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At least 1,099 records · Page 61

State-Based Behavior Modeling of the Integrated SLS-MPCV System

In NASA's effort to foster a human spaceflight capability beyond Earth's orbit, two space systems are being developed - the Space Launch System (SLS) and the Multi-Purpose Crew Vehicle (MPCV). As of this time, the interactions between the two systems during launch are not fully detailed. To remedy this situation, a Systems Engineering approach utilizing models was developed to investigate the behavior of the integrated SLS-MPCV stack during ascent and abort situations. Specifically, this innovative approach combines aspects of Model-Based Systems Engineering (MBSE) and state analysis to simultaneously model the physical, functional, and behavioral aspects of systems. This approach focuses solely on the interactions between the systems, leaving much of the internal workings of either system at a logical level (i.e., black box). By utilizing this newly defined approach, a behavior model for the integrated SLS-MPCV stack was developed, emphasizing only the subset of interactions between the systems that impact behavior. Finally, analysis is performed within the model to investigate requirements gaps and examine the execution times of key behaviors related to various ascent phases and abort scenarios. The work described in this paper is merely a portion of the outlined effort being undertaken for this project; only a segment of the SLS-MPCV system behavior will be described.

Space Launch System (SLS)↗

Next Generation Launch Technology Program Lessons Learned

In November 2002, NASA revised its Integrated Space Transportation Plan (ISTP) to evolve the Space Launch Initiative (SLI) to serve as a theme for two emerging programs. The first of these, the Orbital Space Plane (OSP), was intended to provide crew-escape and crew-transfer functions for the ISS. The second, the NGLT Program, developed technologies needed for safe, routine space access for scientific exploration, commerce, and national defense. The NGLT Program was comprised of 12 projects, ranging from fundamental high-temperature materials research to full-scale engine system developments (turbine and rocket) to scramjet flight test. The Program included technology advancement activities with a broad range of objectives, ultimate applications/timeframes, and technology maturity levels. An over-arching Systems Engineering and Analysis (SE&A) approach was employed to focus technology advancements according to a common set of requirements. Investments were categorized into three segments of technology maturation: propulsion technologies, launch systems technologies, and SE&A.

Cook, Stephen↗

Advanced Modeling of Control-Structure Interaction in Thrust Vector Control Systems

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of 8 mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. During the development of the SLS TVC system, a family of advanced dynamics models were developed to extend and compliment the simplified quasi-linear “simplex” model historically used for flight control design and stability analysis. The importance of these advanced models became increasingly evident after ambient and hot fire testing of the Core Stage, which revealed a number of findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. One driving factor for these results was a higher-than-expected degree of coupling between the TVC system, the engine dynamics, and the Core Stage structure. This paper is the third 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, a new method of modeling rocket vehicle thrust vectoring servoelastic dynamics is presented. In this approach, the load dynamics are replaced by a detailed finite element model containing both the rigid body and elastic modes. A partitioning technique is used to compute the effective compliance from the modal data and obtain accurate simulation results using a reduced number of generalized coordinates. Coupled backup structure and nozzle attach compliance effects on multiple engines are captured in higher fidelity than with a spring approximation, eliciting novel effects due to the complex load paths involved in the Core Stage structure. Validation of the model is demonstrated using a variety of structural/modal, laboratory, and full-scale hot fire test data.

Launch Vehicles↗

Advanced Modeling of Control-Structure Interaction in Thrust Vector Control Systems

The Space Launch System (SLS) Core Stage (CS) Thrust Vector Control (TVC) system is comprised of 8 mechanical feedback Shuttle heritage Type III TVC actuators and four RS-25 engines, each attached to a Shuttle heritage gimbal block/bearing. Two actuators are used to move each engine in two planes perpendicular to one another (i.e., pitch and yaw). The TVC system design leverages hardware from the Space Shuttle program as well as new hardware designed specifically for the Core Stage. During the development of the SLS TVC system, a family of advanced dynamics models were developed to extend and compliment the simplified quasi-linear “simplex” model historically used for flight control design and stability analysis. The importance of these advanced models became increasingly evident after ambient and hot fire testing of the Core Stage, which revealed a number of findings associated with the dynamic response of the TVC integrated system. Test responses suggested that the TVC did not meet its performance specifications and its step and frequency responses exhibited unexpected departures from prior lab tests and modeled behavior. One driving factor for these results was a higher-than-expected degree of coupling between the TVC system, the engine dynamics, and the Core Stage structure. This paper is the third 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, a new method of modeling rocket vehicle thrust vectoring servoelastic dynamics is presented. In this approach, the load dynamics are replaced by a detailed finite element model containing both the rigid body and elastic modes. A partitioning technique is used to compute the effective compliance from the modal data and obtain accurate simulation results using a reduced number of generalized coordinates. Coupled backup structure and nozzle attach compliance effects on multiple engines are captured in higher fidelity than with a spring approximation, eliciting novel effects due to the complex load paths involved in the Core Stage structure. Validation of the model is demonstrated using a variety of structural/modal, laboratory, and full-scale hot fire test data.

Launch Vehicles↗

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗

Steady Surface Pressure Measurement via the Lifetime Method With High-Speed Cameras in NASA's Unitary Plan Wind Tunnel

High spatial resolution measurement of steady surface pressure via pressure-sensitive paint at NASA Ames has traditionally relied on specialized cameras equipped to accumulate charge over multiple exposures, whereas measurement of the fluctuating component of pressure uses an altogether separate set of high-speed cameras. To reduce complexity of installation, data acquisition, and processing, we have implemented methods to use a single set of commercial off-the-shelf cameras to produce both steady and unsteady pressure measurements. Both imaging systems were installed in the 11-by 11-foot NASA Ames Unitary Plan Wind Tunnel and acquired images of a scaled model of the Space Launch System Block 1B Crew and Cargo configurations over a variety of flow conditions. This work focuses on methods for data acquisition, processing, and calibration to produce steady-state pressure estimates on the surface of the wind tunnel model based on the lifetime method. It will then compare the steady solutions produced by the legacy and high-speed imaging systems.

Pressure Sensitive Paint↗

Large Payload Ground Transportation and Test Considerations

During test and verification planning for the Altair lunar lander project, a National Aeronautics and Space Administration (NASA) study team identified several ground transportation and test issues related to the large payload diameter. Although the entire Constellation Program-including Altair-has since been canceled, issues identified by the Altair project serve as important lessons learned for payloads greater than 7 m diameter being considered for NASA's new Space Launch System (SLS). A transportation feasibility study found that Altair's 8.97 m diameter Descent Module would not fit inside available aircraft. Although the Ascent Module cabin was only 2.35 m diameter, the long reaction control system booms extended nearly to the Descent Module diameter, making it equally unsuitable for air transportation without removing the booms and invalidating assembly workmanship screens or acceptance testing that had already been performed. Ground transportation of very large payloads over extended distances is not generally permitted by most states, so overland transportation alone would not be an option. Limited ground transportation to the nearest waterway may be possible, but water transportation could take as long as 66 days per production unit, depending on point of origin and acceptance test facility; transportation from the western United States would require transit through the Panama Canal to access the Kennedy Space Center launch site. Large payloads also pose acceptance test and ground processing challenges. Although propulsion, mechanical vibration, and reverberant acoustic test facilities at NASA's Plum Brook Station have been designed to accommodate large spacecraft, special handling and test work-arounds may be necessary, which could increase cost, schedule, and technical risk. Once at the launch site, there are no facilities currently capable of accommodating the combination of large payload size and hazardous processing such as hypergolic fuels, pyrotechnic devices, and high pressure gasses. Ironically, the limiting factor to a national heavy lift strategy may not be the rocket technology needed to throw a heavy payload, but rather the terrestrial infrastructure-roads, bridges, airframes, and buildings-necessary to transport, acceptance test, and process large spacecraft. Failure to carefully consider where and how large spacecraft are manufactured, tested, and launched could result in unforeseen cost to modify existing (or develop new) infrastructure, or incur additional risk due to increased handling operations or eliminating key verifications.

Rucker, Michelle A.↗

Large Payload Ground Transportation and Test Considerations

Many spacecraft concepts under consideration by the National Aeronautics and Space Administration’s (NASA’s) Evolvable Mars Campaign take advantage of a Space Launch System payload shroud that may be 8 to 10 meters in diameter. Large payloads can theoretically save cost by reducing the number of launches needed--but only if it is possible to build, test, and transport a large payload to the launch site in the first place. Analysis performed previously for the Altair project identified several transportation and test issues with an 8.973 meters diameter payload. Although the entire Constellation Program—including Altair—has since been canceled, these issues serve as important lessons learned for spacecraft designers and program managers considering large payloads for future programs. A transportation feasibility study found that, even broken up into an Ascent and Descent Module, the Altair spacecraft would not fit inside available aircraft. Ground transportation of such large payloads over extended distances is not generally permitted, so overland transportation alone would not be an option. Limited ground transportation to the nearest waterway may be possible, but water transportation could take as long as 67 days per production unit, depending on point of origin and acceptance test facility; transportation from the western United States would require transit through the Panama Canal to access the Kennedy Space Center launch site. Large payloads also pose acceptance test and ground processing challenges. Although propulsion, mechanical vibration, and reverberant acoustic test facilities at NASA’s Plum Brook Station have been designed to accommodate large spacecraft, special handling and test work-arounds may be necessary, which could increase cost, schedule, and technical risk. Once at the launch site, there are no facilities currently capable of accommodating the combination of large payload size and hazardous processing such as hypergolic fuels, pyrotechnic devices, and high pressure gasses. Ironically, the limiting factor to a national heavy lift strategy may not be the rocket technology needed to throw a heavy payload, but rather the terrestrial infrastructure—roads, bridges, airframes, and buildings—necessary to transport, acceptance test, and process large spacecraft. Failure to carefully consider where and how large spacecraft are manufactured, tested, and launched could result in unforeseen cost to modify existing (or develop new) infrastructure, or incur additional risk due to increased handling operations or eliminating key verifications. Although this paper focuses on the canceled Altair spacecraft as a case study, the issues identified here have wide applicability to other large payloads, including concepts under consideration for NASA’s Evolvable Mars Campaign.

Rucker, Michelle A.↗

Validation of Shadowgraph Spectral Analysis using an SLS Block 2 Wind-Tunnel Model

A flow quantification method has previously been developed that uses high-speed shadowgraph images to extract frequency content of a transonic flow field around a wind-tunnel model. In this method, a classical spectral analysis is performed on shadowgraph video pixels to identify their intensity fluctuation frequencies. The spatial change of the image intensity is related to the second derivative of the density gradient. Examining the change of the density gradient as a function of time can be used to understand the flow-field pressure fluctuations. Time-varying pressure measurements collected during a Space Launch System (SLS) unsteady aerodynamic test of an advanced Block 2 booster design are used to calibrate the shadowgraph-based measurements. The test was performed at the NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-foot test section and investigated the aerodynamic environment downstream of candidate booster forward attachment hardware geometries of the SLS Block 2 Cargo configuration. Time-correlated shadowgraph video and model surface pressure measurements were acquired during the test and served as an ideal opportunity to calibrate and validate the shadowgraph image intensity method.

Shadowgraph↗

Validation of Shadowgraph Spectral Analysis using an SLS Block 2 Wind-Tunnel Model

A flow quantification method has previously been developed that uses high-speed shadowgraph images to extract frequency content of a transonic flow field around a wind-tunnel model. In this method, a classical spectral analysis is performed on shadowgraph video pixels to identify their intensity fluctuation frequencies. The spatial change of the image intensity is related to the second derivative of the density gradient. Examining the change of the density gradient as a function of time can be used to understand the flow-field pressure fluctuations. Time-varying pressure measurements collected during a Space Launch System (SLS) unsteady aerodynamic test of an advanced Block 2 booster design are used to calibrate the shadowgraph-based measurements. The test was performed at the NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-foot test section and investigated the aerodynamic environment downstream of candidate booster forward attachment hardware geometries of the SLS Block 2 Cargo configuration. Time-correlated shadowgraph video and model surface pressure measurements were acquired during the test and served as an ideal opportunity to calibrate and validate the shadowgraph image intensity method.

Shadowgraph↗

Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) Cost-Benefit Analysis

Lightning Launch Commit Criteria (LLCC) are designed to prevent space launch vehicles from flight through environments conducive to natural or triggered lightning and are used for all U.S. government and commercial launches at government and civilian ranges. They are maintained by a committee known as the NASA/USAF Lightning Advisory Panel (LAP). The previous LLCC for anvil cloud, meant to avoid triggered lightning, have been shown to be overly restrictive. Some of these rules have had such high safety margins that they prohibited flight under conditions that are now thought to be safe 90% of the time, leading to costly launch delays and scrubs. The LLCC for anvil clouds was upgraded in the summer of 2005 to incorporate results from the Airborne Field Mill (ABFM) experiment at the Eastern Range (ER). Numerous combinations of parameters were considered to develop the best correlation of operational weather observations to in-cloud electric fields capable of rocket triggered lightning in anvil clouds. The Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) was the best metric found. Dr. Harry Koons of Aerospace Corporation conducted a risk analysis of the VAHIRR product. The results indicated that the LLCC based on the VAHIRR product would pose a negligible risk of flying through hazardous electric fields. Based on these findings, the Kennedy Space Center Weather Office is considering seeking funding for development of an automated VAHIRR algorithm for the new ER 45th Weather Squadron (45 WS) RadTec 431250 weather radar and Weather Surveillance Radar-1988 Doppler (WSR-88D) radars. Before developing an automated algorithm, the Applied Meteorology Unit (AMU) was tasked to determine the frequency with which VAHIRR would have allowed a launch to safely proceed during weather conditions otherwise deemed "red" by the Launch Weather Officer. To do this, the AMU manually calculated VAHIRR values based on candidate cases from past launches with known anvil cloud LLCC violations. An automated algorithm may be developed if the analyses from past launches show VAHIRR would have provided a significant cost benefit by allowing a launch to proceed. The 45 WS at the ER and 30th Weather Squadron (30 WS) at the Western Range provided the AMU with launch weather summaries from past launches that were impacted by LLCC. The 45 WS provided summaries from 14 launch attempts and the 30 WS fkom 5. The launch attempts occurred between December 2001 and June 2007. These summaries helped the AMU determine when the LLCC were "red" due to anvil cloud. The AMU collected WSR-88D radar reflectivity, cloud-to-ground lightning strikes, soundings and satellite imagery. The AMU used step-by-step instructions for calculating VAHIRR manually as provided by the 45 WS. These instructions were used for all of the candidate cases when anvil cloud caused an LLCC violation identified in the launch weather summaries. The AMU evaluated several software programs capable of visualizing radar data so that VAHIRR could be calculated and chose GR2Analyst from Gibson Ridge Software, LLC. Data availability and lack of detail from some launch weather summaries permitted analysis of six launch attempts from the ER and none from the WR. The AMU did not take into account whether or not other weather LCC violations were occurring at the same time as the anvil cloud LLCC since the goal of this task was to determine how often VAHIRR provided relief to the anvil cloud LLCC at any time during several previous launch attempts. Therefore, in the statistics presented in this report, it is possible that even though VAHIRR provided relief to the anvil cloud LLCC, other weather LCC could have been violated not permitting the launch to proceed. The results of this cost-benefit analysis indicated VAHIRR provided relief from the anvil cloud LLCC between about 15% and 18% of the time for varying 5-minute time periods based on summaries fkom six launch attempts and would have allowed launch to proceed that were otherwise "NO GO" due to the anvil cloud LLCC if the T-0 time occurred during the anvil cloud LLCC violations.

Bauman, William H., III↗

Natural Environment Capabilities at MSFC

The Natural Environments Branch at Marshall Space Flight Center is integral in developing, maintaining, and investigating NASA missions such as Space Launch Systems (SLS), currently under development, as well as many NASA and other agency satellite missions. We present the space environment capabilities of the Natural Environments Branch at MSFC. These in-house capabilities include model development, analysis of space and terrestrial related data, spacecraft charging anomaly investigations, surface charging modeling including Nascap-2k, space environment definition and radiation parts assessment. All aspects of space and terrestrial design are implemented with the goal of devising missions to be successful at launch and in the space environment of LEO, polar, GEO, and interplanetary orbits. In this poster, we show examples of recent applications of branch capabilities to NASA missions.

Parker, Linda Neergaard↗

Launch Vehicle Manual Steering with Adaptive Augmenting Control In-flight Evaluations Using a Piloted Aircraft

An adaptive augmenting control algorithm for the Space Launch System has been developed at the Marshall Space Flight Center as part of the launch vehicles baseline flight control system. A prototype version of the SLS flight control software was hosted on a piloted aircraft at the Armstrong Flight Research Center to demonstrate the adaptive controller on a full-scale realistic application in a relevant flight environment. Concerns regarding adverse interactions between the adaptive controller and a proposed manual steering mode were investigated by giving the pilot trajectory deviation cues and pitch rate command authority.

pilot ratings↗

Artemis I: Test Flight Buys Down Risk for Humanity's Return to the Moon

The Artemis program successfully demonstrated its foundational deep space human transportation system during the Artemis I test flight in late 2022. This bold mission put the Artemis program on a course to accomplish increasingly complex missions to return humans to the Moon and to prepare for Mars and other destinations. The Artemis I uncrewed mission tested the Space Launch System (SLS) rocket and the Orion spacecraft using the ground processing, launch and recovery services provided by the Exploration Ground Systems (EGS) program at the Kennedy Space Center (KSC). The Artemis team accomplished key mission priorities that deliberately bought down risk for upcoming crewed missions as part of a build-up flight test strategy. The Artemis I mission priorities were 1) demonstrate Orion heatshield at lunar re-entry conditions; 2) operate systems in flight environment; and 3) retrieve the spacecraft. The successful performance and demonstration of these primary mission objectives from lift-off thru orbital insertion, translunar injection, outbound transit towards the Moon, entry into lunar orbit, coast in the lunar Distant Retrograde Orbit (DRO), exit from lunar orbit, transit back to Earth, atmospheric re-entry, descent, splashdown and recovery successfully showed that NASA has a foundational deep space transportation capability in place for human class missions. In addition to the primary mission objectives, a set of scientific payloads, approved Flight Test Objectives (FTOs) and Development Flight Test Objectives (DFTOs) were incorporated into the nominal mission plan and were designated as secondary, or priority 4, and were considered “bonus objectives” in terms of crewed flight risk buydown. During the mission, the team found itself in a position where it was comfortable achieving even more content than originally planned. As a result, DFTOs were added during the mission to further buy down risk to later crewed test flights. This paper presents an overview of the Artemis I test flight, including mission priorities and key test objectives, the launch campaign and as-flown mission profile, test objectives accomplished over the course of the 25.5- day mission, and implications to the crewed Artemis II and later test flight missions.

Artemis↗

Uncertainty Models for the Hybrid Parametric Variation Method of Uncertainty Quantification; Analysis

There is some level of uncertainty in every finite element model (FEM), which flows to a level of uncertainty in predicted results. The purpose of uncertainty quantification (UQ) is to provide statistical bounds on prediction accuracy based on model uncertainty. This is distinct from model updating, which attempts to modify models to improve their accuracy. UQ does not improve the accuracy of models, but accepts that the models are inherently inaccurate and attempts to quantify the impact of that inaccuracy on predicted results. Previously, an alternate method for UQ, called the Hybrid Parametric Variation (HPV) method, was applied to Space Launch System (SLS) Hurty/Craig-Bampton (HCB) components to predict system-level statistics for launch vehicle attitude control transfer functions and core stage section loads due to buffet. The HPV method combines a parametric variation of the HCB fixed-interface (FI) modal frequencies with a nonparametric variation (NPV) method that randomly varies the HCB mass and stiffness matrices as Wishart random matrix distributions using random matrix theory (RMT). Alternatively, the most common method for modeling uncertainty in the structural dynamics community is a parametric approach, which varies physical parameters in the model. However, there are several disadvantages associated with the parametric method. Determining a reduced set of parameters that have a significant impact on the system response can be time consuming, and the selected parameter probability distributions are rarely reliably known. Therefore, in practice, the parameters are surrogates for the actual errors, and the link to parameter uncertainty is unknown. Another major drawback is that the uncertainty that can be represented is limited to the form of the nominal FEM. It is the experience of the authors that based on numerous aerospace programs, almost all FEM errors are in form rather than parameter values. This hypothesis is supported by the observation of the authors that it is almost never possible to ‘tune’ a FEM to match modal test results by only modifying model parameters. Model-form uncertainty cannot be directly represented by FEM input parameters nor included in a parametric approach. However, model-form uncertainty can be modeled using RMT, where a probability distribution is developed for the matrix ensemble of interest. The major advantage of the NPV method is that it covers errors in model form. The HPV method anchors uncertainty at the HCB component level to component modal test results by matching the HCB and test modes based on mode descriptions or other methods, and then applying differing levels of frequency variation. The specific variations depend on the confidence to which a component FEM has been validated through modal testing. The NPV method is layered on the frequency variation to match modal test self-orthogonality and cross-orthogonality (XO) results. Once the component uncertainty models are identified, they are assembled, and the uncertainty is propagated to the system level using a Monte Carlo (MC) analysis approach that generates statistics for system-level predictions This provides a UQ method that can be traced to test data, which can be updated as additional data and improved correlated models become available. The purpose of this paper is to collect and present all of the theory for HPV that has been previously published in reports and papers and to present examples of its application. Specifically, component uncertainty models based on the dispersion of corresponding mass and stiffness matrices using proposed test/analysis correlation metrics are investigated. The first example is purely academic so that the true answers are known, and the validity of the HPV method and the corresponding uncertainty models can be determined. The purpose of this paper is to collect and present all of the theory for HPV that has been previously published in reports and papers and to present examples of its application. Specifically, component uncertainty models based on the dispersion of corresponding mass and stiffness matrices using proposed test/analysis correlation metrics are investigated. The first example is purely academic so that the true answers are known, and the validity of the HPV method and the corresponding uncertainty models can be determined. The second example is an application to a component that is design specific to the SLS. Based on this work and other assessments, the HPV method provides another tool to the toolset used for complex system UQ analysis. From experience gathered to date using the HPV method, additional design specific applications must be investigated to provide further confidence in the validity of the HPV method of UQ analysis.

Uncertainty quantification↗

Microwave and Millimeter Wave Nondestructive Evaluation of the Space Shuttle External Tank Insulating Foam

The Space Shuttle Columbia s catastrophic failure has been attributed to a piece of external fuel tank insulating SOFI (Spray On Foam Insulation) foam striking the leading edge of the left wing of the orbiter causing significant damage to some of the protecting heat tiles. The accident emphasizes the growing need to develop effective, robust and life-cycle oriented methods of nondestructive testing and evaluation (NDT&E) of complex conductor-backed insulating foam and protective acreage heat tiles used in the space shuttle fleet and in future multi-launch space vehicles. The insulating SOFI foam is constructed from closed-cell foam. In the microwave regime this foam is in the family of low permittivity and low loss dielectric materials. Near-field microwave and millimeter wave NDT methods were one of the techniques chosen for this purpose. To this end several flat and thick SOFI foam panels, two structurally complex panels similar to the external fuel tank and a "blind" panel were used in this investigation. Several anomalies such as voids and disbonds were embedded in these panels at various locations. The location and properties of the embedded anomalies in the "blind" panel were not disclosed to the investigating team prior to the investigation. Three frequency bands were used in this investigation covering a frequency range of 8-75 GHz. Moreover, the influence of signal polarization was also investigated. Overall the results of this investigation were very promising for detecting the presence of anomalies in different panels covered with relatively thick insulating SOFI foam. Different types of anomalies were detected in foam up to 9 in thick. Many of the anomalies in the more complex panels were also detected. When investigating the blind panel no false positives were detected. Anomalies in between and underneath bolt heads were not easily detected. This paper presents the results of this investigation along with a discussion of the capabilities of the method used.

Shrestha, S.↗

Using a Network of Boundary Layer Profilers to Characterize the Atmosphere at a Major Spaceport

Space launch, landing, and ground operations at the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) in east-central Florida are highly sensitive to mesoscale weather conditions throughout the year. Due to the complex land-water interfaces and the important role of mesoscale circulations, a high-resolution network of five 915-MHz Doppler Radar Wind Profilers (DRWP) and 44 wind towers was installed over the KSC/CCAFS area. By using quality-controlled 915-MHz DRAT data along with the near-surface tower observations, the Applied Meteorology Unit and KSC Weather Office have studied the development and evolution of various mesoscale phenomena across KSC/CCAFS such as sea and land breezes, low-level jets, and frontal passages. This paper will present some examples of mesoscale phenomena that can impact space operations at KSC/CCAFS, focusing on the utility of the 915-MHz DRWP network in identifying important characteristics of sea/land breezes and low-level jets.

Case, Jonathan L.↗