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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reference Design Cases for Floating Offshore Wind Arrays

Given the immature nature of the Floating Offshore Wind (FLOW) industry, there is a need for reference FLOW farm designs to allow researchers and technology developers to study the behavior of floating wind turbine systems, without having to design every part of those systems or without having to get access to a wide range of information that is often confidential. The International Energy Agency (IEA) Wind Task 49 is facilitating research collaboration on the integrated design of Floating Offshore Wind Arrays (FOWA), and will develop several reference FOWAs to facilitate R&D activities of the floating wind community and efficient scale change of the floating wind industry (from pilot farms to commercial ones). This paper will outline the key design considerations the task has identified for the sustainable deployment of large-scale FOWAs. The aim is to prepare a comprehensive overview of the different elements that impact the design of FOWA to support the development of best practices for FOWA design. The paper will also present three baseline reference design cases that are being prepared for shallow, intermediate and deep water sites. The final designs will be made open access including the engineering and cost inputs to accelerate further innovation, research and the deployment of FOWAs.

array layout↗
NASA NTRS2015

Institutional Schlieren: A Production-Level Wind Tunnel Test Measurement

The following details recent efforts undertaken at the NASA Ames Unitary Plan Wind Tunnel to design and deploy an advanced, institutional, production-level data system for the classical Schlieren-shadowgraph technique. Motivation for the selection of individual system components is discussed along with a software methodology that combines image acquisition and processing into a production-level wind tunnel test measurement. In general terms, a production-level measurement refers to any data system that is seamlessly integrated into the primary wind tunnel data system, and whose data products are available real-time (e.g. force and moment, pressure, temperature data). The advantage of integrating a measurement in such a manner is an immediate increase in data product efficiency, productivity, reliability, and quality. Coupled with these benefits and leveraging recent advancements in high-speed imaging and image processing, automated, synchronized, time-resolved Schlieren-shadowgraph imaging for dynamic flow phenomena is now a reality. This makes possible the synthesis of dynamic off-body imaging with unsteady on-body measurements to produce a uniquely descriptive data product invaluable to the modern researcher.

Shadowgraph↗
DOE OSTI2026

Impact of atmospheric turbulence on performance and loads of wind turbines: knowledge gaps and research challenges

Wind energy harvesting from the atmosphere takes place in the atmospheric boundary layer. The boundary layer shear and buoyancy create three-dimensional turbulent eddies spanning a range of scales that form a continuous forward cascade of kinetic energy to the smallest scales of motion where energy is dissipated. Large-scale atmospheric circulations modulate the boundary layer turbulence, characterized by coherence and intermittency. As wind turbines grow in size and the integrated control of both turbines and wind farms spans greater distances, the relationship between the scales of atmospheric turbulence and the design and operation of wind energy facilities has entered new territory. The boundary layer turbulence impacts both wind turbine power production and turbine loads. Optimizing wind turbine and wind farm performance requires an understanding of how turbulence affects both wind turbine efficiency and reliability. While the characteristics of atmospheric boundary layer turbulence have been observed and studied in detail over the last few decades, there are still significant gaps in our understanding of the impact of turbulence on wind power resources and wind farm operations. This paper outlines the current state of turbulence research relevant to wind energy applications and points to gaps in our knowledge that need to be addressed to effectively utilize wind resources.

Kosović, Branko [Johns Hopkins Univ., Baltimore, M↗
DOE OSTI2020

Exploring the Grid Value Potential of Offshore Wind Energy in Oregon

The grid value of Oregon's offshore wind resource is considered through the lenses of (i) resource complementarity with the hydroelectric system and other Variable Renewable Energy resources, (ii) load complementarity with the four balancing authorities with territory in Oregon, and (iii) spatial value to regional and coastal grids as represented through a Production Cost Model of the WECC system. Capacity implications of the interactions between offshore wind and the historical east-to-west power flows of the region are reviewed. The existing system is shown to accommodate 2GW of offshore wind interconnections without curtailment.

17 WIND ENERGY↗
DOE OSTI2021

North American Renewables Integration Study (NARIS): Cooperative Research and Development Final Report, CRADA Number CRD-16-00633

The goal of the study is to help inform and assist power system planning entities, electricity system operators, government energy agencies, legislators and regulators to better understand the planning, engineering, operational, and economic implications of integrating large amounts of wind, solar and hydro energy into the Canadian, US and Mexican electrical systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Prognosis of Wind Turbine Gearbox Bearing Failures Using SCADA and Modeled Data

Predictive maintenance and condition monitoring systems for wind turbines have seen increased adoption to minimize downtime, reducing operation and maintenance costs. On today’s wind power plants, the integrated supervisory control and data acquisition (SCADA) system provides low- frequency operational data that can be leveraged to quantify a wind turbine’s health. The aim of this study is to utilize machine-learning techniques to predict axial cracking failures in wind turbine gearbox bearings up to 1 month ahead of time. The failures are assumed to have occurred when the investigated bearing was replaced. While current SCADA systems show the overall condition of a wind turbine, often they do not allow for the investigation of specific gearbox bearings’ health. To enrich bearing fault signatures, additional data are computed through physics-based models using gearbox design information. Based on SCADA data, modeled data, and bearing failure log data from an actual wind plant, the performances of different machine-learning models on unseen data are then evaluated using industry-standard metrics such as precision, recall, and F1 score. Results show the overall system performance enhancement in predicting bearing failure when modeled data are included with SCADA data. The reduction in terms of false alarms is about 50%, and improvement in terms of precision and F1 score is about 33% and 12% respectively, based on the best modeling case in this study.

49 EE - Wind and Water Power Program - Wind (EE-4W↗
NASA NTRS1985

Optimal disturbance suppression with application to wind shear

A novel quadratic cost function composed of stochastic and deterministic contributions is used in the design of a digital flight control system for a small commercial jet with wind shear present. The optimal output feedback control design is configured to suppress the effect of the wind shear disturbance and maintain closed loop stability. A new algorithm is presented for finding the feedback gain. A proportional-integral control design with wind shear suppression is tested in a detailed nonlinear simulation of a commercial jet during the landing approach.

Broussard, J. R.↗
NASA NTRS2006

Major Geomagnetic Storms (Dst less than or equal to -100 nT) Generated by Corotating Interaction Regions

Seventy-nine major geomagnetic storms (minimum Dst less than or equal to -100 nT) observed in 1996 to 2004 were the focus of a Living with a Star Coordinated Data-Analysis Workshop (CDAW) in March, 2005. In 9 cases, the storm driver appears to have been purely a corotating interaction region (CIR) without any contribution from coronal mass ejection-related material (interplanetary coronal mass ejections, ICMEs). These storms were generated by structures within CIRs located both before and/or after the stream interface that included persistently southward magnetic fields for intervals of several hours. We compare their geomagnetic effects with those of 159 CIRs observed during 1996 - 2005. The major storms form the extreme tail of a continuous distribution of CIR geoeffectiveness which peaks at Dst approx. -40 nT but is subject to a prominent seasonal variation of - 40 nT which is ordered by the spring and fall equinoxes and the solar wind magnetic field direction towards or away from the Sun. The O'Brien and McPherron [2000] equations, which estimate Dst by integrating the incident solar wind electric field and incorporating a ring current loss term, largely account for the variation in storm size. They tend to underestimate the size of the larger CIR-associated storms by Dst approx. 20 nT. This suggests that injection into the ring current may be more efficient than expected in such storms. Four of the nine major storms in 1996 - 2004 occurred during a period of less than three solar rotations in September - November, 2002, also the time of maximum mean IMF and solar magnetic field intensity during the current solar cycle. The maximum CIR-storm strength found in our sample of events, plus additional 23 probable CIR-associated Dst less than or equal to -100 nT storms in 1972 - 1995, is (Dst = -161 nT). This is consistent with the maximum storm strength (Dst approx. -180 nT) expected from the O'Brien and McPherron equations for the typical range of solar wind electric fields associated with CIRs. This suggests that CIRs alone are unlikely to generate geomagnetic storms that exceed these levels.

Richardson, I. G.↗
NASA NTRS1975

Aerodynamic results of a separation effects test on a 0.01-scale model (52-OTS) of integrated SSV in the AEDC/VKF 40-by-40 inch supersonic wind tunnel A, volume 1

Experimental aerodynamic investigations were conducted, during the period July 18-19, 1974, in the AEDC/VKF Tunnel A facility on a 0.01-scale model (52-OTS) of the integrated space shuttle vehicle, including only one SRB. The purpose of the investigation was to obtain data for close-in proximity (SRB to orbiter/tank) effects with the orbiter/tank combination at relatively high alpha and beta attitudes, and with the SRB separation motors off. The AEDC Captive Trajectory System (CTS), which supported the SRB, was used in conjunction with the tunnel primary sector (supporting the orbiter/tank) to obtain grid type separation effects data. The one symmetrical SRB model was used interchangeably to obtain both right-hand and left-hand SRB data. Free-stream data were also obtained for the orbiter/tank and for the SRB. This data was used to provide baselines for proximity effects. The entire investigation was conducted at a free-stream Mach number of 4.5 with unit Reynolds number ranging from 4.0 to 6.5 million per foot.

Campbell, J. H., II↗
NASA NTRS1974

Wind Tunnel Test Results of Fairings on A.004 Scale Model Rockwell Space Shuttle Integrated Vehicle Aerodynamic Characteristics at Mach Numbers from 0.6 to 4.96 (IA62F)

Experimental aerodynamic investigations were conducted on a .004 scale model (34-OTS) orbiter, external tank, and solid rocket booster combined as an integrated vehicle in the NASA/MSFC 14 x 14 inch trisonic wind tunnel. The primary test objective was to determine the effect of a full length orbiter/external tank fairing on axial force. Secondary objectives were to define the static stability characteristics of the mated vehicle configuration with fairings over a Mach number range of 0.6 thru 4.96. Six component aerodynamic force and moment data were recorded over an angle of attack range from -10 deg to 10 deg at 0 deg sideslip angle and from -10 deg to 10 deg sideslip range at 0 deg and 5 deg angle of attack. Plotted and tabular results are presented herein.

Allen, E. C.↗
NASA NTRS1987

Wind measurements for non-uniform wind fields from spaceborne scatterometers

Radar backscattering coefficient measurements by spaceborne scatterometers are presently simulated for the case of nonuniform wind fields, by means of a detailed numerical integration of the radar equation. The winds thus estimated are then compared with a nominal field which is defined as the average wind vector over the wind cell. The simulation results obtained for the NASA scatterometer are presented for cases of random wind fields whose spectra are consistent with the Seasat scatterometer sea surface wind spectrum. When the nonuniformity is small, system noise dominates the wind error; wind error degradation is therefore small for both perfect and imperfect coregistration cases. When it is relatively large, however, the wind error degradation persistently increases for both perfect and imperfect coregistrations.

Chi, Chong-Yung↗
DOE OSTI2026

WINDPROF: Merged Best-Estimate Wind Profile Data – Nantucket (WFIP3 Campaign)

WINDPROF provides 10-minute wind and turbulence profiles that integrate scanning Doppler lidars, a profiling lidar, a 915 MHz radar wind profiler, and a sonic anemometer across Northeast U.S. coastal and offshore sites during the WFIP3 campaign. Variables include wind speed, wind direction, vertical velocity, turbulence intensity, and turbulent kinetic energy, each with per-instrument quality control and inter-instrument agreement validation. Profiles are mapped to a standardized height grid – a dedicated near-surface level at the sonic measurement height (5 m AGL), 20 m spacing to 100 m, and 30 m spacing above – and carry component and derived uncertainty estimates. Heights are reported above ground level; the site's ground elevation is stored separately. The Nantucket dataset covers 1 February 2024 – 8 September 2025.

17 WIND ENERGY↗
NASA NTRS2007

Efforts to Simulate Solar Wind Turbulence

A three-dimensional integration of the MHD equations in spherical coordinates has been developed that attempts to simulate a variety of solar wind conditions. These include the interaction of Alfven wave packets and the development of a turbulent cascade, the role of the heliospheric current sheet, the role of quasi-two-dimensional fluctuations in determining how magnetic field lines meander throughout the heliosphere, and the role of interstellar pickup ions in perturbing the solar wind in the outer heliosphere.

Goldstein, Melvyn L.↗
DOE OSTI2022

Blackstart Capability and Survivability of Wind Turbines with Fully Rated Converters

We report the blackstart capability of wind turbines is critical for the recovery of wind-dominant power systems from blackouts. If wind power plants are not able to restore a power system, the incorporation of wind resources into electric grids could be limited by blackstart capability. This paper tackles this problem by setting forth a grid-forming controller for Type 4 wind turbines which employ fully rated power converters. To this end, we engineer two-axis anti-windup proportional-integral regulators that serve to ride through restoration disturbances. We also design an active protection system to prevent wind turbines from stalling during recovery from blackouts. We demonstrate in a high-fidelity simulation environment that Type 4 wind turbines with the developed controllers and protection subsystem can: (i) re-energize a notional wind-dominant grid; (ii) ride through asymmetrical faults; and (iii) survive low wind speed events.

17 WIND ENERGY↗
DOE OSTI2025

Cybersecurity Incident Response Guide for Wind

As wind energy systems become increasingly digitized and interconnected, they face a growing array of cyber threats that can disrupt operations, compromise safety, and trigger cascading impacts across the energy ecosystem. The Wind Incident Response Guide provides a structured, wind-specific framework for preparing for, detecting, responding to, and recovering from cyber incidents. Drawing on lessons from field demonstrations, cyber-physical testbeds, and stakeholder engagement across the wind sector, this guide integrates technical, operational, and regulatory considerations to support asset owners, operators, and responders. It outlines key roles and responsibilities, maps incident response phases to wind-specific scenarios, and highlights applicable laws, regulations, standards, and best practices. By tailoring general cybersecurity principles to the unique architectures and operational constraints of wind systems—including remote access, legacy components, and environmental interfaces—this guide aims to enhance resilience, reduce response time, and support coordinated action across public and private stakeholders. It is intended as a practical resource for utilities, developers, regulators, and emergency managers working to secure the future of wind energy.

17 - WIND ENERGY↗
NASA NTRS1982

WTS-4 system verification unit for wind/hydroelectric integration study

The Bureau of Reclamation (Reclamation) initiated a study to investigate the concept of integrating 100 MW of wind energy from megawatt-size wind turbines with the Federal hydroelectric system. As a part of the study, one large wind turbine was purchased through the competitive bid process and is now being installed to serve as a system verification unit (SVU). Reclamation negotiated an agreement with NASA to provide technical management of the project for the design, fabrication, installation, testing, and initial operation. Hamilton Standard was awarded a contract to furnish and install its WTS-4 wind turbine rated at 4 MW at a site near Medicine Bow, Wyoming. The purposes for installing the SVU are to fully evaluate the wind/hydro integration concept, make technical evaluation of the hardware design, train personnel in the technology, evaluate operation and maintenance aspects, and evaluate associated environmental impacts. The SVU will be operational in June 1982. Data from the WTS-4 and from a second SVU, Boeing's MOD-2, will be used to prepare a final design for a 100-MW farm if Congress authorizes the project.

Watts, A. W.↗
NASA NTRSDate not supplied

Risk Assessment of Obstacle Collision for UAVs under off-nominal conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace, demands the need of robust risk monitoring framework for assessing the safety of airspace, ground-structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV's predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV's trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Portia Banerjee↗
NASA NTRSDate not supplied

Risk Assessment of Obstacle Collision for UAVs under Off-nominal Conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace demands the need of robust risk monitoring framework for assessing the safety of airspace, ground structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV’s predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV’s trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Bayesian network↗