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NASA NTRS1977

Inlet Reynolds number and temperature effects on the steady-state performance of a TFE731-2 turbofan engine

Effects of varying engine inlet Reynolds number index (0.75, 0.50, 0.25, and 0.12) and temperature (289 and 244 K) on a TFE731-2 turbofan engine were evaluated. Results were classified as either compression system effects or effects on overall performance. Standard performance maps are used to present compression system performance. Overall performance parameters are presented as a function of low rotor speed corrected to engine inlet temperature.

Bobula, G. A.↗

NASA NTRS1979

On the rational design of compressible flow ejectors

A fluid mechanics review of chemical laser ejectors is presented. The characteristics of ejectors with single and multiple driver nozzles are discussed. Methods to compute an optimized performance map in which secondary Mach number and performance are computed versus mass ratio, to compute the flow distortion at each optimized condition, and to determine the thrust area for the design point to match diffuser impedence are examined.

Ortwerth, P. J.↗

DOE OSTI2023

Field Validation of Air-Source Heat Pumps for Cold Climates

Heating energy is the largest end-use for U.S. residential buildings accounting for approximately one-third of residential building energy consumption (EIA 2021). Historically, air-source heat pumps have been limited to temperate climates because of subpar performance at extremely cold outdoor air temperatures. However, recent advances to cold-climate air-source heat pump technology, which typically rely on inverter-driven, variable-speed compressors and variable-speed fans, have significantly improved low-temperature heat pump performance enabling the technology to save energy for many homes in cold climates. The primary objective of this project was to measure in-field performance of centrally ducted, variable-capacity air-source heat pumps in cold climates to validate performance and develop field-based performance maps. The project focused on quantifying heat pump performance at cold temperatures. The sites identified for the study were primarily located in the Northwest United States since homes in the region tend to have all-electric space heating systems and high-efficiency heat pumps have been incentivized in the region for several years. NREL partnered with Ecotope, Inc., a small energy consulting firm located in Seattle, WA, for site recruitment, monitoring equipment installation, data quality management. All the sites included in the study had previously installed a high-efficiency, central heat pump system. One site was in a Denver, CO suburb, which was the only dual fuel heat pump in the study. We used airside and power measurements, collected at 5-second intervals, to quantify heat pump capacity, coefficient of performance (COP), and auxiliary heater energy consumption. We developed algorithms to automatically determine the heat pump operating mode including defrost and auxiliary heating operation. A whole-house thermal and duct audit was completed during the initial site visit to estimate winter heating loads and assess heat pump sizing. Whole-home heating design loads were calculated at ASHRAE 99% design temperatures and compared to manufacturer-reported maximum capacities to assess the heat pump sizing at each site.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2016

NDARC NASA Design and Analysis of Rotorcraft - Input, Appendix 4

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description consists of all the information, input and derived, that denes the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions. The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for anti-torque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude.

Rotorcraft Input↗

NASA NTRS2002

An Overview of Trajectory Design Operations for the Microwave Anisotropy Probe (MAP) Mission

The main science objective of the Microwave Anisotropy Probe (MAP) mission is to produce an accurate full-sky map of the cosmic microwave background temperature fluctuations - anisotropy. MAP will collect these measurements from a lissajous orbit about the Sun-Earth/Moon L2 Lagrange Point. The NASA Goddard Space Flight Center (GSFC) Flight Dynamics Analysis Branch provided mission analysis, maneuver planning and maneuver calibration for the MAP spacecraft. This paper will provide an overview of the MAP trajectory design, a summary of the maneuvers executed. Differences from the pre-launch nominal plan will also be discussed. During the MAP phasing loops, MAP performed three calibration maneuvers in order to characterize the performance of the primary sets of thrusters - +X, +Z, and -Z. The calibration maneuvers were designed to minimize their impact on the trajectory. Four maneuvers were performed to set up the gravity assist of the Moon - required to propel MAP out to its orbit about L2. These maneuvers were performed at the three phasing loop perigees and at 18 hours after the final perigee. It became necessary to alter some of the perigee maneuvers in order to shape the gravity assist. This shaping was done to help meet some mission goals. In particular, the gravity assist was changed slightly in order to remove lunar shadows in both the cruise out to L2 and in the first revolution about L2. This amounted to a change in the phasing loop AV of less than 1 m/s. After the gravity assist, two mid-course correction (MCC) maneuvers were performed in order to fine-tune the trajectory. MCC1 was used to clean up and errors which resulted from the gravity assist. MCC2 was performed in order to mitigate a large stationkeeping maneuver following a crucial instrument calibration period during the cruise phase. MAP executed it's first stationkeeping maneuver in January 16th and is ready for a second calibration period during late Winter / early Spring. Further information concerning subsequent stationkeeping maneuver will be added as they become available.

Cuevas, Osvaldo O.↗

NASA NTRS1977

NSEG, a segmented mission analysis program for low and high speed aircraft. Volume 1: Theoretical development

A rapid mission analysis code based on the use of approximate flight path equations of motion is presented. Equation form varies with the segment type, for example, accelerations, climbs, cruises, descents, and decelerations. Realistic and detailed characteristics were specified in tabular form. The code also contains extensive flight envelope performance mapping capabilities. Approximate take off and landing analyses were performed. At high speeds, centrifugal lift effects were accounted for. Extensive turbojet and ramjet engine scaling procedures were incorporated in the code.

Hague, D. S.↗

NASA NTRS1977

NSEG: A segmented mission analysis program for low and high speed aircraft. Volume 2: Program users manual

A rapid mission analysis code based on the use of approximate flight path equations of motion is described. Equation form varies with the segment type, for example, accelerations, climbs, cruises, descents, and decelerations. Realistic and detailed vehicle characteristics are specified in tabular form. In addition to its mission performance calculation capabilities, the code also contains extensive flight envelop performance mapping capabilities. Approximate take off and landing analyses can be performed. At high speeds, centrifugal lift effects are taken into account. Extensive turbojet and ramjet engine scaling procedures are incorporated in the code.

Hague, D. S.↗

NASA NTRS1981

Mission options for the first SEPS application

Missions to comets and asteroids are primary candidates for Solar Electric Propulsion System (SEPS) applications. NASA estimates that the first SEPS mission might be launched as early as 1988. This paper presents mission opportunities available for launches between 1988 and early 1991 and discusses the performance capabilities of the current SEPS. Use of a Shuttle Two-Stage IUS and/or a Shuttle Wide Tank Centaur launch vehicle is assumed in the performance assessment. The list of possible first SEPS missions consists of nine missions to comets of primary interest and examples of multiple asteroid rendezvous missions. Both an earth crossing asteroid and a main belt asteroid are considered as first possible targets in the multiple asteroid rendezvous examples. Mission opportunity and performance maps for Eros and Anteros are presented which provide exact performance data and optimal launch and arrival dates for any launch year.

Yen, C.-W. L.↗

NASA NTRS1983

Formulas for Precise Transverse Mercator Projection

Transverse mercator projection, surface of Earth or other spheroid is mapped onto cylinder tangent at meridian of longitude. New method performs mapping by means of mathematical series in which higher order terms correct for deviation from exact sphericity. New method yields precise geodetic maps.

Wallis, D. E.↗

NASA NTRS1980

Inert gas ion thruster development

Two 12 cm magneto-electrostatic containment (MESC) ion thrusters were performance mapped with argon and xenon. The first, hexagonal, thruster produced optimized performance of 48.5to 79 percent argon mass utilization efficiencies at discharge energies of 240 to 425 eV/ion, respectively, Xenon mass utilization efficiencies of 78 to 95 percent were observed at discharge energies of 220 to 290 eV/ion with the same optimized hexagonal thruster. Changes to the cathode baffle reduced the discharge anode potential during xenon operation from approximately 40 volts to about 30 volts. Preliminary tests conducted with the second, hemispherical, MESC thruster showed a nonuniform anode magnetic field adversely affected thruster performance. This performance degradation was partially overcome by changes in the boundary anode placement. Conclusions drawn the hemispherical thruster tests gave insights into the plasma processes in the MESC discharge that will aid in the design of future thrusters.

Ramsey, W. D.↗

NASA NTRS2010

Testing of Liquid Metal Components for Nuclear Surface Power Systems

The Early Flight Fission Test Facility (EFF-TF) was established by the Marshall Space Flight Center (MSFC) to provide a capability for performing hardware-directed activities to support multiple in-space nuclear reactor concepts by using a non-nuclear test methodology. This includes fabrication and testing at both the module/component level and near prototypic reactor configurations. The EFF-TF is currently supporting an effort to develop an affordable fission surface power (AFSP) system that could be deployed on the Lunar surface. The AFSP system is presently based on a pumped liquid metal-cooled (Sodium-Potassium eutectic, NaK-78) reactor design. This design was derived from the only fission system that the United States has deployed for space operation, the Systems for Nuclear Auxiliary Power (SNAP) 10A reactor, which was launched in 1965. Two prototypical components recently tested at MSFC were a pair of Stirling power conversion units that would be used in a reactor system to convert heat to electricity, and an annular linear induction pump (ALIP) that uses travelling electromagnetic fields to pump the liquid metal coolant through the reactor loop. First ever tests were conducted at MSFC to determine baseline performance of a pair of 1 kW Stirling convertors using NaK as the hot side working fluid. A special test rig was designed and constructed and testing was conducted inside a vacuum chamber at MSFC. This test rig delivered pumped NaK for the hot end temperature to the Stirlings and water as the working fluid on the cold end temperature. These test were conducted through a hot end temperature range between 400 to 550C in increments of 50 C and a cold end temperature range from 30 to 70 C in 20 C increments. Piston amplitudes were varied from 6 to 1 1mm in .5 mm increments. A maximum of 2240 Watts electric was produced at the design point of 550 hot end, 40 C cold end with a piston amplitude of 10.5mm. This power level was reached at a gross thermal efficiency of 28%. A baseline performance map was established for the pair of 1kW Stirling convertors. The performance data will then be used for design modification to the Stirling convertors. The ALIP tested at MSFC has no moving parts and no direct electrical connections to the liquid metal containing components. Pressure is developed by the interaction of the magnetic field produced by the stator and the current which flows as a result of the voltage induced in the liquid metal contained in the pump duct. Flow is controlled by variation of the voltage supplied to the pump windings. Under steady-state conditions, pump performance is measured for flow rates from 0.5-4.3 kg/s. The pressure rise developed by the pump to support these flow rates is roughly 5-65 kPa. The RMS input voltage (phase-to-phase voltage) ranges from 5-120 V, while the frequency can be varied arbitrarily up to 60 Hz. Performance is quantified at different loop temperature levels from 50 C up to 650 C, which is the peak operating temperature of the proposed AFSP reactor. The transient response of the pump is also evaluated to determine its behavior during startup and shut-down procedures.

Polzin, Kurt A.↗

NASA NTRS2021

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗

NASA NTRS1990

Workload and strategic adaptation under transformations of visual-coordinative mappings

A study involving a bimanual pursuit-tracking task is conducted to examine strategic exploration of differing visual and motor coordination patterns emphasizing workload as an indicator of strategic behavior. The mappings are conducted for 16 possible variations of order, speed, and combination. Performance is assessed by means of the rms and percent time-on-target, and the NASA task-load index is used to classify subjective reports on workload. The results are broken down into four primary performance mappings and four hybrid mappings called contradictory conditions. The order of difficulty of the conditions is apparently determined by the workload, except that in the case of the three most difficult decoupled conditions some dissociation is reported.

Caird, J. K.↗

DOE OSTI2026

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗

NASA NTRS2022

NDARC - NASA Design and Analysis of Rotorcraft: Input and Data Structures - Vol 2

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NASA NTRS2022

NDARC - NASA Design and Analysis of Rotorcraft: Input - Vol 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NASA NTRS2023

NDARC - NASA Design and Analysis of Rotorcraft: Input - Appendix 3

The NDARC code performs design and analysis tasks. The design task involves sizing the rotorcraft to satisfy specified design conditions and missions. The analysis tasks can include off-design mission performance analysis, flight performance calculation for point operating conditions, and generation of subsystem or component performance maps. Figure 1-1 illustrates the tasks. The principal tasks (sizing, mission analysis, flight performance analysis) are shown in the figure as boxes with heavy borders. Heavy arrows show control of subordinate tasks. The aircraft description (figure 1-1) consists of all the information, input and derived, that defines the aircraft. The aircraft consists of a set of components, including fuselage, rotors, wings, tails, and propulsion. This information can be the result of the sizing task; can come entirely from input, for a fixed model; or can come from the sizing task in a previous case or previous job. The aircraft description information is available to all tasks and all solutions (indicated by light arrows). The sizing task determines the dimensions, power, and weight of a rotorcraft that can perform a specified set of design conditions and missions. The aircraft size is characterized by parameters such as design gross weight, weight empty, rotor radius, and engine power available. The relations between dimensions, power, and weight generally require an iterative solution. From the design flight conditions and missions, the task can determine the total engine power or the rotor radius (or both power and radius can be fixed), as well as the design gross weight, maximum takeoff weight, drive system torque limit, and fuel tank capacity. For each propulsion group, the engine power or the rotor radius can be sized. Missions are defined for the sizing task, and for the mission performance analysis. A mission consists of a number of mission segments, for which time, distance, and fuel burn are evaluated. For the sizing task, certain missions are designated to be used for design gross weight calculations; for transmission sizing; and for fuel tank sizing. The mission parameters include mission takeoff gross weight and useful load. For specified takeoff fuel weight with adjustable segments, the mission time or distance is adjusted so the fuel required for the mission (burned plus reserve) equals the takeoff fuel weight. The mission iteration is on fuel weight or energy. Flight conditions are specified for the sizing task, and for the flight performance analysis. For the sizing task, certain flight conditions are designated to be used for design gross weight calculations; for transmission sizing; for maximum takeoff weight calculations; and for antitorque or auxiliary thrust rotor sizing. The flight condition parameters include gross weight and useful load. For flight conditions and mission takeoff, the gross weight can be maximized, such that the power required equals the power available. A flight state is defined for each mission segment and each flight condition. The aircraft performance can be analyzed for the specified state, or a maximum effort performance can be identified. The maximum effort is specified in terms of a quantity such as best endurance or best range, and a variable such as speed, rate of climb, or altitude. The aircraft must be trimmed, by solving for the controls and motion that produce equilibrium in the specified flight state. Different trim solution definitions are required for various flight states. Evaluating the rotor hub forces may require solution of the blade flap equations of motion.

NDARC↗

NASA NTRS1977

NSEG: A segmented mission analysis program for low and high speed aircraft. Volume 3: Demonstration problems

Program NSEG is a rapid mission analysis code based on the use of approximate flight path equations of motion. Equation form varies with the segment type, for example, accelerations, climbs, cruises, descents, and decelerations. Realistic and detailed vehicle characteristics are specified in tabular form. In addition to its mission performance calculation capabilities, the code also contains extensive flight envelope performance mapping capabilities. For example, rate-of-climb, turn rates, and energy maneuverability parameter values may be mapped in the Mach-altitude plane. Approximate take off and landing analyses are also performed. At high speeds, centrifugal lift effects are accounted for. Extensive turbojet and ramjet engine scaling procedures are incorporated in the code.

Hague, D. S.↗