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NASA NTRS2020

A Modeling Approach for Handling Qualities and Controls Safety Analysis of Electric Air Taxi Vehicles

The combination of modern advances in electric propulsion, fly-by-wire controls, autonomy, and increasing demand for short range air taxi operations, is currently producing an outburst of vehicle designs more diverse than ever before. Advanced software tools are needed to support the rapid and safe introduction of any design into the airspace, including the safety of the deployed flight control system and vehicle handling qualities. This paper presents a methodology for building air taxi vehicle models with distributed electric propulsion for use in analyzing flight control system safety at the conceptual design level.The approach builds on existing software tools capable of outputting aeromechanics-based linear perturbation models for Vertical Take-off and Landing vehicles with multiple rotors. Rotor torque inputs are then converted into equivalent voltage control inputs, and the linear state and input dynamics matrices are modified to include electric motor dynamics with common parameters for direct-current electric motors. The linear perturbation dynamics are then stitched across multiple operating points into a quasi-Linear Parameter Varying model that covers the full flight envelope. A Model Predictive Controller is developed for use with the full envelope model, and a tradeoff analysis between handling quality and motor requirements is demonstrated using a six passenger NASA air taxi reference design.

Urban Air Mobility↗

NASA NTRSDate not supplied

Investigating Solar Radiation Pressure Modeling for Operations in Near Rectilinear Halo Orbit

NASA’s Gateway program will build a crew-tended station in an Earth-Moon Near Rectilinear Halo Orbit (NRHO). Deep space operations differ considerably from Low Earth Orbit (LEO) operations in the environmental modeling, orbit geometry, and propagation timespans in operations. The cislunar environment, as opposed to the LEO environment, lacks atmospheric drag and is simultaneously affected by the gravity of both the Earth and the Moon, and solar radiation pressure (SRP) has a significant effect. This paper investigates the impacts of various SRP models on prediction accuracy, attitude control accuracy, orbit determination performance, and computational burden.

Guidance↗

NASA NTRSDate not supplied

Flight Performance and Stability of Space Launch System Core Stage Thrust Vector Control

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of eight mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. The Core Stage TVC shares vehicle control authority with the SLS 5-segment Solid Rocket Boosters (SRBs) during boost phase flight, and is the sole means of vehicle flight control during in exoatmospheric flight following SRB separation. TVC responses during Green Run Hot Fire (GRHF) testing revealed that the TVC did not meet its performance specifications. Step and frequency responses exhibited unexpected departures from prior laboratory data and modeled behavior. Post-test analysis determined that the characteristics of the structure and gimbal friction are significantly influenced by the thrust-loaded conditions, and the command avionics exhibited a small but important gain nonlinearity. Using the available test data, the design team augmented the flight control TVC models to bound the observed results and include the additional fidelity needed for vehicle flight control analysis so as to build sufficient rationale for flight certification. Prior to the Green Run tests, “simplex” linear models typically used for flight control analysis did not include gimbal friction and other nonlinearities owing to long-standing assumptions that these effects were negligible in the Shuttle Orbiter TVC system. Following the Green Run findings, simulation analysis of the flight dynamics in the time and frequency domain revealed the propensity for a flight control limit cycle oscillation (LCO) if friction and structural compliances fell near the edges of test-predicted bounds. While the “most probable” models did not predict an in-flight LCO, the SLS Program conservatively proceeded with a system-wide evaluation and ultimate acceptance of the possibility for a small amplitude, low-frequency TVC LCO in flight. A final validation of the extensive test and modeling effort occurred when the first flight of SLS successfully demonstrated the fully integrated performance of the vehicle’s TVC system This paper is the final installment in a seven-paper series surveying the design, engineering, test validation, and flight performance of the Core Stage Thrust Vector Control system. In this paper, the development of flight rationale in light of the TVC responses observed in Green Run is discussed, along with a review of the flight telemetry illustrating the correlation of the preflight predictions with the observed performance.

John H. Wall↗

NASA NTRS2020

Generation and Calibration of Linear Models of Aircraft with Highly Coupled Aeroelastic and Flight Dynamics

The lightweight structures and unconventional configurations being considered for the next generation of aircraft mean that any effort to predict or control the flight dynamics is impacted by the structural dynamics. One of the most severe forms of coupling between aeroelasticity and flight dynamics is an instability called body freedom flutter. The existing tools often assume a relatively weak effect of structural dynamics on the flight dynamics, and are therefore incapable of modeling strong interactions like body freedom flutter. A method of combining different sources of data traditionally used for aeroelasticity and flight dynamics is described by reconciling many of the differences between these models. By building upon past modeling efforts, a level of familiarity in the approach is achieved. Generally the differences from the traditional approaches are subtle but significant. The traditional frequency domain flutter model in a modal coordinate system is converted to a form consistent with a time domain flight dynamics model. The time domain rational function approximation about a non-inertial coordinate system and the unique constraints for the conversion between the inertial and non-inertial coordinate systems are discussed. A consistent transformation of the states of aeroelastic models to flight dynamics models is derived, which enables the integration of data from higher fidelity computational fluid dynamics models or wind-tunnel testing. The present method of integrating multidisciplinary data was used to create models that compare well with X-56A flight-test data, including conditions past the flutter speed.

Ouellette, Jeffrey↗

NASA NTRS2000

Analysis and Modeling of Ground Operations at Hub Airports

Building simple and accurate models of hub airports can considerably help one understand airport dynamics, and may provide quantitative estimates of operational airport improvements. In this paper, three models are proposed to capture the dynamics of busy hub airport operations. Two simple queuing models are introduced to capture the taxi-out and taxi-in processes. An integer programming model aimed at representing airline decision-making attempts to capture the dynamics of the aircraft turnaround process. These models can be applied for predictive purposes. They may also be used to evaluate control strategies for improving overall airport efficiency.

Atkins, Stephen↗

NASA NTRS2020

Model Validation for Bigelow Expandable Activity Module (BEAM) with Stowage

The Bigelow Expandable Activity Module (BEAM) was a collaboration between NASA and Bigelow Aerospace to develop an expandable habitat technology that could be used for future space exploration missions such as the Artemis program. On April 26, 2016, the BEAM was launched and berthed to the International Space Station (ISS) on the aft port of Node 3. After the originally planned two-year mission life, BEAM was approved for use as a stowage module for a 109-cargotransfer bag equivalent (CTBE) to alleviate stowage limitations onboard the ISS. The present work builds on the previous 2017 model validation to flight data that demonstrated that BEAM could generally accommodate cargo stowage without adversely affecting BEAM thermal control, primarily for condensation management. Once the stowage was configured in early 2019, model validation efforts resumed. The thermal model revisions included the CTBE stowage and updated CFD-derived heat transfer coefficients for various intra-module ventilation (IMV) flow rates. The coefficients were provided by the Crew and Thermal Systems Division (EC) at NASA JSC and Jacobs Technology. The model is now revalidated and able to predict minimum temperatures with good agreement to flight temperatures (within 1 °C) for both historic and recurring minimum values. Additionally, the model is partially validated for reduced flow rates. With this model, the team was able to provide new flight rule recommendations for condensation and IMV operations management.

Sydney Taylor↗

NASA NTRSDate not supplied

Numerical Study of Water Ice and Molecular Contamination Build Up during JWST Deployment

This paper summarizes a recent numerical analysis of water vapor and volatile condensible material deposition on the James Webb Space Telescope from the initial orbit insertion up to 180 days post launch. The analysis utilized 17 distinct geometry files capturing observatory configuration changes during the deployment. Surface temperature was set from a time-dependent thermal analysis solution. A vapor pressure model was used to calculate the net water ice adsorption. Molecular contamination included a contribution from UV photopolymerization. The analysis predicted levels of ice and molecular accumulation were found to be within the allowable limits specified by the observatory contamination control plan.

James Webb Space Telescope↗

NASA NTRSDate not supplied

Numerical Study of Water Ice and Molecular Contamination Build Up during JWST Deployment

James Webb Space Telescope↗

NASA NTRS1998

Structural Similitude and Scaling Laws

Aircraft and spacecraft comprise the class of aerospace structures that require efficiency and wisdom in design, sophistication and accuracy in analysis and numerous and careful experimental evaluations of components and prototype, in order to achieve the necessary system reliability, performance and safety. Preliminary and/or concept design entails the assemblage of system mission requirements, system expected performance and identification of components and their connections as well as of manufacturing and system assembly techniques. This is accomplished through experience based on previous similar designs, and through the possible use of models to simulate the entire system characteristics. Detail design is heavily dependent on information and concepts derived from the previous steps. This information identifies critical design areas which need sophisticated analyses, and design and redesign procedures to achieve the expected component performance. This step may require several independent analysis models, which, in many instances, require component testing. The last step in the design process, before going to production, is the verification of the design. This step necessitates the production of large components and prototypes in order to test component and system analytical predictions and verify strength and performance requirements under the worst loading conditions that the system is expected to encounter in service. Clearly then, full-scale testing is in many cases necessary and always very expensive. In the aircraft industry, in addition to full-scale tests, certification and safety necessitate large component static and dynamic testing. Such tests are extremely difficult, time consuming and definitely absolutely necessary. Clearly, one should not expect that prototype testing will be totally eliminated in the aircraft industry. It is hoped, though, that we can reduce full-scale testing to a minimum. Full-scale large component testing is necessary in other industries as well, Ship building, automobile and railway car construction all rely heavily on testing. Regardless of the application, a scaled-down (by a large factor) model (scale model) which closely represents the structural behavior of the full-scale system (prototype) can prove to be an extremely beneficial tool. This possible development must be based on the existence of certain structural parameters that control the behavior of a structural system when acted upon by static and/or dynamic loads. If such structural parameters exist, a scaled-down replica can be built, which will duplicate the response of the full-scale system. The two systems are then said to be structurally similar. The term, then, that best describes this similarity is structural similitude. Similarity of systems requires that the relevant system parameters be identical and these systems be governed by a unique set of characteristic equations. Thus, if a relation or equation of variables is written for a system, it is valid for all systems which are similar to it. Each variable in a model is proportional to the corresponding variable of the prototype. This ratio, which plays an essential role in predicting the relationship between the model and its prototype, is called the scale factor.

Simitses, George J.↗

NASA NTRS2011

Six-Tube Freezable Radiator Testing and Model Correlation

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recovering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TradeMark) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested, namely MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Lillibridge, Sean↗

NASA NTRS1979

Stable dielectric charge distributions from field enhancement of secondary mission

The emission of secondary electrons from dielectrics subject to numerous effects of electric field which are experimentally difficult to control is discussed. Measurements are reported using pulse techniques such that local fields do not build to significant levels, but measurements with fields present are also of interest. A specific series of measurements under controlled conditions are described and their implications in terms of fields, magnitude and angle, near the dielectric surface were examined. The measurements were made for a charged fluorinated-ethylene-propylene surface near a grounded aluminum half-round resting on the surface. The geometry produced a stable surface-charge gradient being controlled by a strongly enhanced secondary emission for which a model is constructed. Observations of surface flashovers under various conditions confirm the predictions of some scaling exercises.

Robinson, J. W.↗

NASA NTRS2012

Six-Tube Freezable Radiator Testing and Model Correlation

Freezable Radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft?s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recov ering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TM) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested: MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Lilibridge, Sean T.↗

NASA NTRS2001

A Boundary Condition for Simulation of Flow Over Porous Surfaces

A new boundary condition is presented.for simulating the flow over passively porous surfaces. The model builds on the prior work of R.H. Bush to eliminate the need for constructing grid within an underlying plenum, thereby simplifying the numerical modeling of passively porous flow control systems and reducing computation cost. Code experts.for two structured-grid.flow solvers, TLNS3D and CFL3D. and one unstructured solver, USM3Dns, collaborated with an experimental porosity expert to develop the model and implement it into their respective codes. Results presented,for the three codes on a slender forebody with circumferential porosity and a wing with leading-edge porosity demonstrate a good agreement with experimental data and a remarkable ability to predict the aggregate aerodynamic effects of surface porosity with a simple boundary condition.

Frink, Neal T.↗

NASA NTRS2001

Entropy generation method to quantify thermal comfort

The present paper presents a thermodynamic approach to assess the quality of human-thermal environment interaction and quantify thermal comfort. The approach involves development of entropy generation term by applying second law of thermodynamics to the combined human-environment system. The entropy generation term combines both human thermal physiological responses and thermal environmental variables to provide an objective measure of thermal comfort. The original concepts and definitions form the basis for establishing the mathematical relationship between thermal comfort and entropy generation term. As a result of logic and deterministic approach, an Objective Thermal Comfort Index (OTCI) is defined and established as a function of entropy generation. In order to verify the entropy-based thermal comfort model, human thermal physiological responses due to changes in ambient conditions are simulated using a well established and validated human thermal model developed at the Institute of Environmental Research of Kansas State University (KSU). The finite element based KSU human thermal computer model is being utilized as a "Computational Environmental Chamber" to conduct series of simulations to examine the human thermal responses to different environmental conditions. The output from the simulation, which include human thermal responses and input data consisting of environmental conditions are fed into the thermal comfort model. Continuous monitoring of thermal comfort in comfortable and extreme environmental conditions is demonstrated. The Objective Thermal Comfort values obtained from the entropy-based model are validated against regression based Predicted Mean Vote (PMV) values. Using the corresponding air temperatures and vapor pressures that were used in the computer simulation in the regression equation generates the PMV values. The preliminary results indicate that the OTCI and PMV values correlate well under ideal conditions. However, an experimental study is needed in the future to fully establish the validity of the OTCI formula and the model. One of the practical applications of this index is that could it be integrated in thermal control systems to develop human-centered environmental control systems for potential use in aircraft, mass transit vehicles, intelligent building systems, and space vehicles.

Models, Biological↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗

NASA NTRS1993

Building a generalized distributed system model

The key elements in the 1992-93 period of the project are the following: (1) extensive use of the simulator to implement and test - concurrency control algorithms, interactive user interface, and replica control algorithms; and (2) investigations into the applicability of data and process replication in real-time systems. In the 1993-94 period of the project, we intend to accomplish the following: (1) concentrate on efforts to investigate the effects of data and process replication on hard and soft real-time systems - especially we will concentrate on the impact of semantic-based consistency control schemes on a distributed real-time system in terms of improved reliability, improved availability, better resource utilization, and reduced missed task deadlines; and (2) use the prototype to verify the theoretically predicted performance of locking protocols, etc.

Mukkamala, R.↗

NASA NTRS1991

A research program in empirical computer science

During the grant reporting period our primary activities have been to begin preparation for the establishment of a research program in experimental computer science. The focus of research in this program will be safety-critical systems. Many questions that arise in the effort to improve software dependability can only be addressed empirically. For example, there is no way to predict the performance of the various proposed approaches to building fault-tolerant software. Performance models, though valuable, are parameterized and cannot be used to make quantitative predictions without experimental determination of underlying distributions. In the past, experimentation has been able to shed some light on the practical benefits and limitations of software fault tolerance. It is common, also, for experimentation to reveal new questions or new aspects of problems that were previously unknown. A good example is the Consistent Comparison Problem that was revealed by experimentation and subsequently studied in depth. The result was a clear understanding of a previously unknown problem with software fault tolerance. The purpose of a research program in empirical computer science is to perform controlled experiments in the area of real-time, embedded control systems. The goal of the various experiments will be to determine better approaches to the construction of the software for computing systems that have to be relied upon. As such it will validate research concepts from other sources, provide new research results, and facilitate the transition of research results from concepts to practical procedures that can be applied with low risk to NASA flight projects. The target of experimentation will be the production software development activities undertaken by any organization prepared to contribute to the research program. Experimental goals, procedures, data analysis and result reporting will be performed for the most part by the University of Virginia.

Knight, J. C.↗

NASA NTRS2012

A CloudSat Perspective of the Atmospheric Water Cycle and Precipitation: Recent Progress and Grand Challenges

Summary Global - mean precipitation - is controlled by Earth's energy balance and is a quantifiable consequence of the water vapor feedback. Predictability rests on the degree to which the water vapor feedback is predictable. Regional scale - to a significant extent, changes are shaped by atmospheric circulation changes but we do not know the extent to which regional scale changes are predictable. The impacts of changes to atmospheric circulation on regional scale water cycle changes can be dramatic. Process - scale - significant biases to the CHARACTER of precipitation (frequency and intensity) is related to how the precipitation process is parameterized in models. Aerosol - We still do not know the extent to which the water cycle is influenced by aerosol but anecdotal evidence is building. The character of precipitation is affected by the way aerosol influence clouds and thus affects the forcing of the climate system through the albedo effect. Observations - we still have a way to go and need to approach the problem in a more integrated way (tie clouds, aerosol and precipitation together and then link to soil moisture, etc). Globally our capabilities seriously lag behind the science and model development.

terrestrial water cycles↗