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At least 1,063 records · Page 59

Performance Modeling of Urban Air Mobility Vehicles to Support Air Traffic Management Research

The recent emergence of Urban Air Mobility (UAM) vehicles has resulted in a need for flight performance models that enable comprehensive simulation-based research on air traffic management topics such as route structure, scheduling, and separation standards. Successful performance modeling methods exist for a wide range of traditional aircraft designs. However, comparable modeling methods appropriate for UAM vehicles that combine fixed-wing and rotorcraft performance have not yet been established. One challenge to progress has been the lack of available data capturing the performance characteristics and unique flight profiles of these aircraft. This paper describes methods used to generate the required performance data and the development of performance models for UAM vehicles. Included is a review of the energy and power equations often used in developing performance models for traditional aircraft as well as a discussion of their applicability to UAM vehicles. The challenge of generating realistic performance data in over-actuated vehicles transitioning from hover to cruise flight is also addressed through an approach based on objective function optimization. A table-based performance model format adapted to UAM configurations is described, as well as parametric models intended to accompany the performance table to allow detailed modeling of power and fuel consumption during accelerated flight, turning flight, or flight at an arbitrary climb or descent rate. A discussion of future work is also provided, including the need for refinement of UAM performance modeling methods and formats, especially in conjunction with improvements to aerodynamic modeling of vehicles with complex designs where strong interaction effects may dominate important regions of the flight envelope.

Performance Modeling↗

Performance Modeling of Urban Air Mobility Vehicles to Support Air Traffic Management Research

The recent emergence of Urban Air Mobility (UAM) vehicles has resulted in a need for flight performance models that enable comprehensive simulation-based research on air traffic management topics such as route structure, scheduling, and separation standards. Successful performance modeling methods exist for a wide range of traditional aircraft designs. However, comparable modeling methods appropriate for UAM vehicles that combine fixed-wing and rotorcraft performance have not yet been established. One challenge to progress has been the lack of available data capturing the performance characteristics and unique flight profiles of these aircraft. This paper describes methods used to generate the required performance data and the development of performance models for UAM vehicles. Included is a review of the energy and power equations often used in developing performance models for traditional aircraft as well as a discussion of their applicability to UAM vehicles. The challenge of generating realistic performance data in over-actuated vehicles transitioning from hover to cruise flight is also addressed through an approach based on objective function optimization. A table-based performance model format adapted to UAM configurations is described, as well as parametric models intended to accompany the performance table to allow detailed modeling of power and fuel consumption during accelerated flight, turning flight, or flight at an arbitrary climb or descent rate. A discussion of future work is also provided, including the need for refinement of UAM performance modeling methods and formats, especially in conjunction with improvements to aerodynamic modeling of vehicles with complex designs where strong interaction effects may dominate important regions of the flight envelope.

Performance Modeling↗

Transition Modeling Based on the Dual N-factor Method for the CRM-NLF Wind Tunnel Configuration

The dual N-factor method is used to model the boundary-layer transition over the common research model with natural laminar flow (CRM-NLF) aircraft configuration. The flow conditions match selected test conditions from a wind tunnel experiment in the National Transonic Facility at the NASA Langley Research Center. The paper presents a systematic methodology for transition prediction in the presence of a dual shock system and extends the prior capability for iteratively coupled computational fluid dynamics (CFD) predictions to incorporate three-dimensional, transonic wings. The method employs stability computations based on the linear parabolized stability equations (PSE), along with a dual N-factor criterion. The iterative process begins with the fully turbulent Reynolds-averaged-Navier-Stokes (RANS) mean flow solution. For the first iteration, a mean flow solution is calculated with an imposed transition front that aligns with the shock front from the fully turbulent solution. Subsequently, stability computations are performed along a set of streamlines across the wing to calculate the amplification of planar Tollmien-Schlichting (TS) and stationary crossflow (CF) modes. The transition criterion based on the dual N-factor method is used to infer the updated transition front and the process is successively repeated until convergence of the solution. Within three iterations, the predicted fronts for angles of attack of 1.45, 1.98, 2.46 and 2.94 degrees and a mean-aerodynamic-chord Reynolds number equal to 15 million, approach visual convergence in most regions of the studied cases, and the resulting predictions are in good agreement with the transition fronts deduced from measurements of temperature-sensitive paint. Even though surface pressure measurements based on fully-turbulent flow agree well with the measured pressure coefficient distributions, strong viscous-inviscid interaction effects cause significant shifts in the shock locations based on the imposed transition front, underscoring the intrusive nature of static pressure measurements using surface mounted ports on the CRM-NLF configuration.

Boundary Layer Transition↗

Ab-Initio Study of Stacking Fault Segregation Behavior in Ni-based Superalloys at High Temperatures

Ni-based superalloys demonstrate extraordinary creep properties compared to traditional metallic systems due to the formation of L12 (γ’) precipitates. Despite experimental evidence of alloying element segregation to the stacking faults, prior ab-initio efforts indicated repulsion of Nb from superlattice intrinsic stacking faults (SISFs) . Due to the importance of this element in key strengthening mechanisms, we developed a new technique to account for multi-component segregation behavior at temperature combining ab-initio molecular dynamics (AIMD) and Monte-Carlo (MC) simulations. Using this technique, we replicated experimentally observed segregation behavior of Nb, Co, and Ti to the SISF in L12 (Figure 1). Furthermore, we investigated the co-segregation behaviors of individual pairs of alloying elements to determine the interaction effects which lead to this segregation behavior in the full alloy system. By simulating the reduced-chemistry models using our approach, we reconciled previous ab-initio calculations demonstrating repulsion of Nb from the SISF and the experimentally observed segregation behavior.

Molecular Dynamics↗

Development of the Dust Ejecta Radar Technology (DERT) to Determine Plume-Surface Interaction Ejecta Velocities on Planetary Surfaces

Here we present a novel use of millimeter wave doppler radar to measure the velocity of ejecta generated by the impingement of rocket plumes on a planetary surface. The Dust Ejecta Radar Technology (DERT) provides a unique dataset based on direct measurements of ejecta particle velocities during plume-surface interactions. DERT is a continuous wave (CW) 94 GHz radar unit that is being developed at Kennedy Space Center. DERT has measured velocities of a pendulum (~ 1 m/s), a rotating strip (60 m/s), projected regolith simulant BP-1 (~ 250 m/s) and rifle rounds (~ 820 m/s). Signal-to-Noise Ratios of up to 60 dB have been demonstrated. Data collected from DERT will inform the development of high-fidelity computational models of plume-surface interaction effects and will help address NASA Strategic Knowledge Gaps related to characterizing entry, descent and landing effects, and the risks associated with high-speed ejecta on the lander and lunar surface assets.

PSI↗

Dust Ejecta RADAR Technology (DERT): A Millimeter Wave Doppler Radar to Measure Plume Surface Interaction Ejecta Velocities

A novel method to measure the velocity of ejecta generated by the impingement of rocket plumes on a lunar or planetary surface is presented. Dust Ejecta RADAR Technology (DERT), is a Millimeter Wave Doppler Radar sensor that provides a unique dataset based on direct measurements of ejecta particle velocities during plume-surface interactions, which will help inform risk assessments associated with impacts by high-speed ejecta particles. DERT has measured velocities of a pendulum (~1 m/s), a rotating strip (60 m/s), projected regolith simulant BP-1 (~250 m/s) and rifle rounds (~820 m/s). Signal-to-noise ratios of up to 60 dB with regolith simulant BP-1 have been demonstrated with a CW 94 GHz unit. Data collected from DERT will inform the development of high-fidelity computational models of plume-surface interaction effects and will help address NASA Strategic Knowledge Gaps related to characterizing entry, descent and landing effects, and the risks associated with high-speed ejecta on the lander and lunar surface assets. Recent efforts to develop DERT as a flight instrument are presented as well as the development of a Lunar Regolith Ejecta Simulator (LuRES) system to calibrate DERT.

PSI↗

Development of the Dust Ejecta Radar Technology (DERT) to Determine Plume-Surface Interaction Ejecta Velocities on Planetary Surfaces

Here we present a novel use of millimeter wave doppler radar to measure the velocity of ejecta generated by the impingement of rocket plumes on a planetary surface. The Dust Ejecta Radar Technology (DERT) provides a unique dataset based on direct measurements of ejecta particle velocities during plume-surface interactions. DERT is a continuous wave (CW) 94 GHz radar unit that is being developed at Kennedy Space Center. DERT has measured velocities of a pendulum (~ 1 m/s), a rotating strip (60 m/s), projected regolith simulant BP-1 (~ 250 m/s) and rifle rounds (~ 820 m/s). Signal-to-Noise Ratios of up to 60 dB have been demonstrated. Data collected from DERT will inform the development of high-fidelity computational models of plume-surface interaction effects and will help address NASA Strategic Knowledge Gaps related to characterizing entry, descent and landing effects, and the risks associated with high-speed ejecta on the lander and lunar surface assets.

PSI↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States; NREL (National Renewable Energy Laboratory)

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States: Preprint

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

DEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and domestic hot water. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of an on-going project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users’ decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit. DEEP will be migrated into the DEnCity - DOE’s Energy City, which integrates large-scale energy data for multi-purpose, open, and dynamic database leveraging diverse source of existing simulation data.

Hoon Lee, Sang↗

Dynamic Modeling of Learning in Emerging Energy Industries: The Example of Advanced Biofuels in the United States

This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.

09 BIOMASS FUELS↗

Study of a Novel Oscillating Surge Wave Energy Converter: Preprint

This study investigates the performance of an oscillating surge wave energy converter (OSWEC) that utilizes adjustable geometry as a means of controlling the hydrodynamic coefficients, a concept originally proposed by [1]. The body of the device consists of a bottom-hinged solid rectangular frame with five horizontal flaps spanning the interior of the frame. The flaps can rotate independently about their center of rotation within the frame like a large window shutter. Changing the orientation of the flaps alters the hydrodynamic coefficients and natural frequency of the device as well as the ability to shed or absorb structural loads accordingly. This ability may allow the device to operate in a wider range of sea states than other current wave energy converter designs. This paper presents and compares the results of numerical simulations and experimental testing of the OSWEC's response to regular waves with all five of the horizontal fin configurations sharing the same orientation of 0 degrees (fully closed interior) and 90 degrees (fully open). The numerical simulations were performed using WAMIT, which calculates hydrodynamic coefficients using a boundary element method code to solve the linear potential flow problem, and WEC-Sim, a MATLAB-based tool that simulates multibody devices in the time domain by solving the governing equations of motion. A 1:14 scale model of the device was built for experimental evaluation in an 8-m-long, 1-m wide wave tank, which supports a water depth of 0.7 m. The OSWEC motion in different wave conditions was measured with displacement sensors while nonlinear wave-structure interaction effects like slamming and overtopping were captured using a high-speed camera and used to understand differences between the simulation and experiments.

13 HYDRO ENERGY↗

DEEP: Database of Energy Efficiency Performance

A database of energy efficiency performance (DEEP) is a presimulated database to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 10 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER [sic] prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air conditioning, plug loads, and domestic hot war. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center (NERSC) of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of the CEC PIER project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users' decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit.

Hong, Tianzhen↗

Superconductivity in a doped valley coherent insulator in magic angle graphene: Goldstone-mediated pairing and Kohn-Luttinger mechanism

We consider magic angle graphene in the doping regime around charge neutrality and study the connection between a recently proposed inter-valley coherent insulator at zero doping and the neighboring superconducting domes. The breaking of the valley U(1) symmetry leads to massless Goldstone modes, which couple to the doped charge carriers. We derive the effective interaction between these Goldstone modes and the conduction electrons and study its role in mediating superconductivity. Combining it with the screened Coulomb potential, we find weak-coupling superconducting instabilities in the two-component p- and d-wave channels. The competition between the two channels is set by the distance between the bilayer graphene device and the metallic gates. We find that the p-wave instability originates from the attraction mediated by the Goldstone modes, while the d-wave pairing is caused purely by the screened Coulomb interaction, similarly to the Kohn-Luttinger mechanism.

Kozii, Vladyslav↗

ExaWind: Exascale Predictive Wind Plant Flow Physics Modeling

The scientific goal of the ExaWind project is to advance our fundamental understanding of the flow physics governing whole wind plant performance, including wake formation, complex terrain impacts, and turbine-turbine-interaction effects. The primary application codes in the ExaWind environment are Nalu-Wind, an unstructured-grid computational fluid dynamics (CFD) code, AMR-Wind, a structured-grid CFD code, and OpenFAST, a whole-turbine simulation code. In this poster we present our progress towards simulating the ExaWind challenge problem, which is a predictive simulation of a wind farm with tens of megawatt-scale wind turbines dispersed over an area of 50 square kilometers.

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

ExaWind: Then and Now

The scientific goal of the ExaWind project is to advance our fundamental understanding of the flow physics governing whole wind plant performance, including wake formation, complex terrain impacts, and turbine-turbine-interaction effects. The primary application codes in the ExaWind environment are Nalu-Wind, an unstructured-grid computational fluid dynamics (CFD) code, AMR-Wind, a structured-grid CFD code, and OpenFAST, a whole-turbine simulation code. In this poster we present the current status of the ExaWind software stack in the context of the modeling and simulation capabilities when the project started in 2016.

computational fluid dynamics↗

Neutron Structure Functions at Large Bjorken X

The E12-10-002 (F2) experiment ran in Hall C at JLab to extract the F2 structure functions of proton and neutron from inclusive H(e, e0) and D(e, e0) reactions in the high Bjorken x region. Those extractions put constraints on the Parton Distribution Functions PDFs (especially at large Bjorken x), and facilitate the study of Quark Hadron Duality. The F2 experiment measurements covers a large kinematic range in x from 0.2 to 1.0, and in Q2 from 4 to 16 GeV2 . While the proton F2 structure function has been studied extensively through inelastic electron-proton scattering, much less is known about neutron structure due to the unavailability of high density, free neutron targets. The BONuS12 experiment was proposed to measure the neutron F2 on a nearly free neutron within a weakly bound deuteron target via the spectator tagging method. Tagging the slow backward moving spectator protons minimizes both off-shell and final-state interaction effects, and the measured proton momentum is used to correct for the initial-state momentum of the struck neutron. The recoil detector is used to detect spectator protons with momenta 70 < ps < 150 MeV/c. This dissertation outlines the design, construction and testing of the recoil detector, Radial Time Projection Chamber (RTPC) and discusses the results of the H(e, e0) and D(e, e0) cross sections and the F2 structure functions obtained from the Hall C F2 data analysis.

Nadeeshani, Sooriyaarachchilage↗