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NASA NTRS2000

Mars Global Surveyor Ka-Band Frequency Data Analysis

The Mars Global Surveyor (MGS) spacecraft, launched on November 7, 1996, carries an experimental space-to-ground telecommunications link at Ka-band (32 GHz) along with the primary X-band (8.4 GHz) downlink. The signals are simultaneously transmitted from a 1.5-in diameter parabolic high gain antenna (HGA) on MGS and received by a beam-waveguide (BWG) R&D 34-meter antenna located in NASA's Goldstone Deep Space Network (DSN) complex near Barstow, California. The projected 5-dB link advantage of Ka-band relative to X-band was confirmed in previous reports using measurements of MGS signal strength data acquired during the first two years of the link experiment from December 1996 to December 1998. Analysis of X-band and Ka-band frequency data and difference frequency (f(sub x)-f(sub ka)/3.8) data will be presented here. On board the spacecraft, a low-power sample of the X-band downlink from the transponder is upconverted to 32 GHz, the Ka-band frequency, amplified to I-W using a Solid State Power Amplifier, and radiated from the dual X/Ka HGA. The X-band signal is amplified by one of two 25 W TWTAs. An upconverter first downconverts the 8.42 GHz X-band signal to 8 GHz and then multiplies using a X4 multiplier producing the 32 GHz Ka-band frequency. The frequency source selection is performed by an RF switch which can be commanded to select a VCO (Voltage Controlled Oscillator) or USO (Ultra-Stable Oscillator) reference. The Ka-band frequency can be either coherent with the X-band downlink reference or a hybrid combination of the USO and VCO derived frequencies. The data in this study were chosen such that the Ka-band signal is purely coherent with the X-band signal, that is the downconverter is driven by the same frequency source as the X-band downlink). The ground station used to acquire the data is DSS-13, a 34-meter BWG antenna which incorporates a series of mirrors inside beam waveguide tubes which guide the energy to a subterranean pedestal room, providing a stable environment for the feed and electronics equipment. A dichroic plate is used to reflect the X-band energy and pass the Ka-band energy to another mirror. The RF energy for each band is then focused onto a feed horn and low-noise amplifier package. After amplification and RF/IF downconversion, the IF signals are sent to the Experimental Tone Tracker (ETT), a digital phase-lock-loop receiver, which simultaneously tracks both X-band and Ka-band carrier signals. Once a signal is detected, the ETT outputs estimates of the SNR in a I -Hz bandwidth (Pc/No), baseband phase and frequency of the signals every I -sec. Between December 1996 and December 1998, the Ka-band and X-band signals from MGS were tracked on a regular basis using the ETT. The Ka-band downlink frequencies described here were referenced to the spacecraft's on-board USO which was also the X-band frequency reference (f(sub ka)= 3.8 f(sub x)). The ETT estimates of baseband phase at I -second sampled time tags were converted to sky frequency estimates. Frequency residuals were then generated for each band by removing a model frequency from each observable frequency at each time tag. The model included Doppler and other effects derived from spacecraft trajectory files obtained from the MGS Navigation Team. A simple troposphere correction was applied to the data. In addition to residuals, the USO frequencies emitted by the spacecraft were estimated. For several passes, the USO frequencies were determined from X-band data and from Ka-band data (referred to X-band by dividing by 3.8) and were found to be in good agreement. In addition, X-band USO frequency estimates from MGS Radio Science data acquired from operational DSN stations were available for comparison and were found to agree within the I Hz level. The remaining sub-Hertz differences were attributed to the different models and software algorithms used by MGS Radio Science and KaBLE-11. A summary of the results of a linear fit of the USO frequency versus time (day of year) is presented in Table I for an initial segment of passes.

Morabito, D.↗

NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗

NASA NTRSDate not supplied

Aerosol Wind Profiler (AWP) Doppler Wind Lidar Airborne Observations During the NOAA Joint Venture 3-D Wind Measurement Demonstration and NASA Active-Passive Profiling Experiment (APEX)

The NASA Langley Research Center (LaRC) has recently completed development of the Aerosol Wind Profiler (AWP) airborne Doppler wind lidar (DWL) instrument. AWP was supported by the NASA Earth Science Technology Office and the Earth Science Division, a project that adapted the Wind-Space Pathfinder (Wind-SP) DWL transceiver onto a structure for flight aboard a variety of NASA research aircraft. AWP demonstrates many technologies required for a space DWL mission, including a coherent-detection, optical heterodyne laser transmitter with high pulse energy (up to ~55 mJ) and repetition rate (200 Hz), electronic control of the beam path allowing for multiple viewing angles (allowing vector wind measurements) with no moving parts, compact highly-stable and tunable reference lasers allowing for high-precision measurement of velocity at long ranges while mitigating the impact of satellite platform velocity, and many others. AWP represents NASA’s only currently operational airborne 3-D wind profiling sensor. NASA LaRC was selected by the NOAA Joint Venture (JV) program to conduct a suborbital 3-D Wind measurement campaign demonstrate how data from a coherent-detection DWL like AWP could serve NOAA’s weather analysis and forecasting needs. The NOAA JV program is designed to work with the private sector, academia and other federal agencies to explore the feasibility and capability of emerging technologies spacecraft and other mission-specific tools to meet NOAA’s mission requirements. AWP was initially demonstrated on the NASA DC-8 within this JV program in October 2023, piggybacking on the NASA EcoDemonstrator mission focused on in-situ sampling of jet aircraft emissions and contrail formation from Everett, Washington. The in-situ sampling resulted in very frequent and rapid aircraft attitude changes which unfortunately degraded AWP data quality. But, during times with level flight and AVAPS dropsonde operations, AWP demonstrated excellent precision (< 2 m/s RMS) with high vertical (< 100 meter) resolution and 2 km spacing between profiles. AWP will be flown again on the NASA LaRC Gulfstream-3 from mid-September to mid-October 2024 out of Hampton, VA to complete the NOAA JV 3-D wind demonstration. Additional AWP flights will occur in early November from southern California during the NASA Active-Passive Profiling Experiment (APEX), focused on underflights of the NASA ER-2 equipped with many atmospheric profiling sensors. This presentation will summarize AWP measurements collected during these two fall 2024 flight campaigns, and how the AWP data compares with AVAPS dropsonde, NOAA weather prediction model, and GOES atmospheric motion vector data.

Kristopher Bedka↗

NASA NTRS1996

Random root movements in weightlessness

The dynamics of root growth was studied in weightlessness. In the absence of the gravitropic reference direction during weightlessness, root movements could be controlled by spontaneous growth processes, without any corrective growth induced by the gravitropic system. If truly random of nature, the bending behavior should follow so-called 'random walk' mathematics during weightlessness. Predictions from this hypothesis were critically tested. In a Spacelab ESA-experiment, denoted RANDOM and carried out during the IML-2 Shuttle flight in July 1994, the growth of garden cress (Lepidium sativum) roots was followed by time lapse photography at 1-h intervals. The growth pattern was recorded for about 20 h. Root growth was significantly smaller in weightlessness as compared to gravity (control) conditions. It was found that the roots performed spontaneous movements in weightlessness. The average direction of deviation of the plants consistently stayed equal to zero, despite these spontaneous movements. The average squared deviation increased linearly with time as predicted theoretically (but only for 8-10 h). Autocorrelation calculations showed that bendings of the roots, as determined from the 1-h photographs, were uncorrelated after about a 2-h interval. It is concluded that random processes play an important role in root growth. Predictions from a random walk hypothesis as to the growth dynamics could explain parts of the growth patterns recorded. This test of the hypothesis required microgravity conditions as provided for in a space experiment.

STS-65 Shuttle Project↗

NASA NTRS2020

History and Logic Model NASA Goddard Space Flight Center Instrument and Payload Systems Engineering Technical Performance Study

Historically, some NASA missions have exceeded schedule and cost commitments. Studies suggest technical performance is a contributor. The 1980 NASA Project Management Study concluded, "one of the most significant contributors to cost and schedule growth is inadequate definition of technical and management aspects of a program..." (as cited in GAO/NSIAD-93-97, p. 11). The 1991 NASA Roles and Missions Report identified a "need for increased emphasis on technological readiness and requirements on the front end of a program" (as cited in GAO/NSIAD-93-97, p. 11). The 1992 NASA Program Costs Report stated that NASA officials identified, among other things, "insufficient definition studies... [and] program redesigns and technical complexities" as reasons for cost and schedule overruns (GAO/NSAID-93-97, p. 11). The 2002 Task Force on Acquisition of National Security Space Programs found "requirements definition and control issues, unhealthy cost bias in proposal evaluation, widespread lack of budget reserves required to implement high risk programs on schedule, and an overall underappreciation of the importance of appropriately staffed and trained system engineering staff to manage the technologically demanding and unique aspects of space programs" (DoD, 2003, p.i.) In 2007, The NASA Office of the Chief Engineer chartered the NASA Instrument Capability Study (NICS) “to determine whether NASA instrument developers are facing challenges that impact the capability to design and build quality instruments or whether there are flaws in the acquisition strategy evidenced by schedule delays, cost overruns, and increased technical risk via design deficiencies. The... team was also chartered to determine if occurrences [are]... isolated cases or if there are generic issues... If the issues [are] found to be generic, the team [is] to offer solutions to recover such capability" (NICS Report, 2008, p. vi). The 2008 NICS Report, led by Goddard Space Flight Center (GSFC), identified challenges to instrument technical performance consistent with findings from previous reports. In 2017, the Instrument Project Division (IPD) Implementation Study was initiated to determine if there was a change in meeting schedule and cost commitments after implementing certain NICS recommendations. In 2018, the Instrument Technical Performance Study was initiated to determine the current state of Instrument Technical Performance in the GSFC Payload & Instrument Systems Engineering Branch. The purpose of the combined studies is to answer the question, "Is there a relationship between meeting NASA scientific instrument technical success and meeting schedule and cost commitments? If yes, what is the relationship?" References Department of Defense Office of the Under Secretary of Defense for Acquisition, Technology, and Logistics. (2003). The report of the defense science board/ air force scientific advisory board joint task force on acquisition of national security space programs. Washington DC. Government Accounting Office. (1992). NASA program costs: Space missions require substantially more funding than initially estimated. GAO/NSIAD-93-97. Washington DC. National Aeronautics and Space Administration, National Oceanic and Atmospheric Agency, Department of Defense. (2008). The NASA instrument capability study final report. NP-2008-11-058-GSFC. Washington DC.

Robbins, Geraldine↗

NASA NTRS2004

Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation table in the presence of various sources of laboratory noise is shown. The output of the neural network is called the degradable classification index. The curve was generated by a simultaneous comparison of means, and it shows a peak-to-peak sensitivity of about 100 nm. The following graph uses model generated data from a compressor blade to show that much higher sensitivities are possible when the environment can be controlled better. The peak-to-peak sensitivity here is about 20 nm. The training procedure was modified for the second graph, and the data were subjected to an intensity-dependent transformation called folding. All the measurements for this approach to calibration were optical. The peak-to-peak amplitudes of the vibration modes were measured using heterodyne interferometry, and the modes themselves were recorded using television (electronic) holography.

Decker, Arthur J.↗

NASA NTRS2001

Separating Spatial and Temporal Variations of the Aurora Using Two Nearly Colocated Satellites

This final report describes the efforts accomplished during the grant's period of performance, covering the period of 1 May 1997 to 30 April 2001, of a NASA Supporting Research and Technology Program grant under the Ionospheric, Thermospheric, and Mesospheric Physics component of the Sun-Earth Connections program. We have met and exceeded the goals set forth in the proposed research objectives. Referred publications have appeared in the scientific literature and several others are in the review process. In addition, numerous invited and contributed presentations of these studies were presented at national and international meetings during the performance period. One graduate student completed his PhD and won two AGU Best Student Paper awards based on research funded by this grant. These studies are summarized below. The science goal delineated in the initial proposal was "to systematically explore the temporal and spatial characteristics of the aurora in a way heretofore impossible, using data from two coplanar DMSP spacecraft." We accomplished this goal through a series of related studies. One study used these unique data to establish the role of Ps6 waves in coupling between the magnetosphere and the auroral ionosphere (omega bands) during the recovery phase of a magnetic storm; the published paper demonstrated the causal relationships between geospace processes occurring in different regions and established a simple conceptual model based on the fortuitous constellation of observations. In the second string of papers, we used these data to explore velocity-dispersed ions (VDIS) in and near the cusp, to test region identification models, and to look at space/time structure of auroral precipitation. On the first topic, the unique DMSP data revealed a remarkable double VDIS with a latitudinal overlap. This could only be explained in terms of a unified reconnection geometry that builds on several earlier unrelated models. The paper outlining this discovery has drawn considerable attention from the community and is currently in press - it adds significantly to the debate over whether reconnection is study state versus bursty and patchy versus global. The second paper develops the model further by incorporating the electron signature - these ionospheric particle precipitation signatures reveal the presence of magnetospheric "fossilized" FTEs, demonstrating the power of ionospheric measurements as a remote diagnostic of magnetospheric processes. Finally, the general nature of aurora] stability and coherence and region identification by particle characteristics were fully explored in a final paper. We identify candidate mechanisms controlling coherence time scales and length scales and refine boundary region identification criteria. We also use the dual-DMSP observations to identify the open and closed LLBL region and related its significance to the generalized bursty, multiple x-line model developed in the first paper. All of these topics are chapters of Dr. Boudouridis' recently completed PhD thesis.

Spence, Harlan E.↗

NASA NTRS2012

Internal Structure and Mineralogy of Differentiated Asteroids Assuming Chondritic Bulk Composition: The Case of Vesta

Bulk composition (including oxygen content) is a primary control on the internal structure and mineralogy of differentiated asteroids. For example, oxidation state will affect core size, as well as Mg# and pyroxene content of the silicate mantle. The Howardite-Eucrite-Diogenite class of meteorites (HED) provide an interesting test-case of this idea, in particular in light of results of the Dawn mission which provide information on the size, density and differentiation state of Vesta, the parent body of the HED's. In this work we explore plausible bulk compositions of Vesta and use mass-balance and geochemical modelling to predict possible internal structures and crust/mantle compositions and mineralogies. Models are constrained to be consistent with known HED samples, but the approach has the potential to extend predictions to thermodynamically plausible rock types that are not necessarily present in the HED collection. Nine chondritic bulk compositions are considered (CI, CV, CO, CM, H, L, LL, EH, EL). For each, relative proportions and densities of the core, mantle, and crust are quantified. Considering that the basaltic crust has the composition of the primitive eucrite Juvinas and assuming that this crust is in thermodynamic equilibrium with the residual mantle, it is possible to calculate how much iron is in metallic form (in the core) and how much in oxidized form (in the mantle and crust) for a given bulk composition. Of the nine bulk compositions tested, solutions corresponding to CI and LL groups predicted a negative metal fraction and were not considered further. Solutions for enstatite chondrites imply significant oxidation relative to the starting materials and these solutions too are considered unlikely. For the remaining bulk compositions, the relative proportion of crust to bulk silicate is typically in the range 15 to 20% corresponding to crustal thicknesses of 15 to 20 km for a porosity-free Vesta-sized body. The mantle is predicted to be largely dominated by olivine (>85%) for carbonaceous chondrites, but to be a roughly equal mixture of olivine and pyroxene for ordinary chondrite precursors. All bulk compositions have a significant core, but the relative proportions of metal and sulphide can be widely different. Using these data, total core size (metal+ sulphide) and average core densities can be calculated, providing a useful reference frame within which to consider geophysical/gravity data of the Dawn mission.

Toplis, M. J.↗

NASA NTRS2016

Refined AFC-Enabled High-Lift System Integration Study

A prior trade study established the effectiveness of using Active Flow Control (AFC) for reducing the mechanical complexities associated with a modern high-lift system without sacrificing aerodynamic performance at low-speed flight conditions representative of takeoff and landing. The current technical report expands on this prior work in two ways: (1) a refined conventional high-lift system based on the NASA Common Research Model (CRM) is presented that is more representative of modern commercial transport aircraft in terms of stall characteristics and maximum Lift/Drag (L/D) ratios at takeoff and landing-approach flight conditions; and (2) the design trade space for AFC-enabled high-lift systems is expanded to explore a wider range of options for improving their efficiency. The refined conventional high-lift CRM (HL-CRM) concept features leading edge slats and slotted trailing edge flaps with Fowler motion. For the current AFC-enhanced high lift system trade study, the refined conventional high-lift system is simplified by substituting simply-hinged trailing edge flaps for the slotted single-element flaps with Fowler motion. The high-lift performance of these two high-lift CRM variants is established using Computational Fluid Dynamics (CFD) solutions to the Reynolds-Averaged Navier-Stokes (RANS) equations. These CFD assessments identify the high-lift performance that needs to be recovered through AFC to have the CRM variant with the lighter and mechanically simpler high-lift system match the performance of the conventional high-lift system. In parallel to the conventional high-lift concept development, parametric studies using CFD guided the development of an effective and efficient AFC-enabled simplified high-lift system. This included parametric trailing edge flap geometry studies addressing the effects of flap chord length and flap deflection. As for the AFC implementation, scaling effects (i.e., wind-tunnel versus full-scale flight conditions) are addressed, as are AFC architecture aspects such as AFC unit placement, number AFC units, operating pressures, mass flow rates, and steady versus unsteady AFC applications. These efforts led to the development of a novel traversing AFC actuation concept which is efficient in that it reduces the AFC mass flow requirements by as much as an order of magnitude compared to previous AFC technologies, and it is predicted to be effective in driving the aerodynamic performance of a mechanical simplified high-lift system close to that of the reference conventional high-lift system. Conceptual system integration studies were conducted for the AFC-enhanced high-lift concept applied to a NASA Environmentally Responsible Aircraft (ERA) reference configuration, the so-called ERA-0003 concept. The results from these design integration assessments identify overall system performance improvement opportunities over conventional high-lift systems that suggest the viability of further technology maturation efforts for AFC-enabled high lift flap systems. To that end, technical challenges are identified associated with the application of AFC-enabled high-lift systems to modern transonic commercial transports for future technology maturation efforts.

Hartwich, Peter M.↗

NASA NTRS2001

Comparison of aortic and carotid baroreflex stimulus-response characteristics in humans

In order to characterize the stimulus-response relationships of the arterial, aortic, and carotid baroreflexes in mediating cardiac chronotropic function, we measured heart rate (HR) responses elicited by acute changes in mean arterial pressure (MAP) and carotid sinus pressure (CSP) in 11 healthy individuals. Arterial (aortic + carotid) baroreflex control of HR was quantified using ramped changes in MAP induced by bolus injection of phenylephrine (PE) and sodium nitroprusside (SN). To assess aortic-cardiac responses, neck pressure (NP) and suction (NS) were applied during PE and SN administration, respectively, to counter alterations in CSP thereby isolating the aortic baroreflex. Graded levels of NP and NS were delivered to the carotid sinus using a customized neck collar device to assess the carotid-cardiac baroreflex, independent of drug infusion. The operating characteristics of each reflex were determined from the logistic function of the elicited HR response to the induced change in MAP. The arterial pressures at which the threshold was located on the stimulus-response curves determined for the arterial, aortic and carotid baroreflexes were not significantly different (72+/-4, 67+/-3, and 72+/-4 mm Hg, respectively, P > 0.05). Similarly, the MAP at which the saturation of the reflex responses were elicited did not differ among the baroreflex arcs examined (98+/-3, 99+/-2, and 102+/-3 mm Hg, respectively). These data suggest that the baroreceptor populations studied operate over the same range of arterial pressures. This finding indicates each baroreflex functions as both an important anti-hypotensive and anti-hypertensive mechanism. In addition, this investigation describes a model of aortic baroreflex function in normal healthy humans, which may prove useful in identifying the origin of baroreflex dysfunction in disease- and training-induced conditions.

Non-NASA Center↗

NASA NTRSDate not supplied

New Features of the NEQAIR Radiation Code

The longest-lived code for predicting shock layer radiation, NEQAIR, is now in its 5th decade of service. Substantial changes to the code have been made over the previous decade, the most recent report of which was at the 5th Workshop on Radiation in High Temperature Gases in 2014, for the version referred to as NEQAIR14. This paper will review some of the improvements made to the NEQAIR code since then, which is now at v15.2. Some of these features are discussed briefly below. NEQAIR15 and subsequent versions have enabled parallel evaluation of multiple lines of sight. This is accomplished by utilizing the HDF5 file format and placing multiple lines into a single file, LOS.h5, which is used for both input and output. This approach enables straightforward parallel execution both over the number of lines of sight and the number of points per line. For large problems, runtime reduces linearly with the number of nodes deployed since each line is processed independently by a subset of MPI ranks. Three applications of the multi-line solver are discussed. The first has to do with performing loosely coupled radiation-flowfield solutions. In this case the computed absorption and emission coefficients are used to evaluate the total energy absorbed or emitted at each point, allowing evaluation of the volumetric source term in the flowfield. The second computation is for obtaining heat flux from nonuniform flows, which require integration over spherical co-ordinates. These are of particular interest for evaluating radiation on the vehicle backshell. This 3D option improves the angular integration scheme and allows adaptive line selection that together reduce the number of lines required by about an order of magnitude. The final application is for remote observation, which is essentially the 3D integration problem over a small solid angle. For all three of these computations, data can be stored in the HDF5 file which allows a NEQAIR run to be restarted when it times out, or to add atmospheric absorption or instrument scan functions. An additional level of parallelism is enabled in NEQAIR15.2 using GPU routines. The GPU parallelism has realized up to 8x speed-up when running on a single core but diminishes as CPU parallelism is increased. For running multi-line simulations, it may be easier to reserve a large number of CPU nodes than to obtain the number of GPU nodes required for similar performance. A GUI, known as NEQTPY, allows for reading and creating input files, running NEQAIR, and displaying results. A significant feature of NEQTPY is the ability to perform spectral fits to data. The fits can operate on a single line spectrum (radiance vs. wavelength) or a 3D input file with multiple columns of data. Other new features include improved constants, additional species, more detailed non-Boltzmann modelling, advanced user controls, the ability to read and calculate spectra from HITRAN datafiles, photodissociation and photoionization cross-sections. A “fast” automatic grid option may reduce the size and time of spectral calculations while still maintaining good accuracy for total heat flux.

Brett A Cruden↗

NASA NTRSDate not supplied

Analysis of Launch Vehicle Liftoff Debris: Historical Perspective from Space Shuttle and Application to Artemis I

Human exploration-class launch vehicles are inherently prone to debris due to the extreme environments generated during pre-launch operations, liftoff, and flight. The use of cryogenic propellants often requires thermal protection system (TPS) coatings, typically foam, to maintain the propellant conditions in the tank and prevent an accumulation ice on the external surface of the vehicle. Some ice growth is to be expected at umbilical interfaces, vents, flanges, or brackets where it is difficult to apply TPS. This ice may come loose at any time due to wind on the launch pad, structural vibration and acoustics after rocket ignition, or aerodynamic forces during flight. This phenomena is especially apparent on vehicles with no TPS, such as the Saturn V rockets used in the Apollo Program, see Figure 1. During propellant tanking, the thermal contraction of the underlying substrate may generate cracks in the TPS (Figure 1). Chunks of TPS can release due to the expansion of ingested gas from cryopumping or from aerodynamic forces if the crack creates an offset surface. Most foams will also have a certain amount of “popcorning” where small pieces of foam will pop off during flight because of the differential between the static surface pressure and the pressure of the gas trapped in the foam cell structure. There are a number of other coating or closeout materials that may be shed from the vehicle and become debris. During pre-launch operations and liftoff, the vehicle may also be exposed to debris originating from the launch pad or ground support equipment. This debris is separate from foreign object debris, or FOD, which is not intended to be present and is strictly controlled through operations and maintenance procedures. In this case, debris is generated from hardware and materials that are necessary for launch and are subject to the intense vibration, acoustics, and direct plume impingement of the launch environment. Examples include ice from umbilicals, tape and tie wraps that protect cables, and rust or corrosion from the launch platform. While NASA has historically been aware of debris as a potential issue that could cause a failure resulting in loss of mission, loss of vehicle, or loss of crew, the likelihood and severity of that risk was not always well understood or given sufficient weight in program and flight decisions. After the Space Shuttle Columbia accident (STS-107), the investigation found that foam TPS debris shed from the external tank was the proximate cause of the damage to the orbiter wing. Six previous observations of debris released from the foam ramp that covered the bipod connecting the forward end of the orbiter to the external tank resulted in minor changes or were determined to be accepted flight risks. Two occurrences of bipod ramp foam loss were not identified until the STS-107 investigation. Despite the damage inflicted by these debris strikes, the Shuttle Program Requirements Control Board deemed the vehicle safe to fly. During the Return to Flight effort following the Columbia disaster, NASA Engineering developed a process for the assessment of debris transport, impact, and damage tolerance to support independent assessments of risk by NASA Safety and Mission Assurance (S&MA). Under this system, each element (vehicle or ground system) defines a catalog of all expected debris based on launch history, component testing, or analysis. Debris transport analysis (DTA) is conducted using the debris catalog characteristics and potential flow transport mechanisms (e.g., vehicle aerodynamics, gravity, wind, plume-driven). The predicted debris impact locations and velocities are provided to the hardware owners, who use available test data and analysis to determine whether each component can withstand the impacts. In cases where the element hardware may be severely damaged or fail, the options are to mitigate the debris source through some change in design or operation, or to work with S&MA to try to characterize the probability of the impact and damage for program risk acceptance. Because of the differences in debris characteristics and transport, the DTA has been divided between the Liftoff and Ascent regimes. The development and application of Liftoff DTA methodology from the Shuttle Program to the current Artemis Program is the subject of this paper. Liftoff DTA covers the time from the start of pre-launch operations at the launch pad, up until the vehicle clears the launch tower and there is no longer any interaction with ground systems. Debris transport during this period is broadly classified as either gravity, wind, and plume-entrained (GWPE) or plume driven (PD). GWPE debris is generally lower speed, travelling in a forward-to-aft direction. PD transport includes flow features from the rocket ignition transient, as well as plume impingement and recirculation that occur as the vehicle lifts off the launch platform. In these cases, the debris typically moves in an aft-to-forward direction at higher speeds. The applicable transport mechanisms must be considered for each piece of debris depending on the material, and release location and time. For example, rust or metallic debris from the tower could fall (GWPE) and impact the vehicle before landing on the launch platform deck where it could be also be transported by plume impingement (PD). However, falling ice (GWPE) from an umbilical is unlikely to survive impact with the vehicle or launch platform and be available for PD transport. Modeling of debris transport is accomplished using a set of DTA tools which simulate debris trajectories subject to a reference frame acceleration (i.e., gravity) and aerodynamic drag. Where the trajectory encounters a solid surface, the debris is allowed to rebound with a specified coefficient of restitution. The drag is calculated by interpolating the fluid state at each point in the debris trajectory from high-fidelity computational fluid dynamics (CFD) simulations of the launch vehicle and pad. The CFD data may either be static (steady state or time averaged), typically for GWPE transport, or dynamic (time-accurate) for PD flow features like the ignition transient. Examples of the CFD flow field solutions for the Space Launch System (SLS) rocket and launch pad are shown in Figure 2. Typical SLS debris trajectory predictions from DTA are illustrated in Figure 3. The final version of this paper will include a more detailed examination of the Liftoff DTA process developed during the Shuttle Program, and how it has been augmented and applied to the SLS rocket under the Artemis Program. Comparisons with debris observations from the Artemis I launch will demonstrate validation of the tools and methodology.

Debris↗

NASA NTRSDate not supplied

Open-source Numerical Modeling of Solidification Cracking Susceptibility: Application to Refractory Alloy Systems

Introduction. Alloys such as aluminum, nickel-base, and austenitic stainless steels are susceptible to solidification cracking during welding and 3D printing. Compositional optimization is one method used to effectively mitigate solidification cracking of those alloy systems. With the surge in hypersonic and in-space propulsion activities, refractory metals (Nb, Mo, Ta, W, and Re) and their alloy derivatives are increasing in importance due to their extreme high melting point and retention of high-temperature strength; however, their chemistry was most typically optimized to promote ductility during mechanical operations such as drawing and forming. Welding of such alloys has been a challenge due to a number of issues including solidification cracking, atmospheric contamination (O, C, and N), as well as a shift in ductile-to-brittle transition to higher temperature following grain growth induced by welding. Compositional optimization of refractory alloys for solidification cracking resistance in particular is desirable as their usage increases with the advent of advanced manufacturing methods such as 3D printing. This work evaluates the effect of compositional variation in refractory metal systems on the solidification cracking susceptibility with the goals of optimizing existing alloys and joining process techniques, and formulating new alloys with increased solidification cracking resistance. Experimental Procedures. A python code was developed in a Jupyter notebook environment (Michael and Sowards, 2023) to facilitate the calculation of crack susceptibility index proposed by Kou (2015). Composition is entered as a single point, or as a 1-D or 2-D array. The notebook calls pycalphad (Otis and Liu, 2017 and Bocklund et al, 2020) to calculate the evolution of fraction solid as a function of temperature (under either Scheil or equilibrium assumptions) and then evaluates steepness of the fraction solid curve near the terminal stage of solidification to predict solidification cracking resistance. Open source thermodynamic databases available at online repositories are used (van de Walle). The process is setup in an automated fashion to generate plots that show variation in solidification cracking susceptibility according to composition on 1-D line plots or 2-D contour plots. The Jupyter notebook and crack susceptibility algorithm was also integrated with a widely used commercial CALPHAD code for validation and alloy exploration. Results and Discussion. The crack susceptibility model was first validated against a series of refractory alloy compositions evaluated in past work which utilized a specialized Varestraint test built inside a vacuum chamber environment (Lessman and Gold, 1971). The alloys tested in the Varestraint apparatus included T-111 (Ta-8W-2Hf), ASTAR-811C (Ta-8W-1Re-0.7Hf-0.025C), FS-85 (Nb-27Ta-10W-1Zr), T-222 (Ta-9.6W-2.4Hf-0.01C), Ta-10W, B-66 (Nb-5Mo-5V-1Zr), and SCb-291 (Nb-10W-10Ta). The initial test of the model showed a strong correlation with empirical Varestraint data, i.e., a Spearman rank correlation between model predictions and hot cracking measurements was observed to be greater than 0.8. Following the validation, a set of refractory metal binary mixtures was investigated to evaluate sensitivity of Nb, Mo, W, and Ta to C, N, and O content. A series of plots were produced that suggest ppmw ranges of C, N, and O where solidification cracking increases significantly and reaches a maximum. Also comparative ranking of each primary refractory metal to each interstitial was produced. For example C produces greater cracking response in Mo whereas O produces greater cracking response in Ta and Nb. Such compositional values have utility in setting limits on pickup of these interstitial elements during welding and printing rather than using a one-size-fits-all approach. Furthermore, the results have use in determining additive powder recycling requirements, which is especially pertinent for refractory metal powders due to their high cost compared to conventional alloys. Another application created thousands of hypothetical alloys within the nominal specified composition range of two widely used refractory alloys C103 (Nb-10Hf-1Ti) and TZM (Mo-0.5Ti-0.1Zr). The cracking index was calculated for the alloys and results were fed into machine learning regression techniques including Multiple Linear Regression, Ridge Regression, and Lasso Regression to determine relative potency each alloying element had on computed solidification cracking index. A series of linear equations were produced that relate composition of C103 and TZM to solidification cracking index. The crack susceptibility of C103 for example is described by an equation of the form: cracking index ~ O + 0.667*C + 0.635*N + 0.00037*Ta – 0.0008*Hf (in wt.%) From that equation, it is clear that O has strong propensity to induce solidification cracking. Interestingly, Hf is shown to reduce calculated cracking response. Finally, realizing the potential of this method to discover new refractory alloy formulations across the period table that have low solidification cracking sensitivity, the code was applied to new untested alloy systems including W-Zr-C, W-Ta-C, and others. Conclusions. In summary, an open source numerical method has been developed using Python code to calculate Kou’s crack susceptibility index. The method was applied to refractory metals which are inherently difficult to study from a weldability testing standpoint since inert shielding gas is not sufficient and welding is typically done in vacuum, especially in light of findings presented here where oxygen has profound influence on solidification cracking. This work revealed the effect of compositional variations on a series of refractory metals and showed the framework defined here will be useful in 1) the development of new alloys that have improved weldability and 3D printability, 2) placing compositional limits on existing alloys, and 3) ensuring adequate controls of manufacturing processes such as 3D printing where powder reuse is critical. Keywords. pycalphad; Python; refractory metals; solidification cracking. References. B. Bocklund et. al. (2020) http://doi.org/10.5281/zenodo.3630657. S. Kou. (2015) https://doi.org/10.1016/j.actamat.2015.01.034. G.G. Lessmann and R.E. Gold. Welding Journal, issue 1, pp. 1-s – 8-s (1971). F.N. Michael and J.W. Sowards. NASA/TM-20230002218 (2023). R. Otis and Z.-K. Liu. (2017) http://doi.org/10.5334/jors.140. A. Van de Wallle et. al. (2018) https://doi.org/10.1016/j.calphad.2018.04.003.

pycalphad↗

NASA NTRSDate not supplied

A Machine Learning Approach to Improve Air Traffic Management Initiatives

Collaborating closely with commercial air carriers and related organizations, the Federal Aviation Administration(FAA) regulates air traffic and ensures the safety and efficiency of air operations. Air traffic controllers make strategic decisions, such as delaying, rerouting, or canceling flights, partly based on guidance provided by the FAA’s Air TrafficControl System Command Center (ATCSCC). The guidance includes, among other things, control measures known asTraffic Management Initiatives (TMIs) designed to enhance safety and improve operational efficiency. TMIs play a crucial role in managing the demand and capacity within the U.S. National Airspace System (NAS). Two major TMIs that are routinely used (primarily to mitigate the adverse effects of bad weather) are Ground Delay Programs (GDPs) andGround Stops (GSs). In a GDP, flights destined for airports facing thunderstorm activity experience delays at their origin airports. This proactive approach minimizes the risk of routing aircraft through hazardous weather conditions and also replaces (fuel burning) airborne delays with ground delays. In a GS, a temporary restriction is imposed on the departure or arrival of aircraft at a specific airport or within a designated airspace. Although other TMIs (e.g., miles-in-trail) are also implemented as part of (air) traffic flow management in the NAS, the focus of this work is on GDPs and GSs. Since TMIs, by design, lead to flight delays or cancellations, it is crucial to put in place the right set of parameters(e.g., scope and duration of the GDP). For example, when the end time of a GDP extends beyond what is necessary, it imposes unnecessary delays on departing flights. This situation could occur as a result of inaccurate prediction of the(required) duration of the GDP based on the weather forecast. On the other hand, if a GDP ends prematurely before the underlying capacity constraints are resolved at the destination airport, it may result in airborne holding. The delicate balance lies in matching the termination of the GDP precisely with the resolution of capacity constraints, avoiding both the imposition of unnecessary ground delays and the need for airborne holding due to premature program termination.Failing to specify the right parameters for TMIs also leads to flight delays, creating a significant obstacle in managing the increasing traffic volumes causing increased work load for the controllers. To address this issue, we propose the integration of Machine Learning (ML) models in the traffic flow management(TFM) pipeline. In current operations, decisions are made by human experts based on extensive training, historical patterns, available traffic and weather data. Since we have an abundance of data from past events that tell us the likely impact of various TMIs, by ingesting historical data, properly trained ML models can offer valuable insights and aid human decision-making. With the FAA increasingly exploring advanced analytics, ML emerges as a focal point for enhancing TFM within the National Airspace System (NAS). As a first step, this study aims to provide traffic controllers with decision-making support for the issuance and adjustment of TMIs. Data analytics and machine learning have been previously employed to address some of the challenges associated with TMIs. Numerous studies have concentrated on various facets of TMI issuance, exploring factors influencing TMI parameters, including arrival rate, airport capacity, and delay prediction. For example, using weather forecasts, several statistical methods were used to produce probabilistic capacity profiles which in conjunction with deterministic models provided insights into the GDP planning process [1–4]. The downside of using deterministic models is that they rely on fixed inputs and predetermined rules, which lack the ability to account for the inherent uncertainty and variability present in real-world scenarios. In a separate series of studies, researchers aimed to predict the occurrences of GDPs and GSs. The majority of these studies utilized various supervised learning methods, including Decision Trees, Naive Bayes, Support VectorMachines, and Random Forests to analyze the influence of weather conditions and arrival demand on TMI incidents[5–8]. However, these studies primarily focused on predicting the incidence of TMIs without explicitly addressing the scope of TMIs, including their duration and their geographical coverage. Furthermore, the emphasis of these studies was largely on GDPs, given their higher frequency and longer duration when compared to GSs. A limited number of studies focused on predicting the parameters of TMIs, specifically addressing their duration and extent. In one such study focusing on optimizing the TMI parameters at San Francisco International Airport (SFO),the authors utilized a probabilistic forecast of fog [9]. They simulated various capacity scenarios based on the (fog)burn-off forecasts, selecting GDP parameters that minimized airborne and overall ground delays. However, this approach exclusively emphasizes stratus (fog) burn-off as the primary determinant of GDP and GS, neglecting other influential factors like severe weather events, runway closures, lower capacity than traffic demand, and other important variables. Given the complexity of predicting the TMI and determining its scope, we seek a more holistic approach. We aim to consider all significant factors that could impact TMIs and their parameters. What sets this research apart is the fusion of all data sources relevant to the issuance and adjustment of TMIs and it represents the first comprehensive attempt to optimize TMIs in this manner. Since this comprehensive solution involves various aspects, we break down the problem into smaller components and input all parameters into a unified model called the “TMI Adjuster”. Figure 1 shows the overall framework and the list of datasets used in each model. The objective of the TMI Adjuster module is to deliver reliable, consistent and expedited recommendations for the progression, adjustment, and termination of TMIs. The ML solution entails developing a pipeline capable of predicting the necessity of a TMI (e.g., GS or GDP) along with its various parameters. For example, in the case of a GS, this includes the scope of the GS either in terms of distance from the destination airport or based on pre-defined airspace sectors. Here, scope refers to those regions and departing airports that are subject to the GS. In this paper, we concentrate on the issuance of GSs in the three major airports in the New York area — LaGuardia(LGA), John F. Kennedy International (JFK), and Newark Liberty International (EWR). We fuse traffic, weather and other relevant aviation data from years 2017 to 2019 to train and validate the ML models. In particular, we use the following datasets: •Terminal Aerodrome Forecast (TAF): meteorological forecasts specific to each airport, issued four times a day, covering predefined time periods. •TMI data: includes all GSs and GDPs along with their respective parameters. •Aviation System Performance Metrics (ASPM): includes traffic related data such as aircraft delays, arrival, and departure rates. •Notices to Airmen (NOTAMs): utilized to extract runway closure data and manage interdependencies between terminals in close proximity. •Flight cancellation data •Airspace Flow Programs (AFP): includes information on flight airborne holdings caused by TMIs. The data preprocessing entails transforming ASPM, TMI, AFP, NOTAMs, and weather data into an hourly format and consolidating all datasets by merging them based on date and time as the primary key. The TMI Adjuster framework comprises two parallel models: one dedicated to GS and a second model focused on GDP. As previously mentioned, our specific focus is on the GS model as a multi-classification problem. In this framework, each data point of the GS model input summarizes ten hours of data. Specifically, the data loader for the GS model generates the input and output of the model as follows: at a given time step, the input includes the actual traffic, weather, and TMI data from the two-hour window before the time step, alongside the weather forecast and scheduled traffic for the next 8 hours starting from the time step. Based on this information, the output of the GS model for each time interval consists of three dimensions. The first dimension represents a binary decision on whether there should be a GS in place for the next hour or not. The second dimension is related to the scope of the GS in the United States, and the third dimension is related to the scope of the GS in Canada (i.e., to determine if the GS impacts airports in Canada).One of the challenges with TMI modeling is the sparsity of TMI events, particularly regarding its scope. To address this challenge in the scope of the GS model output, we implement grouping. The GS scope for the US region is defined based on a list of centers that should be included when the GS is in place. With 20 centers in the US, we utilized historical data to group them into 4 categories. In particular, we summarized our historical data in a graph format where nodes represent centers, and link weights are defined based on the co-occurrence of centers in the scope parameter ofTMIs. By identified strongly connected components in this graph, we were able to partition the centers into four groups. We consider two model structures for the GS Model. Firstly, a hierarchical classification model [10], where the human decision-making for a GS is of hierarchical nature. The decision-maker first decides whether there is a need fora GS, and if the answer is yes, determines the scope. A hierarchical classification model organizes the problem into a class hierarchy, typically a tree or a Directed Acyclic Graph (DAG) structure, and considers the dependency of the decision in the previous step to the next component [10]. Here, we employ the local classifier per level approach, which involves training one multi-class classifier for each level of the class hierarchy. The second structure is the independent structure. In this setting, as the name suggests, we do not consider the dependency of the decisions in the different dimensions of the output of the model. Instead, for each dimension, we train a multi-class classifier independently. Table 1 summarizes GS model statistics for training, validation and testing. The table documents the effect of limiting data to the time steps when there was actually a TMI in place or when a TMI had just terminated. This resulted in a more balanced distribution of the GS class(GS positive class)versus “No GS”(GS negative class), which might help the training process. While JFK and LGA follow very similar distributions, with 40% and 42% GS positive class respectively, EWR has proportionally fewer GS incidents at 28%. Our subsequent phase involves evaluating the performance of both hierarchical structure and independent structure using different state-of-the-art multi-class classifier models such as Random Forest, Decision Trees, K-nearest Neighbors, and Logistic Regression and forecast the duration and scope of the GSs.

Farzan Masrour Shalmani↗

NASA NTRS2005

Chapter 19B - Antenna Radiation Patterns

Modern civil and military aircraft are equipped with a variety of communication devices, radio navigation equipment, and air traffic control systems. For all of these devices appropriate antennas must be available to transmit and receive the signals. As a result, as many as 30 antennas, and sometimes even more, are mounted around today's aircraft. For this reason, it is necessary to know the capabilities of the receiving/transmitting equipment on board. These capabilities are driven by the antenna characteristics. Therefore, coverage, shading, and beam pointing pattern data are necessary for optimum electronic coverage. The aircraft antenna has to convert the available power density of the electromagnetic field to an electric voltage at its connector. This voltage level must be sufficiently high to operate the connected equipment. The reciprocity principle states that it makes no difference if the antenna is receiving or transmitting. For the certification of the aircraft antennas it must be proven that the antennas are at least generating the minimum receiver input voltage which is required for each radio service. The prime condition is, of course, that the specified field power densities of the different radio navigation and communication services are available. An important property of a radio frequency link is the electro-magnetic field intensity at every point in space for a given output power of the antenna. As the propagation of radio frequency waves in free space is well known, the spatial distribution of the field intensity needs only be measured at one spatial sphere around the antenna. The information is usually given as distributions along the circumference of flat sections through this sphere: each of these is called an ARP. Several ARPs are usually required to describe the complete spatial antenna pattern of an antenna. In addition to mathematical modeling, measurements on sub-scale models, and static measurements on full size models or aircraft on the ground, dynamic measurements on aircraft in flight play the most important role in the aircraft antenna testing and certification. [19B-1] The shape of an ARP, for one given frequency, is determined by the shape of the antenna and the shape and material of the surface it is mounted on. As the directly transmitted waves interfere with waves reflected by the aircraft skin with its complex geometry, and the surface material parameters are only roughly known, it is not possible to predict the ARP with the required accuracy. In ground measurements the earth's surface also acts as a reflector thereby causing the ground ARP to be different from the in-flight ARP. As the in-flight ARP is the ARP we are actually interested in it becomes clear that it is necessary to conduct in-flight ARP measurements. The Flight Test Engineer must be aware of the needs of the specialists who are establishing the test program for measuring antenna patterns and radar cross sections. These tests will require special test equipment and dedicated flights to obtain the data that they require. This Section provides an introduction to the principles of determining antenna patterns and the flight techniques for determining both antenna patterns and radar cross section. Reference 19B-1 provides detailed information.

Helmut Bothe↗

NASA NTRS2013

The Antarctic Search for Meteorites: A Model for Deep Space Exploration

In an era of shrinking buying power and reduced flight opportunities, NASA must extract the greatest possible value from all sources of insight into the future of human space exploration. Antarctica is one such source. The history of Antarctic exploration has many political and technical parallels with the development of space, and Antarctica's remoteness and harsh climate make it an excellent proxy for space (e.g., [1,2]). Links between exploration of space and of the Antarctic date back to the International Geophysical Year of 1957-1958, which saw both the launch of Sputnik 1 and the establishment of a station at the South Pole. The Antarctic Search for Meteorites (ANSMET) is an annual expedition to the south polar plateau to collect meteorites. Although its intent is not to simulate a space mission, the handful of astronauts who have participated in ANSMET agree that it is very similar to a long-duration space flight. Independently, NASA and other space agencies have simulated deep space exploration missions in "analog" activities at remote field sites on Earth (e.g., [3]). These include NASA Extreme Environment Mission Operations (NEEMO) [4,5], Desert Research And Technology Studies (Desert RATS) [6,7], and the Pavilion Lake Research Project (PLRP or simply Pavilion Lake) [8]. This report focuses on NEEMO, Desert RATS, and PLRP because of the author's firsthand experience with them. Other noteworthy analogs, such as the arctic Haughton Mars Project and the European Space Agency's underground Cooperative Adventure for Valuing and Exercising human behavior and performance Skills (CAVES), are not treated here. NASA analogs often include fully staffed control centers, astronauts serving as crew, and realistic mission timelines lasting one to two weeks. Analogs have provided key insights into system architectures and operational concepts for the future human exploration of deep space. They have pioneered techniques for human communication with significant speed-of-light delays, for conducting spacewalks on natural objects with negligible surface gravity, and for empowering exploration crews to work with reduced dependence on a ground control center. They have field-tested dozens of emerging technologies including spacewalking tools and full-scale prototype vehicles and habitats. They have provided valuable experience for astronauts preparing for their first space flight, and for flown crewmembers who will take command roles on later flights. Some analogs, especially PLRP, have connected observers in the field with science teams in remotely located control centers to produce high-quality, publishable scientific results. The analogs have accomplished all of this at a tiny fraction of the cost of an actual space flight. This report treats ANSMET as space flight analog. The chapter following this introduction describes ANSMET in depth. The report then presents data on logistics and crew considerations that may be useful for developers of future human space exploration missions. It offers detailed comparisons between ANSMET and past, present, and future space flights on the Space Shuttle, the International Space Station (ISS), and a proposed Mars mission. Those comparisons are intended to complement the work of Eppler [2], who compares ANSMET to the Apollo moon flights. This report also compares ANSMET with the Desert RATS, NEEMO, and PLRP analogs. It then presents observations and makes recommendations related to ANSMET's value as a simulated space mission. The report ends with a short conclusion. The remainder of this introductory chapter provides background material to help readers interpret the rest of the report. It gives brief overviews of Space Shuttle and ISS missions along with information on a notional future human flight to Mars. It also presents the general features of three of NASA's space flight "analog" projects. With those points of reference in place, the chapter concludes with an overview of ANSMET.

Love, Stanley G.↗

NASA NTRS1995

Lead-Lag Control for Helicopter Vibration and Noise Reduction

As a helicopter transitions from hover to forward flight, the main rotor blades experience an asymmetry in flow field around the azimuth, with the blade section tangential velocities increasing on the advancing side and decreasing on the retreating side. To compensate for the reduced dynamic pressure on the retreating side, the blade pitch angles over this part of the rotor disk are increased. Eventually, a high enough forward speed is attained to produce compressibility effects on the advancing side of the rotor disk and stall on the retreating side. The onset of these two phenomena drastically increases the rotor vibratory loads and power requirements, thereby effectively establishing a limit on the maximum achievable forward speed. The alleviation of compressibility and stall (and the associated decrease in vibratory loads and power) would potentially result in an increased maximum forward speed. In the past, several methods have been examined and implemented to reduce the vibratory hub loads. Some of these methods are aimed specifically at alleviating vibration at very high flight speeds and increasing the maximum flight speed, while others focus on vibration reduction within the conventional flight envelope. Among the later are several types passive as well as active schemes. Passive schemes include a variety of vibration absorbers such as mechanical springs, pendulums, and bifilar absorbers. These mechanism are easy to design and maintain, but incur significant weight and drag penalties. Among the popular active control schemes in consideration are Higher Harmonic Control (HHC) and Individual Blade Control (IBC). HHC uses a conventional swash plate to generate a multi-cyclic pitch input to the blade. This requires actuators capable of sufficiently high power and bandwidth, increasing the cost and weight of the aircraft. IBC places actuators in the rotating reference frame, requiring the use of slip rings capable of transferring enough power to the actuators. Both schemes cause an increase in pitch link loads. Trailing Edge Flap (TEF) deployment can also used to generate unsteady aerodynamic forces and moments that counter the original vibratory loads, and thereby reduce rotor vibrations. While the vibrations absorbers, HHC, IBC, and TEF concepts discussed above attempt to reduce the vibratory loads, they do not specifically address the phenomena causing the vibrations at high advance ratios. One passive method that attempts to directly alleviate compressibility and stall, instead of reducing the ensuing vibrations, is the use of advanced tip designs. Taper, sweep, anhedral, and the manipulation of other geometric properties of the blade tips can reduce the severity of stall and compressibility effects , as well as reduce rotor power. A completely different approach to solve these problems is the tiltrotor configuration. As the forward velocity of the aircraft increases, the rotors, in this case, are tilted forward until they are perpendicular to the flow and act as propellers. This eliminates the edgewise flow encountered by conventional rotors and circumvents all the problems associated with flow asymmetry. However, the success involves a tremendous increase in cost and complexity of the aircraft. Another possible approach that has been proposed for the alleviation of vibratory loads at high forward flight speeds involves the use of controlled lead-lag motions to reduce the asymmetry in flow. A correctly phased 1/rev controlled lag motion could be introduced such that it produces a backward velocity on the advancing side and a forward velocity on the retreating side, to delay compressibility effects and stall to a higher advance ratio. Using a large enough lead-lag amplitude, the tip velocities could be reduced to levels encountered in hover. This concept was examined by two groups in the 1950's and early 1960's. In the United States, the Research Labs Division of United Aircraft developed a large lead-lag motion rotor, meant to achieve lag motion amplitudes up to 45 degrees. In order to reduce the required actuation force, the blade hinges were moved to 40% of the blade radius to increase the rotating lag frequency to approximately 1/rev. The blade hinges were redesigned to produce a flap-lag coupling so the large flapwise aerodynamic loads could be exploited to actuate the blades in the lag direction. A wind tunnel test of this rotor concept revealed actuation and blade motion scheduling problems. The project was eventually discontinued due to these problems and high blade stresses. Around the same time, at Boelkow in Germany, a similar lead-lag rotor program was conducted under the leadership of Hans Derschmidt. Here, too, the blade hinges were moved outboard to 34% radius to reduce the actuation loads. The main difference between this and the United Aircraft program was the use of a mechanical actuation scheme with maximum lead-lag motions of 400. This program was also discontinued for unclear reasons. The present study is directed toward conducting a comprehensive analytical examination to evaluate the effectiveness of controlled lead-lag motions in reducing vibratory hub loads and increasing maximum flight speed. Since both previous studies on this subject were purely experimental, only a limited data set and physical understanding of the problem was obtained. With the currently available analytical models and computational resources, the present effort is geared toward developing an in-depth physical understanding of the precise underlying mechanisms by which vibration reduction may be achieved. Additionally, in recognition of the fact that large amplitude lead-lag motions would - (i) be difficult to implement, and (ii) produce very large blade stresses; the present study examines the potential of only moderate-to-small lead-lag motions for reduction of vibratory hub loads. Using such an approach, the emphasis is not on eliminating the periodic variations in tangential velocity at the blade tip, but at best reducing these variations slightly so that compressibility and stall are delayed to slightly higher advance ratios. This study was conducted in two steps. In the first step, a hingeless helicopter rotor was modeled using rigid blades undergoing flap-lag-torsion rotations about spring restrained hinges and bearings. This model was then modified by separating the lead-lag degree of freedom into two components, a free and a prescribed motion. Using this model, a parametric study of the effect of phase and amplitude of a prescribed lead-lag motion on hub vibration was conducted. The data gathered was analyzed to obtain an understanding of the basic physics of the problem and show the capability of this method to reduce vibration and expand the flight envelope. In the second half of the study, the similar analysis was conducted using an elastic blade model to confirm the effects predicted by the simpler model.

Gandhi, Farhan↗

NASA NTRS2014

Dividing the Concentrator Target From the Genesis Mission

The Genesis spacecraft, launched in 2001, traveled to a Lagrangian point between the Earth and Sun to collect particles from the solar wind and return them to Earth. However, during the return of the spacecraft in 2004, the parachute failed to open during descent, and the Genesis spacecraft crashed into the Utah desert. Many of the solar wind collectors were broken into smaller pieces, and the field team rapidly collected the capsule and collector pieces for later assessment. On each of the next few days, the team discovered that various collectors had survived intact, including three of four concentrator targets. Within a month, the team had imaged more than 10,000 fragments and packed them for transport to the Astromaterials Acquisition and Curation Office within the ARES Directorate at JSC. Currently, the Genesis samples are curated along with the other extraterrestrial sample collections within ARES. Although they were broken and dirty, the Genesis solar wind collectors still offered the science community the opportunity to better understand our Sun and the solar system as a whole. One of the more highly prized concentrator collectors survived the crash almost completely intact. The Genesis Concentrator was designed to concentrate the solar wind by a factor of at least 20 so that solar oxygen and nitrogen isotopes could be measured. One of these materials was the Diamond-on-Silicon (DoS) concentrator target. Unfortunately, the DoS concentrator broke on impact. Nevertheless, the scientific value of the DoS concentrator target was high. The Genesis Allocation Committee received a request for approximately 1 cm(sup 2) of the DoS specimen taken near the focal point of the concentrator for the analysis of solar wind nitrogen isotopes. The largest fragment, Genesis sample 60000, was designated for this allocation and needed to be precisely cut. The requirement was to subdivide the designated sample in a manner that prevented contamination of the sample and minimized the risk of losing or breaking the precious requested sample fragment. The Genesis curator determined that the use of laser scribing techniques to "cut" a precise line and subsequently cleave the sample (in a controlled break of the sample along that line) was the best method for accomplishing the sample subdivision. However, there were risks, including excess heating of the sample, that could cause some of the implanted solar wind to be lost via thermal diffusion. Accidentally breaking the sample during the handling and cleaving process was an additional risk. Early in fiscal year 2013, to address this delicate, complicated task, the ARES Directorate assembled its top scientists to develop a cutting plan that would ensure success when applied to the actual concentrator target wafer; i.e., to produce an approximately 1 cm(sup 2) piece from the requested area of the wafer. The team, subsequently referred to as the JSC Genesis Tiger Team, spent months researching and testing parameters and techniques related to scribing, cleaving, transporting, handling, and holding (i.e., mounting) the specimen. The investigation required considerable "thinking outside the box," and many, many trials using nonflight wafer analogs. After all preliminary testing, the following method was adopted as the final cutting plan. It was used in two final end-to-end practice runs before being used on the actual flight target wafer. The wafer was oriented on the laser cutting stage with the 100 and 010 directions of the wafer parallel to the corresponding X and Y directions of the cutting stage. The laser was programed to scribe 31 lines of the appropriate length along the Y stage direction. The programed scribe lines were separated by 5 micron in the X direction. The laser parameters were set as follows: (1) The laser power was 0.5 watts; (2) each line consisted of 50 passes, with the Z position being advanced 5 micron per pass; and (3) 30 s would elapse before the next line was scribed to allow for wafer cool down from any possible heating via the laser. The ablated material that "stuck" in the "scribe-cut" was removed from the "cut" using an ultrasonic micro-tool. After all the ablated silicon was removed from the wafer, the wafer was repositioned in exactly the same orientation on the laser stage. The laser was focused using the bottom of the wafer channel, and the 31-line scribing pattern described above was reprogrammed using the Z position of the groove bottom as the starting Z value instead of the top wafer surface, which was used previously. Upon completion of the second set of scribes, the ultrasonic micro-tool was again used to clean out the cut. The wafer was remounted on the stage in exactly the same orientation as before. The laser was again focused on the bottom of the groove. This time, however, the laser was.programed to scribe only one line down the exact center of the channel. The final scribe line consisted of 100 passes with a Z advance of 5 micron per pass and with the laser power set at 0.5 watts. As mentioned above, the final cutting plan was practiced in two end-to-end trials using non-flight, triangular-shaped silicon wafers similar in size and orientation to the actual DOS 60000 target sample. The actual scribing of the triangular-shaped wafers required scribing two lines and cleaving (i.e. scribe-cleave, then scribe-cleave) to obtain the piece requested for allocation. Early in December 2012, after many months of experiments and practicing and perfecting the techniques and procedures, the team successfully subdivided the Genesis DoS 60000 target sample, one of the most scientifically important samples from the Genesis mission (figure 2). On December 17, 2012, the allocated piece of concentrator target sample was delivered to the requesting principal investigator.The cutting plan developed for the subdivision of this sample will be used as the model for subdividing future requested Genesis flight wafers (appropriately modified for different wafer types).

Lauer, H. V., Jr.↗