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NASA NTRS2003

Microgravity Effects on Materials Processing: A Review

Materials processing in space has been studied both theoretically and experimentally for over 1/4 of a century. In the beginning, we naively spoke of zero gravity, elimination of convection, growth of perfect crystals, and eventual manufacturing in space. All of these appear to have fallen by the wayside. On the other hand, we have learned an unprecedented amount about the influences of gravity on materials processing. We have had many surprises, and not all experimental results have yet been satisfactorily explained. Gravity was found to influence processes that were thought to be gravity-independent. One consequence is that materials processing on earth has often been improved. And it is difficult to imagine how the materials-processing industries could have flourished without the engineers and scientists who received their training by working on microgravity materials processing.

Wilcox, William R.↗

NASA NTRS1977

Experimental program for the operational study of data collection platforms in Bolivia

The system developed for the SMS/GOES satellite while learning the limitations possessed by this system with regard to the LANDSAT 1 and 2 satellites with respect to the transmission distance and horizon angle is investigated. The advantages possessed by this system in comparison with conventional methods are evaluated so as to permit studying the feasibility of introducing it into this country in the near future.

Source record↗

NASA NTRS1984

Predictions of Cockpit Simulator Experimental Outcome Using System Models

This study involved predicting the outcome of a cockpit simulator experiment where pilots used cockpit displays of traffic information (CDTI) to establish and maintain in-trail spacing behind a lead aircraft during approach. The experiments were run on the NASA Ames Research Center multicab cockpit simulator facility. Prior to the experiments, a mathematical model of the pilot/aircraft/CDTI flight system was developed which included relative in-trail and vertical dynamics between aircraft in the approach string. This model was used to construct a digital simulation of the string dynamics including response to initial position errors. The model was then used to predict the outcome of the in-trail following cockpit simulator experiments. Outcome included performance and sensitivity to different separation criteria. The experimental results were then used to evaluate the model and its prediction accuracy. Lessons learned in this modeling and prediction study are noted.

Sorensen, J. A.↗

NASA NTRS2011

Lessons Learned from CFD Validation Study of Protuberance Heating

The objectives of this presentation are: (1) Share lessons learned from a recent exercise in CFD validation of protuberance heating (2) Impact of experimental data reduction assumptions and techniques on validation activity (3) Advanced data reduction techniques may provide useful data from non-typical test methods (4) Significance of the recovery factor for high-speed flows (5) Show typical results of the Lag turbulence model on protuberances (6) Introduce and inform the listener of a protuberance heating dataset which will soon be available for comparison

Oliver, Brandon↗

NASA NTRS2012

A Systematic Approach for Real-Time Operator Functional State Assessment

A task overload condition often leads to high stress for an operator, causing performance degradation and possibly disastrous consequences. Just as dangerous, with automated flight systems, an operator may experience a task underload condition (during the en-route flight phase, for example), becoming easily bored and finding it difficult to maintain sustained attention. When an unexpected event occurs, either internal or external to the automated system, the disengaged operator may neglect, misunderstand, or respond slowly/inappropriately to the situation. In this paper, we discuss an approach for Operator Functional State (OFS) monitoring in a typical aviation environment. A systematic ground truth finding procedure has been designed based on subjective evaluations, performance measures, and strong physiological indicators. The derived OFS ground truth is continuous in time compared to a very sparse estimation of OFS based on an expert review or subjective evaluations. It can capture the variations of OFS during a mission to better guide through the training process of the OFS assessment model. Furthermore, an OFS assessment model framework based on advanced machine learning techniques was designed and the systematic approach was then verified and validated with experimental data collected in a high fidelity Boeing 737 simulator. Preliminary results show highly accurate engagement/disengagement detection making it suitable for real-time applications to assess pilot engagement.

Zhang, Guangfan↗

NASA NTRS1993

Lift-fan aircraft: Lessons learned-the pilot's perspective

This paper is written from an engineering test pilot's point of view. Its purpose is to present lift-fan 'lessons learned' from the perspective of first-hand experience accumulated during the period 1962 through 1988 while flight testing vertical/short take-off and landing (V/STOL) experimental aircraft and evaluating piloted engineering simulations of promising V/STOL concepts. Specifically, the scope of the discussions to follow is primarily based upon a critical review of the writer's personal accounts of 30 hours of XV-5A/B and 2 hours of X-14A flight testing as well as a limited simulator evaluation of the Grumman Design 755 lift-fan aircraft. Opinions of other test pilots who flew these aircraft and the aircraft simulator are also included and supplement the writer's comments. Furthermore, the lessons learned are presented from the perspective of the writer's flying experience: 10,000 hours in 100 fixed- and rotary-wing aircraft including 330 hours in 5 experimental V/STOL research aircraft. The paper is organized to present to the reader a clear picture of lift-fan lessons learned from three distinct points of view in order to facilitate application of the lesson principles to future designs. Lessons learned are first discussed with respect to case histories of specific flight and simulator investigations. These principles are then organized and restated with respect to four selected design criteria categories in Appendix I. Lastly, Appendix Il is a discussion of the design of a hypothetical supersonic short take-off vertical landing (STOVL) fighter/attack aircraft.

Gerdes, Ronald M.↗

NASA NTRS2006

Robust Coordination for Large Sets of Simple Rovers

The ability to coordinate sets of rovers in an unknown environment is critical to the long-term success of many of NASA;s exploration missions. Such coordination policies must have the ability to adapt in unmodeled or partially modeled domains and must be robust against environmental noise and rover failures. In addition such coordination policies must accommodate a large number of rovers, without excessive and burdensome hand-tuning. In this paper we present a distributed coordination method that addresses these issues in the domain of controlling a set of simple rovers. The application of these methods allows reliable and efficient robotic exploration in dangerous, dynamic, and previously unexplored domains. Most control policies for space missions are directly programmed by engineers or created through the use of planning tools, and are appropriate for single rover missions or missions requiring the coordination of a small number of rovers. Such methods typically require significant amounts of domain knowledge, and are difficult to scale to large numbers of rovers. The method described in this article aims to address cases where a large number of rovers need to coordinate to solve a complex time dependent problem in a noisy environment. In this approach, each rover decomposes a global utility, representing the overall goal of the system, into rover-specific utilities that properly assign credit to the rover s actions. Each rover then has the responsibility to create a control policy that maximizes its own rover-specific utility. We show a method of creating rover-utilities that are "aligned" with the global utility, such that when the rovers maximize their own utility, they also maximize the global utility. In addition we show that our method creates rover-utilities that allow the rovers to create their control policies quickly and reliably. Our distributed learning method allows large sets rovers be used unmodeled domains, while providing robustness against rover failures and changing environments. In experimental simulations we show that our method scales well with large numbers of rovers in addition to being robust against noisy sensor inputs and noisy servo control. The results show that our method is able to scale to large numbers of rovers and achieves up to 400% performance improvement over standard machine learning methods.

Tumer, Kagan↗

NASA NTRS2019

Shockwave/Boundary-Layer Interaction Studies Performed in the NASA Langley 20-Inch Mach 6 Air Tunnel

This paper highlights results from a collaborative study performed by The University of Tennessee Space Institute (UTSI) and NASA Langley Research Center on the Shockwave/Boundary-Layer Interaction (SWBLI) generated by a cylindrical protuberance on a flat plate in a Mach 6 flow. The study was performed in the 20-Inch Mach 6 Air Tunnel at NASA Langley Research Center and consisted of two separate entries. In the first entry, simultaneous high-speed schlieren and high-speed pressure-sensitive paint (PSP) imaging – which was performed for the first time in the 20-Inch Mach 6 facility at NASA Langley – were performed as well as simultaneous high-speed schlieren and oil-flow imaging. In the second entry, the model configuration was modified to increase the size of the interaction region. High-speed schlieren and infrared thermography (IR) surface imaging were performed in this second entry. The goal of these tests was to characterize the SBLI in the presence of a laminar, transitional, and turbulent boundary layer using high-speed optical imaging techniques. AoA = sting angle-of-attack (°) dcylinder = cylinder diameter (mm) dtrip = cylindrical tripping element diameter (mm) Δshock = shock stand-off distance (mm) hcylinder = cylinder height (mm) htrip = cylindrical tripping element height (mm) HSS = high-speed schlieren M∞ = freestream Mach number PSP = pressure-sensitive paint Re∞ = freestream unit Reynolds number (m-1) SWBLI = shockwave/boundary-layer interaction θplate = model plate angle (°) Introduction his paper highlights two experimental entries performed in the 20-Inch Mach 6 Air Blowdown Tunnel at NASA Langley Research Center in collaboration with The University of Tennessee Space Institute (UTSI). The purpose of these entries was to characterize the dynamic shockwave/boundary-layer interaction (SWBLI) between a vertical cylinder on a flat plate and laminar, transitional (XSWBLI), and turbulent (SWTBLI) boundary layers with a freestream Mach number of 6 using non-intrusive optical diagnostics. Experiments performed by Murphree et al.1,2 were among the first to specifically characterize XSWBLI induced by a vertical cylinder on a flat plate geometry using several optical measurement techniques. Recent optical studies of XSWBLI phenomenon have been performed by UTSI at Mach 2 in their low-enthalpy blow wind tunnel3-8 and by Texas A&M University and UTSI at Mach numbers of 6 and 7 in their Adjustable Contour Expansion wind tunnel.9 The experiments described in this paper were intended to complement previous studies by expanding the freestream unit Reynolds number range, Re∞, over which the XSWBLI phenomena has been observed. Additionally these experiments, made possible under NASA’s new facility funding model under the Aeronautics Evaluation and Test Capabilities (AETC) project, promoted collaboration between university and NASA researchers. The initial entry in the 20-Inch Mach 6 Air Tunnel at NASA Langley occurred in December of 2016. Originally, testing was to occur in November of 2016 in the 31-Inch Mach 10 Air Tunnel at NASA Langley. This facility was chosen so that the XSWBLI phenomenon could be observed at much higher Mach numbers than had previously been attempted in ground test experiments. The model selected for this experiment, a 10° half-angle wedge with a sharp leading edge (described in detail in section II.B), had previously been used by Danehy et al. [10] for boundary layer transition studies using the nitric oxide planar laser-induced fluorescence (NO PLIF) flow visualization technique. In that work, it was determined that transition could be induced downstream of a single htrip = 1-mm tall, dtrip = 4-mm diameter cylindrical tripping element and that the streamwise location of the transition could be changed for a single Re∞ by changing the model angle-of-attack (AoA) (see Fig. A3 in Ref. [10] for more details). Based on the findings of that work, a decision was made to use the wedge model with the cylindrical tripping element to trip the boundary layer flow ahead of a cylindrical protuberance in order to achieve a XSWBLI. Unfortunately, the 31-Inch Mach 10 facility had been taken offline for repairs in October of 2016 and a decision was made to move the test to the 20-Inch Mach 6 facility. Since the behavior of the boundary layer with the chosen model configuration had not been studied before in that facility and the available test time was limited, the entry was considered to be exploratory and was used to collect spatially-resolved and time-resolved flow and surface visualization data that would be used to inform a second entry. Test techniques included simultaneous high-speed schlieren (HSS) captured at 160 kHz and high-speed pressure sensitive paint captured at 10 kHz as well as oil flow visualization, captured at 750 Hz. The second entry in the 20-Inch Mach 6 facility occurred in June and July of 2017. In this follow-on test, modifications to the wind tunnel model were made based on observations made during the first entry and included removing the cylindrical tripping element, increasing the size of the cylinder used to induce the SWBLI to increase the size of the interaction while simultaneously improving spatial resolution, and using a swept ramp array, similar to that described in Ref. [11], to trip the flow to turbulence. Simultaneous HSS (captured at 140 kHz, 100 kHz, and 40 kHz) and conventional IR thermography (captured at 30 Hz) imaging were performed simultaneously in this follow-on entry. This paper is intended to serve as a summary of the work performed during these two entries, to detail lessons learned from each entry, and to highlight some of the datasets acquired. Details on the experimental setup, model configuration, and techniques used are provided. Papers providing a more rigorous analysis of data acquired during the second entry, including statistical, spectral, and modal decomposition methods, can be found in Refs. [12,13]. An entry examining XSWBLI in the 31-Inch Mach 10 Blowdown Wind Tunnel facility is currently planned for mid-to-late calendar year 2019, pending the success of facility repairs. The work performed and described in this paper and the upcoming entry in the 31-Inch Mach 10 facility at NASA Langley have been made possible by NASA’s new facility funding model under the Aeronautics Evaluation and Test Capabilities (AETC) project. Wind Tunnel Facility All experiments discussed in this paper were performed in the 20-Inch Mach 6 Air Tunnel at NASA Langley Research Center. Specific details pertaining to this facility can be found in Refs. [14,15], with only a brief description of the facility provided here. For both entries, the nominal freestream unit Reynolds number was varied between 1.8×106 m-1 (0.5×106 ft-1) and 26.3×106 m-1 (8×106 ft-1). The nominal stagnation pressure was varied between 0.21 MPa and 3.33 MPa and the nominal stagnation temperature was varied between 480 K and 520 K to achieve the desired Re∞ condition. For all runs, the nominal freestream Mach number was 6. The nearly square test section is 520.7-mm (20.5-inches) wide by 508-mm (20-inches) high. Two 431.8-mm (17-inch) diameter windows made of Corning 7940, Grade 5F schlieren-quality glass serve as the side walls of the tunnel and provide optical access for the high-speed schlieren measurements. A rectangular window made of the same material as the side windows served as the top wall of the test section and provided optical access for the high-speed PSP and oil flow measurements. For the second entry, this top window was replaced with a Zinc Selenide (ZnSe) window with an anti-reflection coating capable of passing IR wavelengths between 8μm and 12μm with greater than 98% transmittance. The model was sting supported by a strut attached to a hydraulic system that allows for the model pitch angle to be adjusted between -5° to +55°. For the first entry, an initial pitch/pause sweep of the model AoA was performed to observe the resulting SWBLI. Ultimately, however, the sting pitch angle for this entry was fixed at +10.0° so that the angle of the top surface of the wedge relative to the streamwise axis of the tunnel (referred to herein as the plate angle, θplate), was θplate = 0°. For the second entry, θplate = 0° and θplate = -13.25° were initially tested with the swept ramp array (discussed in the following section) to determine which orientation produced conditions most favorable for XSWBLI to occur based on the heating signatures observed over the top surface of the model in the IR thermography images. Based on these initial tests, θplate = -13.25° was set for the remainder of the runs in the second entry. For both entries, any model changes were performed in a housing located beneath the closed test section. Prior to performing a run of the tunnel, the housing was sealed and the tunnel started. Once the appropriate freestream conditions were achieved, the model was injected into the test section using a hydraulic injection system. B. Model Geometry For all runs, a 10° half-angle (20° full-angle) wedge model with a sharp leading edge was used. The model is described in detail in Refs. [10,16]. The top surface of the sharp leading edge of the model extended 47.8 mm from its upstream-most edge to a junction with the upstream edge of a stainless steel top plate that then extended an (a) (c) (b) Fig. 1 (a) Schematic of top surface of wedge model with gas seeding insert, (b) perspective view of the model in the 20-Inch Mach 6 tunnel with centerline pressure orifices on sharp leading edge, and (c) a perspective view of the model with stainless steel (top) and SLA middle insert (bottom) during the first entry. Flow occurs from left to right.

Bathel, Brett F.↗

NASA NTRSDate not supplied

Artificial Neural Networks to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

INTRODUCTION We use artificial neural networks (ANNs) as an example machine learning (ML) tool to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is attentional set-shifting (ATSET) test scores from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 28Si, or 56Fe, expected for a Lunar or Mars mission [1]. This work investigates rats at a subject-based level and uses applied dose and performance scores taken before irradiation to predict whether a rat will be impaired when irradiated. The results of this study are significant to crewed space missions as they support the potential of predicting an astronaut’s impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. METHODS Data used in this work are scores from the ATSET, a multi-stage constrained cognitive flexibility test [2]. Our computational model utilizes the number of attempts to reach the criterion to pass a stage as a behavioral performance measure for rats. We use the post-irradiation scores, generate thresholds from cumulative distribution plots of non-irradiated rats, and calculate the percent of irradiated rats whose scores fall below the threshold to infer how each radiation type/dose affects a population. Rats scoring above the threshold are labeled impaired while the others are non-impaired. We then employ ANNs as a typical ML technique, and use each subject’s individual scores taken before radiation along with the applied dose, to predict their personal susceptibility to cognitive impairment due to space radiation exposure. RESULTS AND CONCLUSION A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing ML classifiers such as ANNs identifies rats that have a higher tendency for impairment after GCR exposure [1]. The receiver operating characteristic (ROC) and the precision-recall (PR) curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD (Figure 1) and CD stages. They, however, do not depict impairment due to 4He in SD (Figure 1) and 28Si in CD, suggesting no dose-dependent impairment response in these cases. In this work, “good” prediction pertains to “better-than-random-chance”, due to the limited sample size and the high inter- and intra-individual variabilities in response to brain stimulation paradigms, as applicable to both animals and humans. More behavioral tests and biomarkers should be investigated on the same subjects, to be fed to the ML models to capture the agents responsible for performance alterations of some individuals versus others.

machine learning↗

NASA NTRSDate not supplied

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation

machine learning↗

NASA NTRS2008

Automated Assume-Guarantee Reasoning by Abstraction Refinement

Current automated approaches for compositional model checking in the assume-guarantee style are based on learning of assumptions as deterministic automata. We propose an alternative approach based on abstraction refinement. Our new method computes the assumptions for the assume-guarantee rules as conservative and not necessarily deterministic abstractions of some of the components, and refines those abstractions using counter-examples obtained from model checking them together with the other components. Our approach also exploits the alphabets of the interfaces between components and performs iterative refinement of those alphabets as well as of the abstractions. We show experimentally that our preliminary implementation of the proposed alternative achieves similar or better performance than a previous learning-based implementation.

Pasareanu, Corina S.↗

NASA NTRS1988

The space station assembly phase: System design trade-offs for the flight telerobotic servicer

The effects of a recent study aimed at identifying key issues and trade-offs associated with using a Flight Telerobotic Servicer (FTS) to aid in Space Station assembly-phase tasks is described. The use of automation and robotic (A and R) technologies for large space systems often involves a substitution of automation capabilities for human EVA or IVA activities. A methodology is presented that incorporates assessment of candidate assembly-phase tasks, telerobotic performance capabilities, development costs, and effects of operational constaints. Changes in the region of cost-effectiveness are examined under a variety of system design assumptions. A discussion of issues is presented with focus on three roles the FTS might serve: as a research-oriented test bed to learn more about space usage of telerobotics; as a research based test bed having an experimental demonstration orientation with limited assembly and servicing applications; or as an operational system to augment EVA and to aid construction of the Space Station and to reduce the program (schedule) risk by increasing the flexibility of mission operations.

Smith, Jeffrey H.↗

NASA NTRS1988

A methodology for automation and robotics evaluation applied to the space station telerobotic servicer

The efforts of a recent study aimed at identifying key issues and trade-offs associated with using a Flight Telerobotic Servicer (FTS) to aid in Space Station assembly-phase tasks is described. The use of automation and robotic (A and R) technologies for large space systems would involve a substitution of automation capabilities for human extravehicular or intravehicular activities (EVA, IVA). A methodology is presented that incorporates assessment of candidate assembly-phase tasks, telerobotic performance capabilities, development costs, and effect of operational constraints (space transportation system (STS), attached payload, and proximity operations). Changes in the region of cost-effectiveness are examined under a variety of systems design assumptions. A discussion of issues is presented with focus on three roles the FTS might serve: (1) as a research-oriented testbed to learn more about space usage of telerobotics; (2) as a research based testbed having an experimental demonstration orientation with limited assembly and servicing applications; or (3) as an operational system to augment EVA and to aid the construction of the Space Station and to reduce the programmatic (schedule) risk by increasing the flexibility of mission operations.

Smith, Jeffrey H.↗

NASA NTRS1990

Learning-based position control of a closed-kinematic chain robot end-effector

A trajectory control scheme whose design is based on learning theory, for a six-degree-of-freedom (DOF) robot end-effector built to study robotic assembly of NASA hardwares in space is presented. The control scheme consists of two control systems: the feedback control system and the learning control system. The feedback control system is designed using the concept of linearization about a selected operating point, and the method of pole placement so that the closed-loop linearized system is stabilized. The learning control scheme consisting of PD-type learning controllers, provides additional inputs to improve the end-effector performance after each trial. Experimental studies performed on a 2 DOF end-effector built at CUA, for three tracking cases show that actual trajectories approach desired trajectories as the number of trials increases. The tracking errors are substantially reduced after only five trials.

Nguyen, Charles C.↗

NASA NTRSDate not supplied

Combustor-Turbine Interactions By Using the Open National Combustion Code (OpenNCC) and the Glenn-HT Code

We develop the methodology of coupling two different computational fluid dynamic (CFD) codes, OpenNCC and Glenn-HT, in order to investigate the unsteady flow fields inside the combustor and around the first-stage stator of a high-pressure turbine (HPT) from the energy efficient engine (E 3 ) program. In our coupling strategy, OpenNCC, a time accurate unstructured mesh multi-phase combustion CFD code, is applied to the combustor region and Glenn-HT, a structured mesh CFD code designed for turbine applications, is utilized inside the HPT region. As a proof of concept, we first simulate the three-dimensional airflow over the backward facing step and compared the predicted pressure coefficient against experimental data. We then considered a Jet-A/Air combustor with the NASA single learn direct injector (LDI) as a reacting flow test case. Here, Glenn-HT is used in the downstream of the combustor and assumes that the working fluid is a single gas (i.e., air) where the properties of the gas are taken from time- and area-averaged values at the combustor exit. A fully coupled combustor-turbine simulation using both OpenNCC and Glenn-HT was conducted on the E 3 combustor and a detailed analysis done pertaining to how a realistic combustor outflow affects migration of hot-streaks and its impact on the aerodynamic behavior inside the HPT. It is found that the combustion dynamics (i.e., the switching main and pilot flame strength) significantly alters the aerodynamic behavior inside the HPT including hot-streak migration. Variations of the temperature and the velocity magnitude in the passage could be up to ±75 and ±15. These large variations are an important part of the combustor-turbine interactions, which are overlooked by a single component simulation of the HPT while imposing the steady inflow boundary condition at the HPT inlet. Finally, it is observed the strong density gradient associated with the hot-streaks and the pressure gradient at the passage significantly enhances the baroclinic torque, affecting the vorticity field.

CFD hot-streaks↗

NASA NTRSDate not supplied

Flow Boiling and Condensation Experiment (FBCE): Latest Findings from the Summary ISS Experiments

Since 2011, researchers from Purdue University and NASA Glenn Research Center (GRC) have been collaborating to investigate the effects of gravity on several aspects of flow boiling and flow condensation. This massive research endeavor, termed the Flow Boiling and Condensation Experiment (FBCE), has culminated in development of NASA’s largest and most complex facility for investigation of two-phase fluid physics onboard the ISS. FBCE consists of two separate studies: flow boiling, using the Flow Boiling Module (FBM), and flow condensation, using the Condensation Module for Heat Transfer Measurements (CM-HT); the FBM experiments have already been completed while the condensation experiments began in 2024. This presentation will summarize mostly new results from the flow boiling experiments, with a focus on analysis of pressure drop and two-phase flow instabilities in microgravity using both experimental data and video records from the ISS experiments, as well as development of machine learning models. These new predictive tools are part of the arsenal of predictive methods developed by the Purdue-Glenn team for design of future space systems.

Microgravity↗

NASA NTRS2017

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Gentry, Diana↗

NASA NTRS1977

Voice technology and BBN

The following research was discussed: (1) speech signal processing; (2) automatic speech recognition; (3) continuous speech understanding; (4) speaker recognition; (5) speech compression; (6) subjective and objective evaluation of speech communication system; (7) measurement of the intelligibility and quality of speech when degraded by noise or other masking stimuli; (8) speech synthesis; (9) instructional aids for second-language learning and for training of the deaf; and (10) investigation of speech correlates of psychological stress. Experimental psychology, control systems, and human factors engineering, which are often relevant to the proper design and operation of speech systems are described.

Wolf, Jared J.↗