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At least 757 records · Page 42

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NASA NTRS2011

Multi-Axis Identifiability Using Single-Surface Parameter Estimation Maneuvers on the X-48B Blended Wing Body

The problem of parameter estimation on hybrid-wing-body type aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aero- dynamic control effectors that act in coplanar motion. This fact adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of system inputs must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, asymmetric, single-surface maneuvers are used to excite multiple axes of aircraft motion simultaneously. Time history reconstructions of the moment coefficients computed by the solved regression models are then compared to each other in order to assess relative model accuracy. The reduced flight-test time required for inner surface parameter estimation using multi-axis methods was found to come at the cost of slightly reduced accuracy and statistical confidence for linear regression methods. Since the multi-axis maneuvers captured parameter estimates similar to both longitudinal and lateral-directional maneuvers combined, the number of test points required for the inner, aileron-like surfaces could in theory have been reduced by 50%. While trends were similar, however, individual parameters as estimated by a multi-axis model were typically different by an average absolute difference of roughly 15-20%, with decreased statistical significance, than those estimated by a single-axis model. The multi-axis model exhibited an increase in overall fit error of roughly 1-5% for the linear regression estimates with respect to the single-axis model, when applied to flight data designed for each, respectively.

Ratnayake, Nalin A.↗

NASA NTRS2007

ISRU System Model Tool: From Excavation to Oxygen Production

In the late 80's, conceptual designs for an in situ oxygen production plant were documented in a study by Eagle Engineering [1]. In the "Summary of Findings" of this study, it is clearly pointed out that: "reported process mass and power estimates lack a consistent basis to allow comparison." The study goes on to say: "A study to produce a set of process mass, power, and volume requirements on a consistent basis is recommended." Today, approximately twenty years later, as humans plan to return to the moon and venture beyond, the need for flexible up-to-date models of the oxygen extraction production process has become even more clear. Multiple processes for the production of oxygen from lunar regolith are being investigated by NASA, academia, and industry. Three processes that have shown technical merit are molten regolith electrolysis, hydrogen reduction, and carbothermal reduction. These processes have been selected by NASA as the basis for the development of the ISRU System Model Tool (ISMT). In working to develop up-to-date system models for these processes NASA hopes to accomplish the following: (1) help in the evaluation process to select the most cost-effective and efficient process for further prototype development, (2) identify key parameters, (3) optimize the excavation and oxygen production processes, and (4) provide estimates on energy and power requirements, mass and volume of the system, oxygen production rate, mass of regolith required, mass of consumables, and other important parameters. Also, as confidence and high fidelity is achieved with each component's model, new techniques and processes can be introduced and analyzed at a fraction of the cost of traditional hardware development and test approaches. A first generation ISRU System Model Tool has been used to provide inputs to the Lunar Architecture Team studies.

Santiago-Maldonado, Edgardo↗

NASA NTRS2012

Uncertainty Analysis of the Grazing Flow Impedance Tube

This paper outlines a methodology to identify the measurement uncertainty of NASA Langley s Grazing Flow Impedance Tube (GFIT) over its operating range, and to identify the parameters that most significantly contribute to the acoustic impedance prediction. Two acoustic liners are used for this study. The first is a single-layer, perforate-over-honeycomb liner that is nonlinear with respect to sound pressure level. The second consists of a wire-mesh facesheet and a honeycomb core, and is linear with respect to sound pressure level. These liners allow for evaluation of the effects of measurement uncertainty on impedances educed with linear and nonlinear liners. In general, the measurement uncertainty is observed to be larger for the nonlinear liners, with the largest uncertainty occurring near anti-resonance. A sensitivity analysis of the aerodynamic parameters (Mach number, static temperature, and static pressure) used in the impedance eduction process is also conducted using a Monte-Carlo approach. This sensitivity analysis demonstrates that the impedance eduction process is virtually insensitive to each of these parameters.

Brown, Martha C.↗

NASA NTRS2007

Oxygen production System Models for Lunar ISRU

In-Situ Resource Utilization (ISRU) seeks to make human space exploration feasible; by using available resources from a planet or the moon to produce consumables, parts, and structures that otherwise would be brought from Earth. Producing these in situ reduces the mass of such that must be launched and doing so allows more payload mass' for each mission. The production of oxygen from lunar regolith, for life support and propellant, is one of the tasks being studied under ISRU. NASA is currently funding three processes that have shown technical merit for the production of oxygen from regolith: Molten Salt Electrolysis, Hydrogen Reduction of Ilmenite, and Carbothermal Reduction. The ISRU program is currently developing system models of, the , abovementioned processes to: (1) help NASA in the evaluation process to select the most cost-effective and efficient process for further prototype development, (2) identify key parameters, (3) optimize the oxygen production process, (4) provide estimates on energy and power requirements, mass and volume.of the system, oxygen production rate, mass of regolith required, mass of consumables, and other important parameters, and (5) integrate into the overall end-to-end ISRU system model, which could be integrated with mission architecture models. The oxygen production system model is divided into modules that represent unit operations (e.g., reactor, water electrolyzer, heat exchanger). Each module is modeled theoretically using Excel and Visual Basic for Applications (VBA), and will be validated using experimental data from on-going laboratory work. This modularity (plug-n-play) feature of each unit operation allows the use of the same model on different oxygen production systems simulations resulting in comparable results. In this presentation, preliminary results for mass, power, volume will be presented along with brief description of the oxygen production system model.

Santiago-Maldonado, Edgardo↗

NASA NTRS2014

Analytic Ballistic Performance Model of Whipple Shields

The dual-wall Whipple shield is the shield of choice for lightweight, long-duration flight. The shield uses an initial sacrificial wall to initiate fragmentation and melt an impacting threat that expands over a void before hitting a subsequent shield wall of a critical component. The key parameters to this type of shield are the rear wall and its mass which stops the debris, as well as the minimum pressure generated under threat particle impact of the sacrificial wall and the amount of void that is available for expansion. Ensuring the minimum pressure is sufficiently high to achieve large scale fragmentation/melt of the threat particle enables the expansion of the threat and reduces the momentum flux of the debris on the rear wall. Three key factors in the minimum pressure achieved are the thickness of the sacrificial wall relative to the characteristic dimension of the impacting particle, the density and material cohesion contrast of the sacrificial wall relative to the threat particle and the impact speed. The mass of the rear wall and the sacrificial wall are desirable to minimize for launch costs and dynamic concerns making it important to have an understanding of the effects of density contrast and impact speed. In this paper a fourth key parameter is identified related to fragmentation, which corresponds to the ratio of the size of the projectile relative to the transition from brittle to ductile hole growth in the projectile. Ballistic limit equations have been developed to define the failure limits of a MMOD shield, generally in terms of projectile diameter (or mass), impact velocity, and angle. Within the range of impact velocities relevant for Earth-orbiting spacecraft, three distinct regions of penetration phenomenology have been identified for Whipple shields: center dot Low velocity: the projectile is eroded (and possibly deformed) during its passage through the bumper plate, but is not fragmented. Thus, perforation of the rear wall is by a fragment with a mass and speed equal to or less than the original impactor. center dot Intermediate (shatter) velocity: impact velocities are sufficient to induce projectile fragmentation upon impact with the bumper plate, resulting in a coarse debris cloud with large solid fragments. Increasing velocity within the shatter regime results in increased fragmentation, and eventually melting, of the projectile and bumper fragments, generating a finer and more evenly dispersed debris cloud. Failure of the rear wall is a complicated combination of modes observed at low- and hypervelocity. center dot Hypervelocity: the projectile and holed-out bumper material is completely, or nearly completely, melted and/or vaporized by the initial impact. The resultant debris cloud impacts over a dispersed area of the rear wall, loading it impulsively and inducing failure through rupture or petalling. While each of these regimes are well observed with extensive empirical methods to describe these regions, differences in impactor materials, configurations of shields and questions about the limitations of the attainable impact speeds have left questions that are difficult to answer from completely empirical methods.

Miller, J. E.↗

NASA NTRS2014

Buckling Analysis for Stiffened Anisotropic Circular Cylinders Based on Sanders Nonlinear Shell Theory

Nonlinear and bifurcation buckling equations for elastic, stiffened, geometrically perfect, right-circular cylindrical, anisotropic shells subjected to combined loads are presented that are based on Sanders' shell theory. Based on these equations, a three-parameter approximate Rayleigh-Ritz solution and a classical solution to the buckling problem are presented for cylinders with simply supported edges. Extensive comparisons of results obtained from these solutions with published results are also presented for a wide range of cylinder constructions. These comparisons include laminated-composite cylinders with a wide variety of shell-wall orthotropies and anisotropies. Numerous results are also given that show the discrepancies between the results obtained by using Donnell's equations and variants of Sanders' equations. For some cases, nondimensional parameters are identified and "master" curves are presented that facilitate the concise representation of results.

Nemeth, Michael P.↗

NASA NTRS2015

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Spacecraft Systems↗

NASA NTRS2014

Parametric Trace Slicing

A program trace is obtained and events of the program trace are traversed. For each event identified in traversing the program trace, a trace slice of which the identified event is a part is identified based on the parameter instance of the identified event. For each trace slice of which the identified event is a part, the identified event is added to an end of a record of the trace slice. These parametric trace slices can be used in a variety of different manners, such as for monitoring, mining, and predicting.

Rosu, Grigore↗

NASA NTRS2014

Co-Optimization of Blunt Body Shapes for Moving Vehicles

A method and associated system for multi-disciplinary optimization of various parameters associated with a space vehicle that experiences aerocapture and atmospheric entry in a specified atmosphere. In one embodiment, simultaneous maximization of a ratio of landed payload to vehicle atmospheric entry mass, maximization of fluid flow distance before flow separation from vehicle, and minimization of heat transfer to the vehicle are performed with respect to vehicle surface geometric parameters, and aerostructure and aerothermal vehicle response for the vehicle moving along a specified trajectory. A Pareto Optimal set of superior performance parameters is identified.

Brown, James L.↗

NASA NTRS2016

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases.1 Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission.2 Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an Advanced Design Methods (ADM) based approach. This approach applies the concepts of Design of Experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development e ort. In order to t a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of Ground Rules and Assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated \what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are t to the outputs of each environment and are integrated via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any \what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will have the potential to lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗

NASA NTRS2016

Application of Design of Experiments and Surrogate Modeling within the NASA Advanced Concepts Office, Earth-to-Orbit Design Process

Decisions made during early conceptual design have a large impact upon the expected life-cycle cost (LCC) of a new program. It is widely accepted that up to 80% of such cost is committed during these early design phases. Therefore, to help minimize LCC, decisions made during conceptual design must be based upon as much information as possible. To aid in the decision making for new launch vehicle programs, the Advanced Concepts Office (ACO) at NASA Marshall Space Flight Center (MSFC) provides rapid turnaround pre-phase A and phase A concept definition studies. The ACO team utilizes a proven set of tools to provide customers with a full vehicle mass breakdown to tertiary subsystems, preliminary structural sizing based upon worst-case flight loads, and trajectory optimization to quantify integrated vehicle performance for a given mission. Although the team provides rapid turnaround for single vehicle concepts, the scope of the trade space can be limited due to analyst availability and the manpower requirements for manual execution of the analysis tools. In order to enable exploration of a broader design space, the ACO team has implemented an advanced design methods (ADM) based approach. This approach applies the concepts of design of experiments (DOE) and surrogate modeling to more exhaustively explore the trade space and provide the customer with additional design information to inform decision making. This paper will first discuss the automation of the ACO tool set, which represents a majority of the development effort. In order to fit a surrogate model within tolerable error bounds a number of DOE cases are needed. This number will scale with the number of variable parameters desired and the complexity of the system's response to those variables. For all but the smallest design spaces, the number of cases required cannot be produced within an acceptable timeframe using a manual process. Therefore, automation of the tools was a key enabler for the successful application of an ADM approach to an ACO design study. Following the overview of the tool set automation, an example problem will be given to illustrate the implementation of the ADM approach. The example problem will first cover the inclusion of ground rules and assumptions (GR&A) for a study. The GR&A are very important to the study as they determine the constraints within which a trade study can be conducted. These trades must ultimately reconcile with the customer's desired output and any anticipated "what if" questions. The example problem will then illustrate the setup and execution of a DOE through the automated ACO tools. This process is accomplished more efficiently in this work by splitting the tools into two separate environments. The first environment encompasses the structural optimization and mass estimation tools, while the second is focused on trajectory optimization. Surrogate models are fit to the outputs of each environment and are "integrated" via connection of the surrogate equations. Throughout this process, checks are implemented to compare the output of the surrogates to the output of manually run cases to ensure that the error of the final surrogates is at an acceptable level. The conclusion of the example problem demonstrates the utility of the ADM based approach. Using surrogate models gives the ACO team the ability to visualize vehicle sensitivities to various design parameters and identify regions of interest within the design space. The ADM approach can thus be used to inform concept down selection and isolate promising vehicle configurations to be explored in more detail through the manual design process. In addition it provides the customer with an almost instantaneous turnaround on any ''what if" questions that may arise within the bounds of the surrogate model. This approach ultimately expands the ability of the ACO team to provide its customer with broad and rapid turnaround trade studies for launch vehicle conceptual design. The ability to identify a selection of designs which can meet the customer requirements will help ensure lower LCC of launch vehicle designs originating from ACO.

Zwack, Mathew R.↗

NASA NTRS2016

Optimizing Power Density and Efficiency of a Double-Halbach Array Permanent-Magnet Ironless Axial-Flux Motor

NASA Glenn Research Center is investigating hybrid electric and turboelectric propulsion concepts for future aircraft to reduce fuel burn, emissions, and noise. Systems studies show that the weight and efficiency of the electric system components need to be improved for this concept to be feasible. This effort aims to identify design parameters that affect power density and efficiency for a double-Halbach array permanent-magnet ironless axial flux motor configuration. These parameters include both geometrical and higher-order parameters, including pole count, rotor speed, current density, and geometries of the magnets, windings, and air gap.

hybrid propulsion↗

NASA NTRS2016

Optimizing Power Density and Efficiency of a Double-Halbach Array Permanent-Magnet Ironless Axial-Flux Motor

electric propulsion↗

NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion systems core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

icing↗

NASA NTRS2017

Ice Crystal Icing Research at NASA

upwind schemes↗

NASA NTRS2017

Ice Crystal Icing Research at NASA

Ice crystals found at high altitude near convective clouds are known to cause jet engine power-loss events. These events occur due to ice crystals entering a propulsion system's core flowpath and accreting ice resulting in events such as uncommanded loss of thrust (rollback), engine stall, surge, and damage due to ice shedding. As part of a community with a growing need to understand the underlying physics of ice crystal icing, NASA has been performing experimental efforts aimed at providing datasets that can be used to generate models to predict the ice accretion inside current and future engine designs. Fundamental icing physics studies on particle impacts, accretion on a single airfoil, and ice accretions observed during a rollback event inside a full-scale engine in the Propulsion Systems Laboratory are summarized. Low fidelity code development using the results from the engine tests which identify key parameters for ice accretion risk and the development of high fidelity codes are described. These activities have been conducted internal to NASA and through collaboration efforts with industry, academia, and other government agencies. The details of the research activities and progress made to date in addressing ice crystal icing research challenges are discussed.

crysta↗

NASA NTRS2018

Aerodynamics and Aeroacoustic Sources of a Coaxial Rotor

Vehicles with coaxial, contra-rotating rotor systems (CACR) are being considered for a range of applications. Design parameters are identified that effect the fundamental aerodynamics and fluid dynamic features of a CACR in hover, vertical, and edgewise flight. Understanding the fluid dynamic features is a precursor to studying the aeroacoustics of a coaxial rotor. Rotor performance was computed initially using Navier-Stokes solver with prescribed blade section aerodynamic properties, the results validated against generic experimental test cases. Using a A 2D potential flow code and 2D OVERFLOW compressible-flow Navier-Stokes solver, the fluid dynamics of blade interactions was simplified and broken into a 2D blade crossing problem, with crossing locations and velocity fields from the rotor results to understand circulation, thickness, compressibility, shed vorticity, downwash, and viscosity effects. A calculation tool has been developed to identify time and location of blade overlap and BVI time location for CACR. Specific aerodynamic phenomena that occur for each noise source relevant to CACR are presented, along with computational tools to predict these occurrences.

Aeroacoustic↗

NASA NTRS2013

A Proposal for A Lean, Fast Mars Round-Trip Mission Architecture: Using Current Technologies for A Human Mission to Mars In The 2030s

We present a lean-minded, fast-transfer mission strategy and architecture concept for a first human mission to Mars that deliberately utilizes a current-technology-favored approach by means of introducing and quantitatively dening two pivotal parameters: 1) an end-to-end Mars mission duration of approximately one year, and 2) a deep space habitat of approximately 4050 metric tons. These parameters are identified and introduced by a 2012 deep space habitat study conducted at the NASA Johnson Space Center (JSC) that focused on a subset of recognized high-engineering-risk factors that may otherwise inhibit or encumber remote space travel to destinations such as Mars or near-Earth asteroids (NEAs). Additional constraints in the study favoring current technology and a lean-minded (very short) surface stay on Mars are shown to offer such Mars mission opportunities in the 2030s, enabled by a combination of on-orbit staging, mission element pre-positioning, and unique round-trip trajectories identied by state-of-the-art astrodynamics algorithms.

Architecture↗