrestrial soil carbon (C) is stored in the northern circumpolar permafrost region, where air temperatures are increasing two times faster than the global average. As climate warms, permafrost thaws and soil organic matter becomes vulnerable to greater microbial decomposition. Long-term soil warming of ice-rich permafrost can result in thermokarst formation that creates variability in environmental conditions. Consequently, plant and microbial proportional contributions to ecosystem respiration may change in response to long-term soil warming. Natural abundance δ 13 C and Δ 14 C of aboveground and belowground plant material, and of young and old soil respiration were used to inform a mixing model to partition the contribution of each source to ecosystem respiration fluxes. We employed a hierarchical Bayesian approach that incorporated gross primary productivity and environmental drivers to constrain source contributions. We found that long-term experimental permafrost warming introduced a soil hydrology component that interacted with temperature to affect old soil C respiration. Old soil C loss was suppressed in plots with warmer deep soil temperatures because they tended to be wetter. When soil volumetric water content significantly decreased in 2018 relative to 2016 and 2017, the dominant respiration sources shifted from plant aboveground and young soil respiration to old soil respiration. The proportion of ecosystem respiration from old soil C accounted for up to 39% of ecosystem respiration and represented a 30-fold increase compared to the wet-year average. Our findings show that thermokarst formation may act to moderate microbial decomposition of old soil C when soil is highly saturated. However, when soil moisture decreases, a higher proportion of old soil C is vulnerable to decomposition and can become a large flux to the atmosphere. Furthermore, as permafrost systems continue to change with climate, we must understand the thresholds that may propel these systems from a C sink to a source.

permafrost↗

DOE OSTI2022

Optimising response to an introduction of African swine fever in wild pigs

African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the United States, invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on the size of the control areas required to rapidly eliminate the ASFv in wild pigs and how this area should change with management constraints and local ecology is needed to optimize response planning. We developed a spatially explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in Southeastern United States. We simulated ASFv spread and determined the optimal response area (reported as the radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv was detected relative to the true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly) and wild pig densities. Large radii for response areas (14 km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions, the ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within 1 year. The results highlight the importance of adjusting response plans based on local ecology and show that wild pig movement is a better predictor of the optimal response area than the number of ASFv cases early in the outbreak trajectory. Furthermore, our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Agro-IBIS/THMB Modeled Yield, Nitrogen Loss, and Profitability Maps for the Raccoon River Basin, Iowa, USA

This data was used to assess the potential for improving water quality in this watershed when integrating miscanthus, a bioenergy perennial grass, on to areas of low profit under current corn-soybean management and areas of high nitrogen leaching under both current and future climate conditions. This dataset includes all observations (yield, streamflow, nitrogen loads) and model simulation data used from Dr. Kelsie Ferin’s (former PhD student with Dr. Andy VanLoocke, ISU Dept. of Agronomy) dissertation and publication in Global Change Biology – Bioenergy (DOI: 10.1111/gcbb.13078). Modeled output included in this dataset includes corn, soybean, and miscanthus yields, nitrogen leaching rates, net mineralization rates, land use cover fractions with and without the inclusion of miscanthus, profitability maps, additional soil property maps, and simulated streamflow and nitrogen loads near the outlet of the Raccoon River Basin (Van Meter, Iowa) for both historical and future climate conditions. This dataset includes a mixture of netCDF, .tiff, .csv, and .xlsx files. See README.pdf for more information.

Ferin, Kelsie↗

DOE OSTI2024

Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways, and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The CORDEX-CORE EXP-I Initiative: Description and Highlight Results from the Initial Analysis

Here we describe the first effort within the Coordinated Regional Climate Downscaling Experiment–Coordinated Output for Regional Evaluation, or CORDEX-CORE EXP-I. It consists of a set of twenty-first-century projections with two regional climate models (RCMs) downscaling three global climate model (GCM) simulations from the CMIP5 program, for two greenhouse gas concentration pathways (RCP8.5 and RCP2.6), over nine CORDEX domains at ~25-km grid spacing. Illustrative examples from the initial analysis of this ensemble are presented, covering a wide range of topics, such as added value of RCM nesting, extreme indices, tropical and extratropical storms, monsoons, ENSO, severe storm environments, emergence of change signals, and energy production. They show that the CORDEX-CORE EXP-I ensemble can provide downscaled information of unprecedented comprehensiveness to increase understanding of processes relevant for regional climate change and impacts, and to assess the added value of RCMs. The CORDEX-CORE EXP-I dataset, which will be incrementally augmented with new simulations, is intended to be a public resource available to the scientific and end-user communities for application to process studies, impacts on different socioeconomic sectors, and climate service activities. The future of the CORDEX-CORE initiative is also discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Universally high transcript error rates in bacteria

Errors can occur at any level during the replication and transcription of genetic information. Genetic mutations derived mainly from replication errors have been extensively studied. However, fundamental details of transcript errors, such as their rate, molecular spectrum, and functional effects, remain largely unknown. To globally identify transcript errors, we applied an adapted rolling-circle sequencing approach to Escherichia coli, Bacillus subtilis, Agrobacterium tumefaciens, and Mesoplasma florum, revealing transcript-error rates 3 to 4 orders of magnitude higher than the corresponding genetic mutation rates. The majority of detected errors would result in amino-acid changes, if translated. With errors identified from 9929 loci, the molecular spectrum and distribution of errors were uncovered in great detail. A G→A substitution bias was observed in M. florum, which apparently has an error-prone RNA polymerase. Surprisingly, an increased frequency of nonsense errors towards the 3' end of mRNAs was observed, suggesting a Nonsense-Mediated Decay-like quality-control mechanism in prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Coffee supply chain planning under climate change

The growing demand but uncertain supply makes the sustainability of the coffee industry a shared concern for all participants along the coffee supply chain. This study proposed a decision-making model that comprises the cultivation management, including shade management and annual agriculture management, and the supply chain logistics. A two-stage stochastic program is presented and used within a rolling horizon scheme that periodically updates input data information to deal with uncertainty associated with future climate scenarios. The program minimizes the total expected cost of the entire supply chain of arabica coffee. The study applied the model to the real case study of arabica coffee bean supply to the U.S. market, trying to answer whether arabica coffee supply can meet the U.S. demand from 2022 to 2050 and how to best mitigate any shortage through corporate-farmer partnerships. The results show that the coffee supply will have a 3% shortage in the future; medium-level shade management and more irrigation and fertilization are possible mitigation strategies. These results demonstrate the need for all participants to adopt suitable technologies for the sustainability of global coffee supply chains together.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

A conceptual framework for residential energy security in the context of clean energy transitions

Energy security is a crucial aspect of human well-being. As climate change impacts become more evident, countries are constructing equitable, resilient, and sustainable clean energy transition policies to reduce emissions while ensuring energy security. Climate policies globally highlight the importance of national energy security. Furthermore, adequate and affordable access to household energy is also critical to the continued prioritization of climate mitigation. However, past energy security discussions within the broader climate research and policymaking community primarily focused on national-level energy supply as a critical metric of energy security. Less research has explored the potential implications of energy transitions for residential energy security, often focusing on a single dimension of residential energy security. Thus, we conduct a review of journal articles and governmental plans to develop a conceptual framework of residential energy security and facilitate communication among researchers and policymakers. The framework is designed around four foundational pillars, five metrics measuring residential energy security, and seven drivers influencing the metrics. Additionally, we provide policy examples to show how this framework can be applied to inform decision-making. Thus, this paper makes important contributions to the literature by (a) creating a framework to better understand the concept of energy security at the household level for future research and policy-relevant communications, (b) identifying gaps in the current literature, and (c) highlighting instances where aspects of residential energy security are discussed in policies and governmental plans, which help serve as guiding examples for future applications of our framework in the policymaking processes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

The HTAP_v3.2 emission mosaic: merging regional and global monthly emissions (2000–2020) to support air quality modelling and policies

This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the need of the global and regional atmospheric modelling community of having a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of a high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3.2, an ad-hoc global mosaic of anthropogenic inventories, is an update to the HTAP_v3 global mosaic inventory and has been developed by integrating official inventories over specific areas (North America, Europe, Asia including China, Japan and Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO 2 , NO x , CO, NMVOC, NH 3 , PM 10 , PM 2.5 , Black Carbon (BC), and Organic Carbon (OC), with a spatial resolution of 0.1 × 0.1° and time intervals of months and years covering the period 2000–2020 (https://doi.org/10.5281/zenodo.17086684, Crippa, 2025, https://edgar.jrc.ec.europa.eu/dataset_htap_v32, last access: 27 October 2025). The emissions are further disaggregated to 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3.2 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past two decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policy making, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

Guizzardi, Diego [European Commission, Ispra (Ital↗

DOE OSTI2026

Space Cooling: Recovery, Reuse, Recycling and Supply Chain Impacts

The global cooling sector has undergone tremendous growth in recent years, and cooling demand is projected to double or triple by 2050. Surging air conditioning demand will continue to be driven by increased populations, incomes and occurrences of extreme heat and humidity events. Cooling equipment growth has important pollution and material implications as they are made up of critical metals and precious raw materials - including ferrous metals, copper, aluminum and printed circuit boards composed of copper, silver, gold and palladium - that generate significant electronic waste at end-of-life. Air conditioning equipment also contains fluorinated gas (F-gas) refrigerants, which are potent gases that are thousands of times more heat-trapping than carbon dioxide (CO2). While recovery, reuse, and recycling strategies have been assessed for cold chain and refrigeration, there is currently limited analysis on how these strategies could be adopted for the global space cooling industry and potential supply chain implications. This paper aims to address this research gap by qualitatively evaluating product and material recovery, reuse and recycling frameworks from both demand and supply-side perspectives and with the support of cooling-specific case studies. It also focuses on quantitatively assessing potential energy, emissions and resource benefits of such strategies for space cooling equipment. This paper first analyzes how existing recovery, reuse and recycling frameworks can be applied to space cooling, with emphasis on the demand-side enablers (e.g., innovative business models, supporting policies and regulations) and changes in supply-side production network throughout the supply chain (e.g., design, production and distribution, end-of-life recovery) needed to overcome existing barriers. It will present case studies of innovative business models for space cooling technologies, including reuse and recycling, and how effective refrigerant reclamation and recovery programs have been operationalized. Lastly, the paper will highlight global modeling results of energy, emissions and material recovery from scenario analysis of selected strategies for air conditioners. The findings of this paper are intended to inform the development of product and material recovery, reuse and recycling strategies for a rapidly growing stock of space conditioning equipment by addressing existing organizational, economic and regulatory barriers and potential supply-chain bottlenecks.

Khanna, Nina↗

DOE OSTI2024

Earth's record-high greenness and its attributions in 2020

Terrestrial vegetation is a crucial component of Earth's biosphere, regulating global carbon and water cycles and contributing to human welfare. Despite an overall greening trend, terrestrial vegetation exhibits a significant inter-annual variability. The mechanisms driving this variability, particularly those related to climatic and anthropogenic factors, remain poorly understood, which hampers our ability to project the long-term sustainability of ecosystem services. Here, in this work, by leveraging diverse remote sensing measurements, we pinpointed 2020 as a historic landmark, registering as the greenest year in modern satellite records from 2001 to 2020. Using ensemble machine learning and Earth system models, we found this exceptional greening primarily stemmed from consistent growth in boreal and temperate vegetation, attributed to rising CO 2 levels, climate warming, and reforestation efforts, alongside a transient tropical green-up linked to the enhanced rainfall. Contrary to expectations, the COVID-19 pandemic lockdowns had a limited impact on this global greening anomaly. Our findings highlight the resilience and dynamic nature of global vegetation in response to diverse climatic and anthropogenic influences, offering valuable insights for optimizing ecosystem management and informing climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Human perturbations to mercury in global rivers

Mercury compounds are potent neurotoxins that pose threats to human health, primarily through fish consumption. Rivers, critical for drinking water and food supply, have seen rapid increases in mercury concentrations and export to coastal margins since the Industrial Revolution (~1850). However, patterns of these changes remain understudied, limiting assessments of environmental policies. Here, we develop a global model to simulate preindustrial riverine total mercury and assess human perturbations by comparing it to present-day conditions. We find that global rivers transported ~390 megagrams annually of mercury to the oceans in the preindustrial era, with spatial variability. Human activities have elevated riverine mercury budgets by two to three times in the present day. Establishing a baseline riverine mercury level, our findings reveal rapid responses of riverine mercury to human perturbations and could be used to inform targets for global riverine mercury restoration. Total riverine mercury concentrations could also be used as indicators to comprehensively understand the effectiveness of mercury pollution governance.

Science & Technology - Other Topics↗

DOE OSTI2022

Observing, Measuring, and Assessing the Consequences of Snow Drought

Warmer and shorter winters from climate change will reduce snowpacks in most seasonally snow-covered regions of the world, with consequences for freshwater availability in spring and summer when people and ecosystems demand water most. Recent record-low snowpacks, such as those in the winters of 2013/14 and 2014/15 in the western United States, have led to a surge in research on “snow droughts,” which are pointed to as harbingers of global warming that pose significant societal hazards. Yet, despite the importance of understanding snow droughts to best prepare for their attendant impacts, the concept remains amorphous, with no agreed-upon definition of what they are, how best to measure them, and how such snow droughts connect to warm-season impacts. These knowledge gaps limit our understanding of the risks posed by snow droughts in the present and future, and thus our preparedness for their differential impacts on freshwater resources. To address these issues, we compile a hemispheric ensemble of in situ, satellite, and reanalysis snowpack datasets. We use this ensemble to evaluate the scientific challenges and uncertainties arising from differences in defining and measuring snow droughts, and to identify opportunities to leverage this information to better understand the significance of snow droughts. We show that a clearer quantification of what constitutes a snow drought, including its uncertainties, improves our ability to anticipate costly and disruptive warm-season droughts, which is vital for informing risk management and adaptation to changing snow regimes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Use-Inspired, Process-Oriented GCM Selection: Prioritizing Models for Regional Dynamical Downscaling

Dynamical downscaling is a crucial process for providing regional climate information for broad uses, using coarser-resolution global models to drive higher-resolution regional climate simulations. The pool of global climate models (GCMs) providing the fields needed for dynamical downscaling has increased from the previous generations of the Coupled Model Intercomparison Project (CMIP). However, with limited computational resources, the need for prioritizing the GCMs for subsequent downscaling studies remains. GCM selection for dynamical downscaling should focus on evaluating processes relevant for providing boundary conditions to the regional models and be inspired by regional uses such as the response of extremes to changes in the boundary conditions. This leads to the need for metrics representing processes of relevance to diverse stakeholders and subregions of a domain. Procedures to account for metric redundancy and the statistical distinguishability of GCM rankings are required. Further, procedures for selecting realizations from ensembles of top-performing GCM simulations can be used to span the range of climate change signals in multiple ways. As a result, distinct weighting of metrics and prioritization of particular realizations may depend on user needs. We provide high-level guidelines for such region-specific evaluations and address how CMIP7 might enable dynamical downscaling of a representative sample of high-quality models across representative shared socioeconomic pathways (SSPs).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A Global Building Occupant Behavior Database

This paper introduces a database of 34 field-measured building occupant behavior datasets collected from 15 countries and 39 institutions across 10 climatic zones covering various building types in both commercial and residential sectors. This is a comprehensive global database about building occupant behavior. The database includes occupancy patterns (i.e., presence and people count) and occupant behaviors (i.e., interactions with devices, equipment, and technical systems in buildings). Brick schema models were developed to represent sensor and room metadata information. The database is publicly available, and a website was created for the public to access, query, and download specific datasets or the whole database interactively. The database can help to advance the knowledge and understanding of realistic occupancy patterns and human-building interactions with building systems (e.g., light switching, set-point changes on thermostats, fans on/off, etc.) and envelopes (e.g., window opening/closing). With these more realistic inputs of occupants’ schedules and their interactions with buildings and systems, building designers, energy modelers, and consultants can improve the accuracy of building energy simulation and building load forecasting.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

The ReSWARM microgravity flight experiments: Planning, control, and model estimation for on‐orbit close proximity operations

Abstract On‐orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on‐orbit assembly, repair, and astronaut assistance. Of these scenarios, on‐orbit assembly is an enabling technology that will allow large space structures to be built in situ, using smaller building block modules. However, like many of these scenarios, robotic on‐orbit assembly involves several technical hurdles, such as changing system models. For instance, grappled modules moved by a free‐flying “assembler” robot can cause significant changes in the combined system inertia, which have cascading impacts on motion planning and control portions of the autonomy stack. Further, on‐orbit assembly and other scenarios require collision‐avoiding motion planning, particularly when operating in a “construction site” scenario of multiple assembler robots and structures. Multiple key technologies that address these complicating factors for autonomous microgravity close proximity operations are detailed in this work, in particular: (1) application of global long‐horizon planning, accomplished using offline and online sampling‐based planner options that consider the system dynamics; (2) adaptation of the recently proposed RATTLE information‐aware planning framework for on‐orbit reconfiguration model learning; and (3) connection with robust control tools to provide low‐level control robustness using current system knowledge. These approaches were demonstrated for an autonomous on‐orbit assembly use case by the RElative Satellite sWarming and Robotic Maneuvering (ReSWARM) experiments using NASA's Astrobee robots on the International Space Station. Results of the ReSWARM experiments are provided along with significant operational and implementation detail discussing the practicalities of hardware implementation and unique aspects of working with the Astrobee free‐flyer robots in microgravity. ReSWARM provides a base set of planning and control tools for robotic close proximity operations, demonstrates them in microgravity, and outlines some of the important hardware aspects that future autonomous free‐flyers will need to consider.

Robotics↗

DOE OSTI2026

TES: Modelling Microbes to Predict Post-Fire Carbon Cycling in the Boreal Forest across Burn Severities (Exploratory Proposal)

Wildfires in boreal ecosystems represent a globally significant ecological process that is expected to be sensitive to changing climate as well as forest management strategies, but is currently insufficiently understood and represented in models. We sought to determine whether linking belowground microbial community composition, size, and activity to aboveground properties of burn severity and plant community composition (upland jack pine and upland spruce) would allow us to better model post-fire soil CO 2 fluxes using the Carbon, Organisms, Rhizosphere and Protection in the Soil Environment (CORPSE) model. We used an integrated modelling experimental approach, with mechanistic laboratory experiments designed to inform models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Numerical Modeling of a Two-Stage Ocean Current Turbine

The Equinox Ocean Turbines (EQOT) current energy converter has a unique design with power generation in two small-diameter turbines attached to the tips of a large-diameter passive rotor. This configuration offers some key advantages for capturing ocean currents. With no centrally placed generator, almost no reaction torque is required at the nacelle of the main large-diameter rotor, and the small-diameter tip turbine generators operate at a higher speed and lower torque. The physics that determine the performance and loads on the turbine are also unique. The interactions of the flow field between the two stages and the general architecture of the system cannot be captured with traditional mid-fidelity modeling tools. For design iterations and large sets of load cases, it is important to have mid-fidelity models that can capture the important phenomenon with enough accuracy to identify global trends. This work uses a limited set of high-fidelity computational fluid dynamics (CFD) simulations to help inform the selection of and construction of a custom mid-fidelity model. Mid-fidelity modeling approaches were verified by comparing key turbine performance quantities to those found with the CFD model. Hydrodynamic interactions of the two-stage rotor were identified through high-fidelity CFD modeling. This highlighted the impact of the main rotor tip vortex and wake on the secondary rotor apparent inflow. This results in a relative flow rotation and sharp deficit, that change the optimal secondary rotor rotation speed and adds unsteadiness to the blade loading respectively. Multiple mid-fidelity approaches were evaluated for their ability to capture these effects. A simple approximation of the combined-stage performance based on single-stage BEM provides a reasonable rough prediction, especially near the peak TSR values, with some larger discrepancy at higher TSRs. Predicting the combined-stage performance based on single-stage CFD data improves this prediction across the TSR range. Although the combined-stage modeling in OLAF was not successful in this stage of the project, it showed promise as a mid-fidelity method, assuming the parameters can be tuned to account for the significant differences in time and length scales between the main and secondary rotors. This may be addressed through code changes in future work. A significant finding from the OLAF work was the agreement between the vortex core radius values found independently via a parameter space search and via CFD. The technique of using single-stage secondary rotor BEM, with a custom inflow taken from single-stage main rotor CFD or OLAF, provides an efficient method to capture one-way coupled flow interactions. This method provided generally good predictions of the impact of the flow rotation on the secondary rotor but struggled to accurately predict the peaks of the unsteady load progression. Future work could include some superposition of a tuned main rotor trailing edge viscous wake into the custom inflow to better predict this interaction.

16 TIDAL AND WAVE POWER↗