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NASA NTRSDate not supplied

Modeling and Simulation of Tank Pressure Control using Zero-Boiloff Active Thermal Control for LOXSAT Technology Demonstration Mission

To-date, research and modeling of cryogenic fluid management technologies (CFM) for spaceflight has been limited to ground tests, short-duration zero-g simulations (e.g. drop towers), and small-scale experiments on-orbit. There has not been a large-scale flight demonstration of a flight-like system. As future NASA missions to take humans further from Earth will require large, in-space cryogenic propulsion vehicles, it is imperative to begin collecting flight data for these systems to accurately model and design future vehicles. To meet this goal, NASA awarded tipping point technology demonstration awards to Eta Space, Lockheed Martin, Space Exploration Technologies (SpaceX), and United Launch Alliance (ULA) to demonstrate on-orbit storage and transfer of cryogenic propellant. For its award, Eta Space is developing LOXSAT-1. It is a small satellite that will be launched on a Rocket Lab Electron rocket. The spacecraft consists of a Rocket Lab Photon spacecraft bus with a primary payload of a spherical liquid oxygen (LOX) storage tank with thermodynamic control systems. The primary objective of the mission is to demonstrate zero-boil-off storage of liquid oxygen. To accomplish this objective, the payload is equipped with an active thermal control system fluid loop that consists of propellant management device (PMD), positive-displacement pump, heat exchanger connected to a cryocooler, and a spray bar mixing injector. When the fluid loop is operating, fluid is drawn from the tank by the PMD and pumped through the heat exchanger, lowering the fluid temperature below the fluid temperature in the tank. This subcooled liquid is then injected back into the tank through the spray bar. The subcooled injected liquid has two effects. If it is sprayed into the ullage space, the injected liquid will form into jets or droplets and exchange heat with the ullage gas. This will cool and condense the gas, reducing the pressure in the tank. Additionally, the liquid that is not sprayed through the ullage, as well as any remaining liquid spray from the ullage, will rejoin the liquid mass of the tank, lowering the bulk temperature of the liquid. These combines effects provide for zero-boil off pressure control by lowering the tank pressure and the liquid saturation pressure simultaneously, ensuring the liquid stays subcooled. To model these complex mechanics and predict the performance of the active thermal control system, NASA is providing Eta Space with 3 parallel models of the tank. The approach of providing 3 different models allows for cross-checking and comparisons between the three to better understand how different modeling assumptions and selection semi-empirical factors affects the modeling result. Additionally, developing 3 models provides three different schemes for numerical simulation, providing confidence that results depict real physical phenomenon and not numerical quirks of the program. Within the tank thermodynamics, there are two primary areas of heat transfer we concern ourselves with: the heat transfer between the ullage space and the droplet spray, and between the ullage space and bulk liquid. For the droplet heat transfer, there are multiple sets of assumptions that can be made and correlations that can be used. Currently, two working models - the TankSIM model and Easy5 model – provide for an overview of the different approaches available. The TankSIM model and Easy5 model use two different models for droplet heating and evaporation that illustrate how the models use different types of mechanisms to arrive at the same answer. For the TankSIM model, droplets are treated as spheres of constant radius. Heat is transferred from the ullage to the droplet and warms the droplet until it reaches saturation, then the droplet begins evaporating and reducing its radius and mass. To calculate the heat transfer coefficient between the droplet and ullage, the Ranz-Marshall correlation is used. To determine the number of droplets in the ullage, a resident mass approach is used. This approach averages the number of droplets such that residuals at the start-up and shut-off of the spray bar cancel out. This same approach is used in the Easy5 model. The GFSSP model implements a linked list to track individual droplet “nodes” within the model. For the Easy5 model, the droplet is assumed to have an interface at a temperature equal to the saturation temperature corresponding to the pressure of the gas phase. The heat transfer from the gas to the interface and the interface to the droplet bulk is then calculated, and the net mass transfer between the droplet and interface is determined by performing an energy balance across the interface. For the gas side of the interface, the Ranz-Marshall correlation is used. For the liquid side of the interface, a variety of correlations were tried, including Kronig and Brink (1950) and effective conductivity models. As a result of these assumptions, the Easy5 model currently predicts faster depressurization, as at saturated vapor conditions, the heat transfer coeffect on the liquid side for the Easy5 model is greater than the heat transfer coefficient predicted by Ranz-Marshall used in the TankSIM code. This greater heat flux translates into faster condensation of the saturated ullage gas. At the bulk liquid to ullage interface, the models are in much closer agreement. Both models model the ullage as a sphere centered within the bulk liquid in the tank, and both use the energy-jumping boundary condition to model heat and mass transfer across the interface. There are slight differences in how the interface temperature is calculated, however. The Easy5 model assumes the temperature of the interface is equal to the saturation temperature associated with the pressure of the gas phase. The TankSIM model calculates this temperature with Alabovskii’s equation, which provides a correction factor for interface temperatures. Analysis tasks are focused on determining rates of depressurization within the tank during active cooling operation. To maintain net positive suction head at the pump inlet, the tank pressure cannot fall faster than the saturation pressure associated with the temperature of the bulk liquid. Additionally, there is interest in analyzing the performance of the loop at different pump speeds and cryocooler input powers. Adjusting the flowrate affects both the performance of the heat exchanger between the cryocooler and pumped liquid, and the heat transfer between the droplet spray and the ullage. Ideally, a pump speed and cryocooler power can be selected that will allow the tank to operate in zero-boil-off mode with a very narrow range of storage pressure.

zero boil-off↗

NASA NTRS1992

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

The need to record some measure of the low-gravity environment of an orbiting space vehicle was recognized at an early stage of the U.S. Space Program. Such information was considered important for both the assessment of an astronaut's physical condition during and after space missions and the analysis of the fluid physics, materials processing, and biological sciences experiments run in space. Various measurement systems were developed and flown on space platforms beginning in the early 1970's. Similar in concept to land based seismometers that measure vibrations caused by earthquakes and explosions, accelerometers mounted on orbiting space vehicles measure vibrations in and of the vehicle due to internal and external sources, as well as vibrations in a sensor's relative acceleration with respect to the vehicle to which it is attached. The data collected over the years have helped to alter the perception of gravity on-board a space vehicle from the public's early concept of zero-gravity to the science community's evolution of thought from microgravity to milligravity to g-jitter or vibrational environment. Since the advent of the Shuttle Orbiter Program, especially since the start of Spacelab flights dedicated to scientific investigations, the interest in measuring the low-gravity environment in which experiments are run has increased. This interest led to the development and flight of numerous accelerometer systems dedicated to specific experiments. It also prompted the development of the NASA MSAD-sponsored Space Acceleration Measurement System (SAMS). The first SAMS units flew in the Spacelab on STS-40 in June 1991 in support of the first Spacelab Life Sciences mission (SLS-1). SAMS is currently manifested to fly on all future Spacelab missions.

Rogers, Melissa J. B.↗

NASA NTRS1983

Radiation enhancement by nonequilibrium in earth's atmosphere

The status of knowledge of shock-layer radiation in the low-density, nonequilibrium regime, as appropriate to the flight of the proposed aero-assisted orbital transfer vehicle, is surveyed. The existing laboratory data and the flight data from Apollo and Fire are scrutinized. Nonequilibrium radiation is found to be significant in the flight regime of the vehicle, but a factor of 3 uncertainty is found in its magnitude. The available theoretical models are reviewed, their weaknesses are pointed out, a computer code that approximately reproduces the existing data is introduced, and recommendations are made for future research.

Park, C.↗

NASA NTRS1991

Expert systems for assembly sequence evaluation

The objective is to identify delivered orbital subassemblies derived from a phase A conceptual space vehicle design while minimizing on-orbit assembly complexity. The topics covered are presented in viewgraph form and include the following: an orbital assembly scenario; subassemblies; subassembly identification and simulation model; estimating subassembly interfaces by engineering functional allocation using MBR; representative data base of interface connections; vehicle decomposition model; connection interface estimation model results; knowledge-source 1 and 2 results; knowledge-source 3 -- connection-index results (Boeing NTR-2016 CI-profile); KS3 algorithm, and KS3 flight manifest results.

Jolly, Steve↗

NASA NTRSDate not supplied

NASA and Advanced Air Mobility (AAM) National Campaign (NC) Tech Talk: Integrated Data Product

NASA Advanced Air Mobility (AAM) National Campaign has hosted multiple flight tests in a effort to promote public confidence and accelerate the realization of emerging aviation markets for passenger and cargo transportation in urban, suburban, rural, and regional environments. The goals and objectives for each flight test are intended to assess the performance of the vehicle’s capacity to operate safely, efficiently, and sustainably in urban areas. The Airspace Test and Infrastructure (ATI) team processes the flight data to evaluate the effectiveness of air vehicle and airspace management integration, while its analysis capabilities support the assessment of the efficacy of proposed vehicles and ground systems required to enable the vehicles’ operations. The ATI data services team creates many products from the data, first by transforming and merging the data into a single Integrated Data Product (IDP). This aligns data from many sources by time, so that, for example, the winds that impacted a flight can be aligned with its ground track and speed. A detailed IDP enables many types of statistical computation and visualizations that help researchers understand what transpired during the flight and how it can be explained. This Tech Talk will give an overview of the IDP process, including examples of the resulting products created by the data services team. It will also share an application that will allow participants to perform their own data analysis.

National Campaign, Advanced Air Mobility, Integrat↗

NASA NTRS1966

Advanced telemetry system with adaptive capability Final technical summary report, 1 Jul. 1964 - 25 Feb. 1966

Data processing telemetry system with adaptive control for application in space vehicle environment

DATA PROCESSING↗

NASA NTRS2000

Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy

Aerospace vehicles are produced in limited quantities that do not always allow development of MIL-HDBK-5 A-basis design allowables. One method of examining production and composition variations is to perform 100% lot acceptance testing for aerospace Aluminum (Al) alloys. This paper discusses statistical trends seen in strength data for one Al alloy. A four-step approach reduced the data to residuals, visualized residuals as a function of time, grouped data with quantified scatter, and conducted analysis of variance (ANOVA).

Neergaard, Lynn↗

NASA NTRS2001

Statistical Analysis of Strength Data for an Aerospace Aluminum Alloy

Neergaard, L.↗

NASA NTRSDate not supplied

Multihierarchy Gaussian Process Models for Probabilistic Aerodynamic Databases using Uncertain Nominal and Off-Nominal Configuration Data

Probabilistic aerodynamic databases are a crucial component of the development lifecycle for aerospace vehicles. A key challenge when building aerodynamic databases is that most data used to construct them represent various simplifications of the real flight vehicle. For example, wind tunnel models often simplify the vehicle geometry and surface roughness characteristics, while CFD computations often make simplifications to the physics being modeled, such as fully laminar or turbulent calculations. Multifidelity data fusion models rely on a user being able to define a hierarchy of fidelity levels anchored to some "truth" data. This approach is unsatisfactory when no data can be considered to accurately reflect real flight conditions. In this work, we provide an alternative approach by presenting a consistent mathematical framework for building probabilistic aerodynamic databases in the form of a conditional probability distribution described by an ensemble of multifidelity Gaussian Processes. Instead of relying on a single hierarchy of data fidelity levels, the presented framework identifies a "nominal" configuration and potential corrections to the nominal which represent specific physical phenomena not represented in the nominal data. The nominal and correction functions themselves are constructed as multifidelity Gaussian Processes and linearly combined to form an ensemble model which fuses the uncertainties associated nominal and correction models. Results obtained using the proposed framework on a simplified Orion Crew Module wind tunnel dataset demonstrate the predictive capability of the multihierarchy framework. We further demonstrate the benefits of such a probabilistic aerodynamic database approach through function sampling and computing the conditional distributions of derived quantities, such as the trim angle of attack and aerodynamic coefficients at trim.

Gaussian Processes↗

NASA NTRSDate not supplied

AEGIS: Autonomous Entity Global Intelligence System for Urban Air Mobility

This paper presents a global intelligence system that synthesizes aerial vehicles’ real-time physical data, planned actions, and historical behavior into engineered data frames representing the collective state of the airspace and suitable for efficient machine learning consumption. These data frames are then learnt by a deep neural net to build a prediction model that estimates the expected evolution path of the current state, thereby identifying potential future conflicts. This approach lends itself to an automated early warning system that the aerial vehicles can implement onboard with a suitable edge computing module more efficiently and effectively than non-AI methods, and eventually take preventive or corrective measures towards self/collaborative resolution of the issues. Contrary to a centralized early warning system where all vehicles’ task-space eventually converges to a global optimum state, the presented distributed global intelligence system brings in a balance between local utility functions of each vehicle and the global operating framework. This contributes to effectively handle the potential massive scaling in urban air mobility in the near future.

Artificial Intelligence↗

NASA NTRS1987

An aerothermodynamic study of slender conical vehicles

A numerical study was performed to assess the applicability of some current techniques which can be used for aerothermal predictions over slender spherically blunted cones. Predictions using a viscous-shock-layer method and several engineering approaches were compared with experimental results from flight and ground-based tests, with each other, and with other detailed results. Good agreement was obtained in comparisons with laminar and turbulent heating data from the Reentry F flight vehicle and with the wind-tunnel data. In particular, the viscous-shock-layer method was shown to yield excellent comparisons and should be useful in providing detailed flowfield and surface values for slender blunted cones. Additional predictions were obtained with these methods for two 5-deg half-angle cones with different nose radii to illustrate the effects of nose bluntness and angle of attack on drag and heat transfer. These results demonstrate the benefit of nose blunting with respect to heating and drag for laminar and transitional flow at zero-lift conditions and the benefit of heating reduction at angle of attack. Detailed comparison of the engineering code predictions with the viscous-shock-layer results for these additional cases generally showed good agreement except for the laminar prodictions at angle of attack on the forward cone surface. Nonequilibrium calculations at 0-deg angle of attack showed that substantial benefits of low surface catalysis existed only in the nose-dominated region.

Thompson, R. A.↗

NASA NTRSDate not supplied

Quality Control Methods of Tower Data at Kennedy Space Center’s Launch Complex 39-B and the USAF Cape Canaveral 500 Foot Tower

The National Aeronautics and Space Administration (NASA) has long used meteorological data from weather towers located at Kennedy Space Center (KSC) and the United States Air Force’s Eastern Range(ER) in support of their various launch vehicles and climate studies. Some of the most valuable data is gathered at the Launch Complex 39-B (LC39-B) and the 500 foot tower located approximately two miles west of LC39-B and three miles north of the Vehicle Assembly Building (VAB). The data from LC39-B gives NASA Space Launch System (SLS) engineers valuable insight into the weather the vehicle can expect at the pad, while the 500 foot tower has a longer period of record and has been used by the Shuttle and SLS programs. However, numerous data quality (DQ) control issues have arisen when utilizing this data for analysis. In addition, instrumentation tends to deteriorate faster than normal due to the corrosive nature of the high salt content in the air. NASA’s Natural Environments branch has developed several QC databases of these towers, but these studies were for fixed periods of records. EV44 identified a need for a continually updated and QC’ed database of tower data not only to provide along term QC’ed database for vehicle and climate analyses, but also to provide the capability to investigate recent weather events such as downbursts and other high wind events. This study follows the methods developed in prior Natural Environment QC tower databases, which includes variable specific QC thresholds and checks used to generate QC flags. However, this study developed new techniques such as the development and design of the graphical user interface (GUI) for manual verification, and the creation of the final monthly QC files.

Quality Control↗

DOE OSTI2020

Efficient proactive vehicle relocation for on-demand mobility service with recurrent neural networks

One major challenge for on-demand mobility service (OMS) providers is to seamlessly match empty vehicles with trip requests so that the total vacant mileage is minimized. In this work, we develop an innovative data-driven approach for devising efficient vehicle relocation policy for OMS that (1) proactively relocates vehicles before the demand is observed and (2) reduces the inequality among drivers' income so that the proactive relocation policy is fair and is likely to be followed by drivers. Our approach represents the fusion of optimization and machine learning methods, which comprises three steps: First, we formulate the optimal proactive relocation as an optimal/stable matching problems and solve for global optimal solutions based on historical data. Second, the optimal solutions are then grouped and fed to train the deep learning models which consist of fully connected layers and long short-term memory networks. Low rank approximation is introduced to reduce the model complexity and improve the training performances. Finally, we use the trained model to predict the relocation policy which can be implemented in real time. We conduct comprehensive numerical experiments and sensitivity analyses to demonstrate the performances of the proposed method using New York City taxi data. Here, the results suggest that our method will reduce empty mileage per trip by 54-70% under optimal matching strategy, and a 25-32% reduction can also be achieved by following stable matching strategy. We also validate that the predicted relocation policies are robust in the presence of uncertain passenger demand level and passenger trip-requesting behavior.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1987

Mass storage systems for data transport in the early space station era 1992-1998

NASA's Space Station Program will provide a vehicle to deploy an unprecedented number of data producing experiments and operational devices. Peak down link data rates are expected to be in the 500 megabit per second range and the daily data volume could reach 2.4 terabytes. Such startling requirements inspired an internal NASA study to determine if economically viable data storage solutions are likely to be available to support the Ground Data Transport segment of the NASA data system. To derive the requirements for data storage subsystems, several alternative data transport architectures were identified with different degrees of decentralization. Data storage operations at each subsystem were categorized based on access time and retrieval functions, and reduced to the following types of subsystems: First in First out (FIFO) storage, fast random access storage, and slow access with staging. The study showed that industry funded magnetic and optical storage technology has a reasonable probability of meeting these requirements. There are, however, system level issues that need to be addressed in the near term.

Carper, Richard↗

NASA NTRS1998

Flight Acoustics Measurement Techniques and Applications

Careful consideration must be given to data acquisition and analysis techniques in the design of experiments for the measurement of noise generated by flight vehicles. Although noise measurement locations and data reduction procedures are specified for aircraft certification by FAA and ICAO directives, for example, there are virtually no established procedures for aircraft noise measurement for other purposes. To optimize the quality and quantity of information obtained in a flight acoustics experiment, microphone layout, data acquisition, and analysis must be tailored to the specific test objective. This paper will review flight acoustics technology at NASA Langley Research Center developed over the past decade. In particular, the paper will focus on flight experiments performed for three diverse objectives: (1) research applications, such as noise prediction code validation, (2) noise impact modeling, and (3) noise abatement flight procedures. To best achieve these diverse objectives, different deployments of microphone systems on the ground are required, and different data analysis techniques are needed. In all cases, accurate positioning of the aircraft synchronized in time with the data recording is necessary. However, there are some restrictions on flight operations unique to each case for the methods to properly work.

Preisser, J. S.↗

NASA NTRS2024

Presound: UAV Diagnostic System Enabled by Vibration-Based Machine Learning

A low-weight, inexpensive small unmanned aerial system (sUAS) that takes off, performs a mission, lands, and safely stows and recharges itself has myriad future applications ranging from agricultural imaging to last-mile package delivery. Likewise, Urban Air Mobility (UAM) systems will enable people to take air taxis from point to point in cities, rapidly moving commuters long distances without concern for road traffic and congestion. Fully electric aviation systems will be cleaner and quieter than ground transport. Cities could eliminate cars and buses, and convert roads to higher capacity bike and pedestrian throughways. Yet, for sUAS as well as UAM, system reliability and assurance is a limiting factor to deploying affordable autonomous flight systems. For this bright future of aviation to be realized, aircraft must be able to autonomously and accurately self-diagnose health issues both before takeoff and during flight. The GreenSight PreSound system is designed to identify defects on aircraft through intelligent analysis of vibration. It accomplishes this by measuring structural vibrations induced by the vehicle’s own propellers, and analyzing that data using a machine learning model that determines whether a defect is present. The PreSound system is designed to require no human oversight, and to operate across a wide array of vehicles through re-training of the model for each target aircraft. PreSound has been developed and seen limited early success using data collected from the GreenSight Dreamer sUAS, a 5lb quadrotor vehicle designed for aerial imaging applications. The final detection model, trained on data with props spinning at 50% throttle, achieves excellent performance with over 99% average accuracy in detecting blade damage using a single FFT vector input. It demonstrates the ability to generalize to new types of blade damage, correctly classifying a different type of blade damage with 98% accuracy. Full test pulses were classified with 100% accuracy, and in live testing, all sets of data during blade movement were classified accurately with over 95% confidence. When trained on in-flight data, the same model achieves an average accuracy of 85% in distinguishing between undamaged and blade-damaged states in flight. The authors believe that these accuracies show significant potential of this approach to expand unmanned flight safety, with significant potential benefits in accelerating Advanced Aerial Mobility (AAM) and UAM aviation applications.

UAS↗

NASA NTRS1980

Determination of the hypersonic-continuum/rarefied-flow drag coefficient of the Viking lander capsule 1 aeroshell from flight data

Results of an investigation to determine the full scale drag coefficient in the high speed, low density regime of the Viking lander capsule 1 entry vehicle are presented. The principal flight data used in the study were from onboard pressure, mass spectrometer, and accelerometer instrumentation. The hypersonic continuum flow drag coefficient was unambiguously obtained from pressure and accelerometer data; the free molecule flow drag coefficient was indirectly estimated from accelerometer and mass spectrometer data; the slip flow drag coefficient variation was obtained from an appropriate scaling of existing experimental sphere data. Comparison of the flight derived drag hypersonic continuum flow regime except for Reynolds numbers from 1000 to 100,000, for which an unaccountable difference between flight and ground test data of about 8% existed. The flight derived drag coefficients in the free molecule flow regime were considerably larger than those previously calculated with classical theory. The general character of the previously determined temperature profile was not changed appreciably by the results of this investigation; however, a slightly more symmetrical temperature variation at the highest altitudes was obtained.

Blanchard, R. C.↗

NASA NTRS2011

Ares I-X Flight Data Evaluation: Executive Overview

NASA's Constellation Program (CxP) successfully launched the Ares I-X flight test vehicle on October 28, 2009. The Ares I-X flight was a developmental flight test to demonstrate that this very large, long, and slender vehicle could be controlled successfully. The flight offered a unique opportunity for early engineering data to influence the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office (APO) established a set of 33 flight evaluation tasks to correlate flight results with prospective design assumptions and models. The flight evaluation tasks used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. Included within these tasks were direct comparisons of flight data with preflight predictions and post-flight assessments utilizing models and processes being applied to design and develop Ares I. The benefits of early development flight testing were made evident by results from these flight evaluation tasks. This overview provides summary information from assessment of the Ares I-X flight test data and represents a small subset of the detailed technical results. The Ares Projects Office published a 1,600-plus-page detailed technical report that documents the full set of results. This detailed report is subject to the International Traffic in Arms Regulations (ITAR) and is available in the Ares Projects Office archives files.

Huebner, Lawrence D.↗