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NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗

NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Data Assessment↗

NASA NTRS2023

Risk Trade-Space Analysis for Safe Human Expeditions to Mars

We assessed the integrated safety, health, and performance risk to crews on long-duration missions, specifically to Mars. Using a systems approach rather than one focused on individual countermeasures, we examined the trade space around several such risks to identify high-potential risk mitigation strategies and characterize aspects of Mars mission architectures that could lower aggregated risk. Current Mars Design Reference missions would require durations well over two years and would increase crew exposure to radiation and microgravity well beyond ISS levels, likely resulting in significantly reduced performance beyond our current capability to mitigate that could jeopardize mission success. A “fast Mars transit” round-trip mission concept was studied using an innovative flight dynamics approach to quantify the minimum total mission energy required for a Mars transit with total mission duration less than 400 days. This approach holds promise for sending humans to Mars and returning them safely with acceptable, potentially mitigatable, exposure to microgravity and radiation using current or near-term technologies. The fast transit concept would also result in fewer time-driven vehicle failures and enable sustainable deployment of humans and infrastructure to Mars on a regular cadence, allowing steady exploration and colonization of Mars. Finally, we conclude that reliance on the Low Earth Orbit (LEO) mission operations paradigm – i.e., one of near-complete real-time dependence on experts at Mission Control to manage the combined state of the mission, vehicle, and crew – is high risk given the communication delays and limited resupply of any Mars mission, and this risk is not eliminated by the shorter missions durations of fast transit scenarios. Based on historical trends, it is highly likely that the crew will face a high-consequence problem of uncertain origin during Mars transit when ground support will be greatly reduced. While it may be possible to reduce anomaly rates through improved reliability analysis and testing, and to reduce anomaly impacts through added robustness, such mitigations address only known failure modes and known uncertainties. Therefore, a radical shift in the Human-Systems Integration Architecture (HSIA) that defines the operational paradigm, systems design, and human-systems interactions is required to improve the risk posture to an acceptable level regardless of mission duration.

Mars↗

NASA NTRSDate not supplied

Assessing Hot Fire Data with WinPlot

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health and performance pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

J. Davis Hunter↗

NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗

NASA NTRS2010

Physics-Based Methods of Failure Analysis and Diagnostics in Human Space Flight

The Integrated Health Management (IHM) for the future aerospace systems requires to interface models of multiple subsystems in an efficient and accurate information environment at the earlier stages of system design. The complexity of modern aeronautic and aircraft systems (including e.g. the power distribution, flight control, solid and liquid motors) dictates employment of hybrid models and high-level reasoners for analysing mixed continuous and discrete information flow involving multiple modes of operation in uncertain environments, unknown state variables, heterogeneous software and hardware components. To provide the information link between key design/performance parameters and high-level reasoners we rely on development of multi-physics performance models, distributed sensors networks, and fault diagnostic and prognostic (FD&P) technologies in close collaboration with system designers. The main challenges of our research are related to the in-flight assessment of the structural stability, engine performance, and trajectory control. The main goal is to develop an intelligent IHM that not only enhances components and system reliability, but also provides a post-flight feedback helping to optimize design of the next generation of aerospace systems. Our efforts are concentrated on several directions of the research. One of the key components of our strategy is an innovative approach to the diagnostics/prognostics based on the real time dynamical inference (DI) technologies extended to encompass hybrid systems with hidden state trajectories. The major investments are into the multiphysics performance modelling that provides an access of the FD&P technologies to the main performance parameters of e.g. solid and liquid rocket motors and composite materials of the nozzle and case. Some of the recent results of our research are discussed in this chapter. We begin by introducing the problem of dynamical inference of stochastic nonlinear models and reviewing earlier results. Next, we present our analytical approach to the solution of this problem based on the path integral formulation. The resulting algorithm does not require an extensive global search for the model parameters, provides optimal compensation for the effects of dynamical noise, and is robust for a broad range of dynamical models. In the following Section the strengths of the algorithm are illustrated illustrated by inferring the parameters of the stochastic Lorenz system and comparing the results with those of earlier research. Next, we discuss a number of recent results in application to the development of the IHM for aerospace system. Firstly, we apply dynamical inference approach to a solution of classical three tank problems with mixed unknown continuous and binary parameters. The problem is considered in the context of ground support system for filling fuel tanks of liquid rocket motors. It is shown that the DI algorithm is well suited for successful solution of a hybrid version of this benchmark problem even in the presence of additional periodic and stochastic perturbation of unknown strength. Secondly, we illustrate our approach by its application to an analysis of the nozzle fault in a solid rocket motor (SRM). The internal ballistics of the SRM is modelled as a set of one-dimensional partial differential equations coupled to the dynamics of the propellant regression. In this example we are specifically focussed on the inference of discrete and continuous parameters of the nozzle blocking fault and on the possibility of an application of the DI algorithm to reducing the probability of "misses" of an on-board FD&P for SRM. In the next section re-contact problem caused by first stage/upper stage separation failure is discussed. The reaction forces imposed on the nozzle of the upper stage during the re-contact and their connection to the nozzle damage and to the thrust vector control (TVC) signal are obtained. It is shown that transient impact induced torquean be modelled as a response of an effective damped oscillator. A possible application of the DI algorithm to the inference of damage parameters and predicting fault dynamics ahead of time using the actuator signal is discussed. Finally, we formulate Bayesian inferential framework for development of the IHM system for in-flight structural health monitoring (SHM) of composite materials. We consider the signal generated by piezoelectric actuator mounted on composite structure generating elastic waves in it. The signal received by the sensor is than compared with the baseline signal. The possibility of damage inference is discussed in the context of development of the SHM.

Smelyanskiy, Vadim N.↗

NASA NTRSDate not supplied

Zero-Trust Architecture for Autonomous Edge Computing

We are at the apex of an aviation revolution where autonomy will play a central role in enabling complex, multi-agent systems to communicate, interact, and collaborate on a myriad of applications spanning autonomous swarms to wild-fire management. Autonomy is not an absolute but rather a spectrum ranging from a system requiring significant human intervention to one requiring little to none [1]. For example, the extreme, in the case of an autonomous aircraft, is one that operates independently in the airspace interacting with all other elements (air traffic controllers, other pilots) as if it were a human pilot. Critical to this vision is an architecture that enables autonomous agents to interact with minimal latency. Edge computing is an emerging architecture where compute and storage is pushed to the ‘edge’ of the network in order to minimize the round-trip time from agent to resource thereby mitigating the latency associated with cloud-only based approaches. Additionally, services can generate massive amounts of data (e.g., video feeds), which may require analysis in near real-time. Moving this data to the cloud for further processing may not be feasible due to latency, bandwidth, and cost. Privacy, security, and reliability can also be improved by edge computing architectures. However, this geo-distributed and dynamic* architecture complicates the establishment of unambiguous network security boundaries and can lead to vulnerabilities including man in the middle attacks, replay attacks, physical security breaches of edge nodes, signal interception, etc. This motivates the need for zero-trust architectures [2–4] which de-emphasize the notion of static network perimeters and, as the name implies, do not instill any innate trust in any particular agent. It is required that all agents must be authorized and approved in every transaction. In this paper, we present a zero-trust architecture suitable for edge-computing applications that demand significant low-latency, security, privacy, and reliability.

zero trust↗

NASA NTRS1999

On-Line Analysis of Physiologic and Neurobehavioral Variables During Long-Duration Space Missions

The goal of this project is to develop reliable statistical algorithms for on-line analysis of physiologic and neurobehavioral variables monitored during long-duration space missions. Maintenance of physiologic and neurobehavioral homeostasis during long-duration space missions is crucial for ensuring optimal crew performance. If countermeasures are not applied, alterations in homeostasis will occur in nearly all-physiologic systems. During such missions data from most of these systems will be either continually and/or continuously monitored. Therefore, if these data can be analyzed as they are acquired and the status of these systems can be continually assessed, then once alterations are detected, appropriate countermeasures can be applied to correct them. One of the most important physiologic systems in which to maintain homeostasis during long-duration missions is the circadian system. To detect and treat alterations in circadian physiology during long duration space missions requires development of: 1) a ground-based protocol to assess the status of the circadian system under the light-dark environment in which crews in space will typically work; and 2) appropriate statistical methods to make this assessment. The protocol in Project 1, Circadian Entrainment, Sleep-Wake Regulation and Neurobehavioral will study human volunteers under the simulated light-dark environment of long-duration space missions. Therefore, we propose to develop statistical models to characterize in near real time circadian and neurobehavioral physiology under these conditions. The specific aims of this project are to test the hypotheses that: 1) Dynamic statistical methods based on the Kronauer model of the human circadian system can be developed to estimate circadian phase, period, amplitude from core-temperature data collected under simulated light- dark conditions of long-duration space missions. 2) Analytic formulae and numerical algorithms can be developed to compute the error in the estimates of circadian phase, period and amplitude determined from the data in Specific Aim 1. 3) Statistical models can detect reliably in near real- time (daily) significant alternations in the circadian physiology of individual subjects by analyzing the circadian and neurobehavioral data collected in Project 1. 4) Criteria can be developed using the Kronauer model and the recently developed Jewett model of cognitive -performance and subjective alertness to define altered circadian and neurobehavioral physiology and to set conditions for immediate administration of countermeasures.

Brown, Emery N.↗

NASA NTRS2013

Near-Earth Phase Risk Comparison of Human Mars Campaign Architectures

A risk analysis of the launch, orbital assembly, and Earth-departure phases of human Mars exploration campaign architectures was completed as an extension of a probabilistic risk assessment (PRA) originally carried out under the NASA Constellation Program Ares V Project. The objective of the updated analysis was to study the sensitivity of loss-of-campaign risk to such architectural factors as composition of the propellant delivery portion of the launch vehicle fleet (Ares V heavy-lift launch vehicle vs. smaller/cheaper commercial launchers) and the degree of launcher or Mars-bound spacecraft element sparing. Both a static PRA analysis and a dynamic, event-based Monte Carlo simulation were developed and used to evaluate the probability of loss of campaign under different sparing options. Results showed that with no sparing, loss-of-campaign risk is strongly driven by launcher count and on-orbit loiter duration, favoring an all-Ares V launch approach. Further, the reliability of the all-Ares V architecture showed significant improvement with the addition of a single spare launcher/payload. Among architectures utilizing a mix of Ares V and commercial launchers, those that minimized the on-orbit loiter duration of Mars-bound elements were found to exceed the reliability of no spare all-Ares V campaign if unlimited commercial vehicle sparing was assumed

Manning, Ted A.↗

NASA NTRS2008

Engineering America's Current and Future Space Transportation Systems: 50 Years of Systems Engineering Innovation for Sustainable Exploration

Over the past 50 years, the National Aeronautics and Space Administration (NASA) has delivered space transportation solutions for America's complex missions, ranging from scientific payloads that expand knowledge, such as the Hubble Space Telescope, to astronauts and lunar rovers destined for voyages to the Moon. Currently, the venerable Space Shuttle, which has been in service since 1981, provides the United States' (U.S.) capability for both crew and heavy cargo to low-Earth orbit to' construct the International Space Station, before the Shuttle is retired in 2010. In the next decade, NASA will replace this system with a duo of launch vehicles: the Ares I Crew Launch Vehicle and the Ares V Cargo Launch Vehicle (Figure 1). The goals for this new system include increased safety and reliability coupled with lower operations costs that promote sustainable space exploration for decades to come. The Ares I will loft the Orion Crew Exploration Vehicle, while the heavy-lift Ares V will carry the Altair Lunar Lander and the equipment and supplies needed to construct a lunar outpost for a new generation of human and robotic space pioneers. This paper will provide details of the in-house systems engineering and vehicle integration work now being performed for the Ares I and planned for the Ares V. It will give an overview of the Ares I system-level test activities, such as the ground vibration testing that will be conducted in the Marshall Center's Dynamic Test Stand to verify the integrated vehicle stack's structural integrity and to validate computer modeling and simulation (Figure 2), as well as the main propulsion test article analysis to be conducted in the Static Test Stand. These activities also will help prove and refine mission concepts of operation, while supporting the spectrum of design and development work being performed by Marshall's Engineering Directorate, ranging from launch vehicles and lunar rovers to scientific spacecraft and associated experiments. Ultimately, fielding a robust space transportation solution that will carry international explorers and essential payloads will pave the way for a new century of scientific discovery beyond planet Earth.

Dmbacher, Daniel L.↗

NASA NTRS1999

Measuring the Chemical Potential of the Martian Regolith to Generate and Sustain Life

A critical component for identifying chemical biosignatures is the ability to assess in-situ the potential of an aqueous geochemical environment to generate and sustain life. On Mars or other solar bodies, in-situ chemical characterization could provide evidence as to whether the chemical composition of the regolith or evaporites in suspected ancient water bodies have been biologically influenced or possess the chemical parameters within which life may have existed, or may still exist. A variety of analytical techniques have been proposed for use in detecting and identify signatures of past or present life. These techniques fall into two groups; visual observation with instruments such as cameras or optical/atomic-force microscopes; or elemental chemical analysis with such instruments as X-ray fluorescence (XRF) and diffraction (XRD), a-proton backscatter (APX), y-ray, Mossbauer, Raman, IR, UV/VIS spectroscopies, gas chromatography (GC), or mass spectrometry (MS). Direct observation of an identifiable lifeform by the first set of instruments in a single sample is highly unlikely, especially for extinct organisms or on the surface. The later instruments can provide vital data as to the elemental mineralogy and geological history of the planet, but are highly inadequate for understanding the chemistry of the planet in terms of indigenous life or interactions with human explorers. Techniques such as XRD, XRF, and APX, provide elemental composition at high limits of detection. Some of this data can be extrapolated or interpolated to provide chemical parameters such as oxidation state or composition. Gas chromatography (GC) without standards and non-specific detectors, has little chance of identifying a mixture of unknown components. Combined with GC or by itself, mass spectrometry (MS) can provide identification of compounds, but in both cases the sample must be appropriately prepared for accurate and reliable analysis. Life as we know it, and probably identify it as such, requires an aqueous environment. Deciphering die chemical speciation of this aqueous environment is the key to recognizing therein the biosignatures of any extinct or present life forms. Identifying the soluble (ionic and nonionic) components by reacting a currently dormant environment can provide a "picture" of the thermodynamics and chemical components of a possibly bioactive environment. The only devices which can provide such information are electrochemical sensors based on the potentiometric ion selective electrodes (ISEs) and on dynamic techniques such as cyclic voltammetry (CV) and stripping voltammetry (SV). Such an array of devices can provide not only the chemical composition of a water-soluble Martian soil sample, but also several other vital chemical parameters such as pH, conductivity, redox potential, and dissolved gases. To address these issues we have been investigating the possible use of an electrochemically-based ion sensor array as a new integrated approach to quantitative analytical and chemometric electrochemical measurements. The sensor array will consist of specific and semispecific ion selective and amperometric transducers, which can simultaneously and continuously identify and semiquantitatively determine over 50 organic and inorganic analytes in water-based environments. Several individual sensors, based on the same principle, have been flight-tested and have been installed as part of the MECA instrumentation on the Mars 2001 Lander for in-situ analyses. However, the microfabrication, integration and multiplexing of such a large number of these sensors on a single substrate have not been previously attempted.

Kounaves, S. P.↗

NASA NTRS1989

Control of the errors of discretization and idealization in finite element analysis

Understanding of the basic principles which control errors of discretization in finite element analysis has increased very substantially since 1980. The main milestones were: (1) development of the theoretical basis of p-extensions (1981); (2) understanding of the proper interplay between mesh design and assignment of polynomial degree to elements. Practical realization of exponential convergence rates, independently of the smoothness of the exact solution (1984); and (3) industrial experience with the new finite element technology known as the p- or hp-version of the finite element method: General Dynamics reported thirty- to forty-fold savings in terms of human time and large savings in computer time (1986). Lockheed reported favorably on their evaluation of error estimation and quality control capabilities of the p-version in industrial settings (1987). The gains in our understanding of how to control the errors of discretization represent only half of the control necessary to ensure that a numerical model is in fact an accurate representation of the corresponding physical system. Control of the errors of idealization is equally important. A brief overview of the main ideas of how to ensure the quality and reliability of mathematical models of structural systems is presented.

Szabo, Barna A.↗

NASA NTRSDate not supplied

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA’s near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center’s (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC’s Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA’s CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

Hong Q. Yang↗

NASA NTRSDate not supplied

Validation of Cryogenic Propellant Tank Self-Pressurization

NASA's near-future long-term space missions necessitate advancements in cryogenic fluid management (CFM), which includes safe and reliable long-term propellant storage. Consequently, NASA STMD (Space Technology Mission Directorate) has established the CFM Portfolio Project to improve CFM technologies for upcoming missions. As a part of CFM Modeling Portfolio, NASA Marshall Space Flight Center's (MSFC) Fluid Dynamics branch within the Propulsion Systems Department is tasked with assessing and improving computational tools used to support flight projects such as Human Lander System and Commercial Lunar Payload Services. One of the challenging modeling problems is that of self-pressurization of propellant tank due to heat leakage over long time periods. Reduced order and nodal tools find it extremely difficult to accurately predict self-pressurization under transient conditions or where complex flow patterns or thermal gradients exist, and application of 3-D CFD (computational fluid dynamics) simulations is necessary to characterize these problems. Until recently, CFD simulations for these long-term processes (order of hours or days) have been too impractical to conduct due to prohibitive wall time and computational resource requirements. The requisite CFD tool need to be efficient, computationally scalable, modular with ability to incorporate various physics models, and robust enough to not accumulate conservation errors over several hours of simulated time. NASA MSFC's Loci-Stream CFD tool along with the VOF module is a great candidate to fit this mold. In this paper, we validate Loci-Stream for predicting self-pressurization of a flight scale propellant tank so it can serve as a reliable design and analysis tool for NASA's CFM application needs. Liquid hydrogen tank pressurization tests carried out at the K-site testing facility provide a reliable data set for this purpose. These tests were simulated using Loci-Stream solver with VOF module as well as a hybrid approach which uses a lumped model for the ullage gas domain and CFD simulation of the liquid propellant. Both are shown to have very good predictive capabilities over multiple K-site experiments.

cryogenic fluid management↗

NASA NTRS2000

Section on Observed Impacts on El Nino

Agricultural applications of El Nino forecasts are already underway in some countries and need to be evaluated or re-evaluated. For example, in Peru, El Nino forecasts have been incorporated into national planning for the agricultural sector, and areas planted with rice and cotton (cotton being the more drought-tolerant crop) are adjusted accordingly. How well are this and other such programs working? Such evaluations will contribute to the governmental and intergovernmental institutions, including the Inter-American Institute for Global Change Research and the US National Ocean and Atmospheric Agency that are fostering programs to aid the effective use of forecasts. As El Nino climate forecasting grows out of the research mode into operational mode, the research focus shifts to include the design of appropriate modes of utilization. Awareness of and sensitivity to the costs of prediction errors also grow. For example, one major forecasting model failed to predict the very large El Nino event of 1997, when Pacific sea-surface temperatures were the highest on record. Although simple correlations between El Nino events and crop yields may be suggestive, more sophisticated work is needed to understand the subtleties of the interplay among the global climate system, regional climate patterns, and local agricultural systems. Honesty about the limitations of an forecast is essential, especially when human livelihoods are at stake. An end-to-end analysis links tools and expertise from the full sequence of ENSO cause-and-effect processes. Representatives from many disciplines are needed to achieve insights, e.g, oceanographers and atmospheric scientists who predict El Nino events, climatologists who drive global climate models with sea-surface temperature predictions, agronomists who translate regional climate connections in to crop yield forecasts, and economists who analyze market adjustments to the vagaries of climate and determine the value of climate forecasts. Methods include historical studies to understand past patterns and to test hindcasts of the prediction tools, crop modeling, spatial analysis and remote sensing. This research involves expanding, deepening, and applying the understanding of physical climate to the fields of agronomy and social science; and the reciprocal understanding of crop growth and farm economics to climatology. Delivery of a regional climate forecast with no information about how the climate forecast was derived limits its effectiveness. Explanation of a region's major climate driving forces helps to place a seasonal forecast in context. Then, a useful approach is to show historical responses to previous El Nino events, and projections, with uncertainty intervals, of crop response from dynamic process crop growth models. Regional ID forecasts should be updated with real-time weather conditions. Since every El Nino event is different, it is important to track, report and advise on each new event as it unfolds. The stability of human enterprises depends on understanding both the potentialities and the limits of predictability. Farmers rely on past experience to anticipate and respond to fluctuations in the biophysical systems on which their livelihoods depend. Now scientists are improving their ability to predict some major elements of climate variability. The improvements in the reliability of El Nino forecasts are encouraging, but seasonal forecasts for agriculture are not, and will probably never be completely infallible, due to the chaotic nature of the climate system. Uncertainties proliferate as we extend beyond Pacific sea-surface temperatures to climate teleconnections and agricultural outcomes. The goal of this research is to shed as a clear light as possible on these inherent uncertainties and thus to contribute to the development of appropriate responses to El Nino and other seasonal forecasts for a range of stakeholders, which, ultimately, includes food consumers everywhere.

Rosenzweig, Cynthia↗

NASA NTRS2025

Influence of Actuator Movement Rate During Acquisition of Inlet Characterization Data

This report considers using a process to acquire performance data for supersonic mixed-compression inlets that is faster and less costly than the previous process. In the previous process for acquiring data during wind tunnel experiments, actuators for backpressuring an inlet moved in discrete increments, paused for dynamics to dampen, measured data for 5 s, recorded the data, and then reduced the data to graphic plots of pressure recovery versus mass capture ratio. This discrete data acquisition procedure was methodical, reliable, and accurate. However, acquiring data to characterize the inlet consumed significant wind-on time. Wind tunnel operation was costly when considering maintenance, energy, and human resources (operators and research team); therefore, the price for each data point was high. This report presents a quicker method to obtain all measurements, one which can also be used in blowdown wind tunnels. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. The backpressuring actuator moves continuously, and measurements from high-speed pressure sensors are recorded as the actuator progresses to and past the incremental points. Despite its advantages, the approach raised the following questions: (1) Will the new process be as accurate as the previous process? and (2) Are there any hidden costs? These concerns are addressed in this report. This report reviews a study that was undertaken to compare wind tunnel experiment data taken using the previous discrete data acquisition procedure with data recorded using the dynamic inlet characterization data acquisition procedure. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data for analysis are explained, and a discussion of the results is given. Finally, conclusions from this study that may guide further work in this area are presented.

Inlet Characterization Curves↗

NASA NTRS2019

Technology Development and Infusion by NASA's Entry Systems Modeling Project

This paper describes recent development of modeling and simulation technologies for entry systems and their infusion into NASA's exploration missions. Technology development is organized and prioritized using a system-level perspective, resulting in four broad technical areas of investment: (1) Thermal protection material modeling, (2) Shock layer kinetics and radiation, (3) Computational and experimental aerosciences, and (4) Guidance, navigation, and control. The paper will highlight key contributions from each of these areas, their impacts from a spacecraft and mission design perspective, and discuss planned future investment. Aspects of each technical area are only briefly summarized here. Thermal protection material modeling is geared toward high-fidelity, predictive models capable of optimizing design performance, post-flight reconstruction, and quantifying thermal protection system reliability. New computational tools and experimental techniques have been applied to Orion, MSL/Mars 2020, Mars InSight, and Mars Sample Return missions. Research and development in the area of shock layer kinetics has focused on air and CO2-based atmospheres. In both cases, substantial improvements in model uncertainty have directly impacted the development of mission margin policies, flight instrumentation design and analysis (Orion and Mars 2020), and have even revealed the importance of neglected phenomena like mid-wave infrared radiation of CO2. Aerosciences is a very broad area of interest in entry systems, yet a number of important challenges are being addressed: Coupled fluid-structure simulations of parachute inflation and dynamics affecting Orion, Commercial Crew, and Mars programs; Experimental and computational studies of vehicle dynamics; Multi-phase flow with dust particles to simulate augmentation of aerothermal environments at Mars during dust storms; and studies of roughness-induced heating augmentation relevant to tiled (Orion, Mars 2020) and woven (Mars Sample Return) thermal protection systems. Guidance and control in the context of entry systems has focused on development of methods for multi-axis control (i.e. pitch and yaw, rather than bank angle alone) of spacecraft during entry and descent, with precision landing requirements driven by Mars human exploration goals.

Barnhardt, Michael D.↗

NASA NTRSDate not supplied

An Efficient Approach to Collect Inlet Characterization Data

This report considers a novel process to acquire performance data for supersonic mixed compression inlets that is faster, and therefore less costly, than the previous one. In the previous process, measurements were recorded in discrete increments. The backpressuring actuator was advanced, there was a pause to allow for airflow fluctuations to diminish, and then the measurements were recorded. While this process was methodical, reliable and accurate, it consumed significant wind-on time. In general, high-speed wind tunnels are expensive to operate considering maintenance, energy and human resource requirements. Furthermore, many facilities, such as blowdown wind tunnels, are limited in the duration that they can maintain the desired test condition. Consequently, a quick method to collect the measurements is desired. A favored approach has the actuator moving in a continuous fashion with measurements recorded as the actuator continuously progresses through the increment points. This approach, identified as the dynamic inlet characteristic data acquisition procedure, uses in situ dynamic high-speed pressure sensors to measure pressure signals. While faster, continuous movement adds dynamic effects to the data. To better understand these dynamic effects and other potential influences, a study was undertaken to compare wind tunnel measurements taken at discrete actuator position points with data gathered during continuous actuator movement. Specially, plots of inlet pressure recovery versus mass capture ratio, or total pressure characteristic curves, were examined. The data were measured during experiments in the NASA Glenn Research Center Abe Silverstein 10- by 10-Foot Supersonic Wind Tunnel (SWT) with an inlet propulsion test article. In this report, the wind tunnel experiment and the study objectives are described. The processes to reduce the data and for analysis are explained. A discussion of the results along with features noted in the data is given. Finally, conclusions from this study that may be used to guide future wind tunnel experiment planning are presented.

Inlet↗