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DOE OSTI2024

Visualizing an Exascale Data Center Digital Twin: Considerations, Challenges and Opportunities

Digital twins are an excellent tool to model, visualize, and simulate complex systems, to understand and optimize their operation. In this work, we present the technical challenges of real-time visualization of a digital twin of the Frontier supercomputer.We show the initial prototype and current state of the twin and highlight technical design challenges of visualizing such a large High Performance Computing (HPC) system. The goal is to understand the use of augmented reality as a primary way to extract information and collaborate on digital twins of complex systems. This leverages the spatio-temporal aspect of a 3D representation of a digital twin, with the ability to view historical and real-time telemetry, triggering simulations of a system state and viewing the results, which can be augmented via dashboards for details. Finally, we discuss considerations and opportunities for augmented reality of digital twins of large-scale, parallel computers.

Maiterth, Matthias↗

DOE OSTI2024

Oak Ridge National Laboratory's Strategic Research and Development Insights for Digital Twins

Oak Ridge National Laboratory (ORNL) is pleased to provide our response to the NITRD RFI on Digital Twins Research and Development. Digital twins are virtual representations of physical systems, leveraging real-time data to simulate and predict behaviors. ORNL is advancing digital twin technology across various disciplines, including neutron scattering, networking, science ecosystems, supercomputing, secure facilities, mobility technologies, materials design and discovery, power systems, fusion reactors, biological sciences, and earth observation. These efforts aim to enhance scientific research, operational efficiency, and decision-making processes. ORNL facilities, such as the High Flux Isotope Reactor (HFIR), Grid-C, Spallation Neutron Source (SNS), and Oak Ridge Leadership Computing Facility (OLCF), provide the infrastructure to develop and demonstrate these digital twin technologies. In this document, we lay out key challenges, research gaps, and future opportunities based on our experience with digital twins that aim to serve as useful contributions towards a National Digital Twins R&D Strategic Plan. In the remaining document, we address nine of the thirteen topic areas specified in the RFI.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

White Paper: Scalable Digital Twin Capabilities for Aging and Surveillance of Engineered Systems

This white paper presents a multi-year initiative to develop practical, secure, and scalable digital twin capabilities for engineered systems in aging and surveillance contexts—an approach pioneered at the National Nuclear Security Administration (NNSA) Lawrence Livermore National Laboratory (LLNL) that maps directly onto the needs and ambitions of the Navy for ship- and fleet-level digital twins. LLNL’s work in building part- and process-level digital twins for advanced manufacturing, with a vision to scale up to entire factory floors and, ultimately, enterprise-wide digital twins, offers an adaptable pathway for the Navy as it seeks to modernize lifecycle management, readiness, and predictive maintenance across ships and fleets. For our application, we integrate physics-based modeling with automated data ingestion, processing, and AI-driven calibration, creating hybrid models that are both interpretable and data responsive. We modernized legacy workflows, established centralized data infrastructure, automated experimental pipelines, and demonstrated end-to-end coupling of accelerated aging data with finite element simulations via optimization and surrogate modeling. The result is a generalizable framework that supports part-level digital twins today and lays the groundwork for future system-level twins suitable for Navy applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1961

Static Stability and Control of Canard Configurations at Mach Numbers from 0.70 to 2.22 - Triangular Wing and Canard with Twin Vertical Tails

The static aerodynamic characteristics of a canard airplane configuration having twin vertical stabilizing surfaces are presented. The model consisted of a wing and canard both of triangular plan form and aspect ratio 2 mounted on a Sears-Haack body of fineness ratio 12.5 and two swept and tapered wing-mounted vertical tails of aspect ratio 1.35. Data are presented for Mach numbers from 0.70 to 2.22 and for angles of attack from -6 to +18 deg. at 0 and 5 deg. sideslip. Tests were made with the canard off and with the canard on. Nominal canard deflection angles ranged from 0 to 10 deg. The Reynolds number was 3.68 x 10(exp 6) based on the wing mean aerodynamic chord. Selected portions of the data obtained in this investigation are compared with previously published results for the same model having a single vertical tail instead of twin vertical tails. Without the canard, the directional stability at supersonic Mach numbers and high angles of attack was improved slightly by replacing the single tail with twin tails. However, at a Mach number of 0.70, the directional stability of the twin-tail model deteriorated rapidly with increasing angle of attack above 10 deg. and fell considerably below the level for the single-tail model. At subsonic speeds the directional stability of the twin-tail model with the canard was comparable to that for the single-tail model and at supersonic speed it was considerably greater at high angles of attack. Unlike the single-tail model, the twin-tail model at 50 sideslip exhibited an unstable break in the variation of pitching-moment coefficient with lift coefficient near 10 deg. angle of attack for 0.70 Mach number.

Peterson, Victor L.↗

NASA NTRS2001

The Effect of Twin Boundaries on the Spectroscopic Performance of CdZnTe Detectors

Most single grains in cadmium zinc telluride (CdZnTe) grown by the high-pressure Bridgman (HPB) technique contain multiple twin boundaries. As a consequence, twin boundaries are one of the most common macroscopic material defects found in large area (400 to 700 sq mm) CdZnTe specimens obtained from HPB ingots. Due to the prevalence of twin boundaries, understanding their effect on detector performance is key to the material selection process. Twin boundaries in several 2 mm thick large area specimens were first, documented using infrared transmission imaging. These specimens were then fabricated into either 2 mm pixel or planar detectors in order to examine the effect of the twin boundaries on detector performance. Preliminary results show that twin boundaries, which are decorated with tellurium inclusions, produce a reduction in detector efficiency and a degradation in resolution. The extent of the degradation appears to be a function of the density of tellurium inclusions.

Parker, Bradford H.↗

NASA NTRS2012

The Impact of Subsonic Twin Jets on Airport Noise

Subsonic and supersonic aircraft concepts proposed through NASA s Fundamental Aeronautics Program have multiple engines mounted near one another. Engine configurations with multiple jets introduce an asymmetry to the azimuthal directivity of the jet noise. Current system noise predictions add the jet noise from each jet incoherently, therefore, twin jets are estimated by adding 3 EPNdB to the far-field noise radiated from a single jet. Twin jet effects have the ability to increase or decrease the radiated noise to different azimuthal observation locations. Experiments have shown that twin jet effects are reduced with forward flight and increasing spacings. The current experiment investigates the impact of spacing, and flight effects on airport noise for twin jets. Estimating the jet noise radiated from twin jets as that of a single jet plus 3 EPNdB may be sufficient for horizontal twin jets with an s/d of 4.4 and 5.5, where s is the center-to-center spacing and d is the jet diameter. However, up to a 3 EPNdB error could be present for jet spacings with an s/d of 2.6 and 3.2.

Bozak, Richard, F.↗

NASA NTRS2012

The Impact of Subsonic Twin Jets on Airport Noise

Bozak, Richard F.↗

DOE OSTI2024

Effect of Co on twin formation and magnetic properties of Sm(Fe,Ti,V) 12 alloys

Transferring the excellent intrinsic magnetic properties of SmFe 12 -based compounds to their extrinsic properties remains the main challenge in the development of high-performance SmFe12-based permanent magnets. Twin formation is one of the reasons for the inability to achieve high coercivity and remanence. Here we have shown that the addition of Co in Sm(Fe 1-x Co x ) 10–11 M 1–2 alloys, where M=Ti and V, leads to an increase in twin density. Microstructural characterizations revealed that the atomic arrangement in the twin boundary changes depending on the stabilizing element, which directly influences the local intrinsic magnetic properties. Theoretical investigations showed that the critical grain size at which twin formation can be hindered by grain size reduction decreases when the stabilizer changes from V to Ti. Furthermore, this study shows that the alloy composition influences not only the intrinsic magnetic properties but also the twin formation energy and its grain size dependence, crucial for the design of SmFe12-based permanent magnets.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Impact of the nuclear equation of state on the formation of twin stars

Twin stars-two stable neutron stars (NSs) with the same mass but different radii have long been proposed to appear as a consequence of a possible first-order phase transition in NS matter. Within a meta-model for the EOS of hybrid stars, we revisit the viability of twin stars and its dependence on numerous parameters characterizing the EOS of nuclear matter, quark matter, and the phase transition between them. While essentially no experimental constraint exists for the last two, parameters characterizing the EOS of neutron-rich nucleonic matter have been constrained within various ranges by terrestrial experiments and astrophysical observations. Within these ranges, the impact of nuclear EOS and crust-core transition density on the formation of twin stars is studied. Here, it is found that the symmetry energy of neutron-rich nucleonic matter notably influences the formation of twin stars, particularly through its slope L and curvature K sym . Conversely, varying the EOS of symmetric nuclear matter within their currently known uncertainty ranges shows minimal influence on the formation of twin stars.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2014

Twin Jet Effects on Noise of Round and Rectangular Jets: Experiment and Model

Many subsonic and supersonic aircraft concepts proposed by NASA's Fundamental Aeronautics Program have asymmetric, integrated propulsion systems. The asymmetries in the exhaust of these propulsion systems create an asymmetric acoustic field. The asymmetries investigated in the current study are from twin jets and rectangular nozzles. Each effect produces its own variation of the acoustic field. An empirical model was developed to predict the acoustic field variation from round twin jets with twin jet spacing from 2.6 to 5.6, where s is the center-to-center spacing over the jet diameter. The model includes parameters to account for the effects of twin jet spacing, jet static temperature ratio, flight Mach number, frequency, and observer angle (both polar and azimuthal angles). The model was then applied to twin 2:1 and 8:1 aspect ratio nozzles to determine the impact of jet aspect ratio. For the round and rectangular jets, the use of the model reduces the average magnitude of the error over all frequencies, observation angles, and jet spacings by approximately 0.5dB when compared against the assumption of adding two jets incoherently.

Noise↗

NASA NTRSDate not supplied

Initial Development of A Digital Twin Model for an Electrified Aircraft Propulsion Emulation Rig

In support of aviation fuel burn and emission reduction goals, NASA is pursing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP), which relies on the generation, storage, transmission, and use of electrical power for producing thrust and optimizing propulsion system efficiency. Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes advances in propulsion controls, which will be vital for ensuring coordinated efficient operation of the complex integrated subsystems that comprise EAP architectures. To support EAP controls research, the NASA Glenn Research Center has developed the Hybrid Propulsion Emulation Rig (HyPER). The HyPER laboratory hardware includes shaft-mounted electric machines, power converters, power supplies, power distribution cables, and an energy storage device that can be reconfigured to represent a variety of EAP architectures. It also includes an integrated real-time computer system that hosts developed EAP control software and turbomachinery simulations. This enables the electrical system and rotating shafts of EAP designs to be implemented in actual hardware and integrated with turbomachinery simulations and system-level EAP control logic implemented in software. In this form, the HyPER laboratory provides a partially simulated, partially hardware-in-the-loop test environment enabling the initial development and evaluation of EAP control technology. A prerequisite for the development of EAP control designs is the availability of a system model that accurately reflects the operation of the electrical system hardware. To support this need, a digital twin model of the HyPER electrical system hardware is under development. This model is being coded in the MATLAB Simulink environment and uses the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) to construct a digital twin framework. EMTAT contains generic electrical component building blocks that are simulated at turbomachinery timescales. Associated inputs and outputs allow the blocks to be combined to model complete electrical systems. The EMTAT blocks also contain adjustable internal maps and parameters that can be set to reflect the operation of a specific electrical component. For the HyPER digital twin, the settings of these EMTAT block internal maps and parameters is determined through machine learning approaches applied to characterization run data collected from the laboratory. During characterization runs the laboratory electrical system hardware is subjected to a full range of torque, speed, and power settings. Acquired data is then used to estimate EMTAT block parameters using a variety of machine learning techniques. The resulting digital twin model is found to match the operation of actual HyPER hardware with an accuracy suitable for control development purposes. It also holds promise for other applications including modeling the performance of HyPER laboratory reconfigurations and model-based anomaly detection. Planned follow-on work to automate post-processing of acquired laboratory data to update the HyPER digital twin model will also be presented and discussed.

Electrified Aircraft Propulsion↗

NASA NTRS2024

MBSE (SysML) and Digital Twin Integration to Support Engineering Analysis & Design

Problem Statement: The complexity of Gateway systems and of managing the integrated safety analysis have made traditional methods of engineering analysis and design increasingly challenging. To address these challenges, a prototype that integrate Model-Based Systems Engineering (MBSE) with Digital Twin technology has been developed to demonstrate the utilities and functions. Project Goal: Develop a prototype of a Digital Twin Of Gateway ECLSS IMV system to enhance fault management analysis through collaboration, visualization, and simulation. Overall Project Results / Accomplishments: - Developed extension to streamline the integration of SysML models with the Digital Twin platform - Demonstrated the capability to aggregate any relevant information and provide simulation integration within the DT prototype. - Generated digital twin simulation using SysML Activity Diagrams - Implemented a complex trade study use case based on the integrated SysML-Digital Twin infrastructure

MBSE↗

DOE OSTI2025

Nucleation and Antiphase Twin Control in Bi 2 Se 3 via Step‐Terminated Al 2 O 3 Substrates

The epitaxial synthesis of high-quality 2D layered materials is an essential driver of both fundamental physics studies and technological applications. Bi 2 Se 3 , a prototypical 2D layered topological insulator, is sensitive to defects imparted during the growth, either thermodynamically or due to the film-substrate interaction. Here, in this study, it is shown that step-terminated Al 2 O 3 substrates with a high miscut angle (3°) can effectively suppress a particular hard-to-mitigate defect, the antiphase twin. Systematic investigations across a range of growth temperatures and substrate miscut angles confirm that atomic step edges act as preferential nucleation sites, stabilizing a single twin domain. First-principles calculations suggest that there is a significant energy barrier for twin boundary formation at step edges, supporting the experimental observations. Detailed structural characterization indicates that this twin-selectivity is lost through the mechanism of the 2D layers overgrowing the step edges, leading to higher twin density as the thickness increases. These findings highlight the complex energy landscape unique to 2D materials that is driven by the interplay between substrate properties, nucleation dynamics, and defect formation, and overcoming and controlling these are critical to improve material quality for quantum and electronic applications.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗

NASA NTRS1990

NAE Twin Otter operations in FIFE 1989

During the summer of 1989, the National Aeronautical Establishment (Canada) Twin Otter Atmospheric Research Aircraft was flow in support of the NASA sponsored First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment called FIFE-89. Airborne measurements of the fluxes of heat, momentum, water vapor and carbon dioxide were made during 16 flow-altitude flights over the FIFE project area in central Kansas. The Twin Otter operations in FIFE are documented and details are included on the instrumentation, software, flight procedures, atmospheric conditions and analysis methods. Comparisons of Twin Otter measured fluxes are made with those determined at several surface sites and with those made by other instrumented aircraft in the FIFE-87 measurements. Airborne flux measurements are related to run length, altitude, and environmental parameters such as vegetation type, temperature, and wind speed. One night flight was run in an attempt to measure the respiration component of the CO2 flux. The use of aircraft was studied for regional observations of fluxes and to relate these to satellite radiance measurements. Run average data are presented for all 285 flux runs flown by the Twin Otter in FIFE-89. This should serve as as a working reference for scientists utilizing Twin Otter data either directly of through the FIFE data archive.

Macpherson, J. I.↗

NASA NTRS1996

Twin Tail/Delta Wing Configuration Buffet Due to Unsteady Vortex Breakdown Flow

The buffet response of the twin-tail configuration of the F/A-18 aircraft; a multidisciplinary problem, is investigated using three sets of equations on a multi-block grid structure. The first set is the unsteady, compressible, full Navier-Stokes equations. The second set is the coupled aeroelastic equations for bending and torsional twin-tail responses. The third set is the grid-displacement equations which are used to update the grid coordinates due to the tail deflections. The computational model consists of a 76 deg-swept back, sharp edged delta wing of aspect ratio of one and a swept-back F/A-18 twin-tails. The configuration is pitched at 32 deg angle of attack and the freestream Mach number and Reynolds number are 0.2 and 0.75 x 10(exp 6) respectively. The problem is solved for the initial flow conditions with the twin tail kept rigid. Next, the aeroelastic equations of the tails are turned on along with the grid-displacement equations to solve for the uncoupled bending and torsional tails response due to the unsteady loads produced by the vortex breakdown flow of the vortex cores of the delta wing. Two lateral locations of the twin tail are investigated. These locations are called the midspan and inboard locations.

Kandil, Osama A.↗

NASA NTRS1998

Computational Investigation and Validation of Twin-Tail Buffet Response Including Dynamics and Control

Multidisciplinary tools for prediction of single rectangular-tail buffet are extended to single swept-back-tail buffet in transonic-speed flow, and multidisciplinary tools for prediction and control of twin-tail buffet are developed and presented. The configuration model consists of a sharp-edged delta wing with single or twin tails that are oriented normal to the wing surface. The tails are treated as cantilevered beams fixed at the root and allowed to oscillate in both bending and torsion. This complex multidisciplinary problem is solved sequentially using three sets of equations on a dynamic single or multi-block grid structure. The first set is the unsteady, compressible, Reynolds-averaged Navier-Stokes equations which are used for obtaining the flow field vector and the aerodynamic loads on the tails. The Navier-Stokes equations are solved accurately in time using the implicit, upwind, flux-difference splitting, finite volume scheme. The second set is the coupled bending and torsion aeroelastic equations of cantilevered beams which are used for obtaining the bending and torsion deflections of the tails. The aeroelastic equations'are solved accurately in time using, a fifth-order-accurate Runge-Kutta scheme. The third set is the grid-displacement equations and the rigid-body dynamics equations, which are used for updating the grid coordinates due to the tail deflections and rigid-body motions. The tail-buffet phenomenon is predicted for highly-swept, single vertical tail placed at the plane of geometric symmetry, and for highly-swept, vertical twin tails placed at three different spanwise separation distances. The investigation demonstrates the effects of structural inertial coupling and uncoupling of the bending and torsion modes of vibration, spanwise positions of the twin-tail, angle of attack, and pitching and rolling dynamic motions of the configuration model on the tail buffet loading and response. The fundamental issue of twin-tail buffet alleviation is addressed using two active flow-control methods. These methods are the tangential leading-edge blowing and the flow suction from the leading-edge vortex cores along their paths. Qualitative and quantitative comparisons with the available experimental data are presented. The comparisons indicate that the present multidisciplinary aeroelastic analysis tools are robust, accurate and efficient.

Kandil, Osama A.↗