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NASA NTRS1990

Hybrid Propulsion Technology Program

Future launch systems of the United States will require improvements in booster safety, reliability, and cost. In order to increase payload capabilities, performance improvements are also desirable. The hybrid rocket motor (HRM) offers the potential for improvements in all of these areas. The designs are presented for two sizes of hybrid boosters, a large 4.57 m (180 in.) diameter booster duplicating the Advanced Solid Rocket Motor (ASRM) vacuum thrust-time profile and smaller 2.44 m (96 in.), one-quater thrust level booster. The large booster would be used in tandem, while eight small boosters would be used to achieve the same total thrust. These preliminary designs were generated as part of the NASA Hybrid Propulsion Technology Program. This program is the first phase of an eventual three-phaes program culminating in the demonstration of a large subscale engine. The initial trade and sizing studies resulted in preferred motor diameters, operating pressures, nozzle geometry, and fuel grain systems for both the large and small boosters. The data were then used for specific performance predictions in terms of payload and the definition and selection of the requirements for the major components: the oxidizer feed system, nozzle, and thrust vector system. All of the parametric studies were performed using realistic fuel regression models based upon specific experimental data.

Jensen, G. E.↗

NASA NTRS1991

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Kirlik, Alex↗

NASA NTRS1996

Crew Selection and Training

This research addressed a number of issues relevant to the performance of teams in demanding environments. Initial work, conducted in the aviation analog environment, focused on developing new measures of performance related attitudes and behaviors. The attitude measures were used to assess acceptance of concepts related to effective teamwork and personal capabilities under stress. The behavioral measures were used to evaluate the effectiveness of flight crews operating in commercial aviation. Assessment of team issues in aviation led further to the evaluation and development of training to enhance team performance. Much of the work addressed evaluation of the effectiveness of such training, which has become known as Crew Resource Management (CRM). A second line of investigation was into personality characteristics that predict performance in challenging environments such as aviation and space. A third line of investigation of team performance grew out of the study of flight crews in different organizations. This led to the development of a theoretical model of crew performance that included not only individual attributes such as personality and ability, but also organizational and national culture. A final line of investigation involved beginning to assess whether the methodologies and measures developed for the aviation analog could be applied to another domain -- the performance of medical teams working in the operating room.

Helmreich, Robert L.↗

NASA NTRS2019

Characterization of a Photon Counting Test Bed for Space to Ground Optical Pulse Position Modulation Communications Links

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) has developed a laboratory transmitter and receiver prototype of a space-to-ground optical communications link. The system is meant to emulate future deep space optical communication links, such as the first crewed flight of Orion, in which the transmitted laser is modulated using pulse position modulation and the receiver is capable of detecting single photons. The transmitter prototype consists of a software defined radio, a high extinction ratio electro-optic modulator system, and a 1550 nm laser. The receiver is a scalable concept and utilizes a single-pixel array of fiber coupled superconducting nanowire single photon detectors. The transmit and receive waveforms follow the Consultative Committee for Space Data Systems (CCSDS) Optical Communications Coding and Synchronization Standard. A software model of the optical transmitter and receiver has also been implemented to predict performance of the optical test bed. This paper describes the transmitter and receiver prototypes as well as the system test configuration. System level tests results are presented and shown to align with predictions from software simulations. The validated software model can be used to in the future to reduce the design cycle of optical communications systems.

software defined radio↗

DOE OSTI2020

Transition Core Planning and Safety Analyses in Support of LEU Fuel Conversion of the University of Missouri Research Reactor (MURR)

The University of Missouri Research Reactor (MURR®) is one of six U.S. High Performance Research Reactors (USHPRR), including one critical facility, that is working with the National Nuclear Security Administration (NNSA) Office of Material Management and Minimization (M3) Reactor Conversion Program to convert from highly enriched uranium (HEU) to low-enriched uranium (LEU) fuel. The M3 Reactor Conversion USHPRR Project objectives include the development of LEU fuel element designs that will ensure safe reactor operations and to maintain the existing experimental performance of each facility. The work is being conducted through many inter-related activities being completed by four Project Pillars: Fuel Qualification (FQ), Fuel Fabrication (FF), Reactor Conversion (RC), and Cross Cutting (CC). A new type of LEU fuel based on an alloy of uranium-10 wt% molybdenum (U-10Mo) is expected to allow the conversion of those USHPRR, like MURR, requiring higher density fuels. The very-high-density LEU U-10Mo monolithic fuel is currently undergoing irradiation testing and post-irradiation examination under a planned and documented fuel qualification effort. The FQ Pillar will document fuel property and fuel performance data and qualify the fuel for use in these reactors. The FF Pillar is fabricating fuel for ongoing and future irradiation tests, as well as conducting fabrication demonstrations to validate or update preliminary fabrication assumptions. The FF Pillar is also working to develop and install commercial manufacturing capacity with the U-10Mo monolithic fuel to produce prototypic fuel. Working with the RC Pillar at Argonne, MURR has progressed through a preliminary fuel element design using preliminary data for the proposed monolithic alloy of U-10Mo. Analyses were completed in previous work that found for typical equilibrium operations with the preliminary LEU fuel element design, in conjunction with a power uprate to 12 MW and appropriate changes to the MURR Limiting safety system settings (LSSS), MURR will have adequate margins to safety for steady-state operations and postulated transient accidents and will have experimental performance in key locations that meets or exceeds current operations with HEU fuel. The purpose of this work is to develop a sequence of transition cycles that will enable MURR to transition from operation with the reactor core loaded with fresh LEU fuel elements only to typical equilibrium operations with mixed-burnup cores following conversion while meeting operational requirements on safety and experimental performance. It is expected that the use of fresh LEU fuel at conversion and subsequent low burnup of the LEU fuel elements that will initially be available for use following conversion will result in critical control blade positions that will substantially change the axial power distribution in the core and the neutron flux available in key experimental locations relative to equilibrium LEU operations. Given the constraints of MURR safety margins, operational practices, and production and research, a novel method has been developed to identify a transition sequence that minimizes the time MURR operates atypically compared to the current prototypic cycles using HEU fuel. The proposed transition sequence moves quickly to the same sort of equilibrium cycles for the LEU fuel that have already been evaluated in documented preliminary safety analyses. Although shifting the neutron flux peak to the lower half of the core during initial cycles with LEU at 12 MW reduces the experiment performance in some key locations relative to current HEU operations at 10 MW, all LEU cores provide an average performance that meets or exceeds that of HEU. An LEU cycle is reached that meets or exceeds the level of experimental performance predicted for current HEU and equilibrium LEU operations in more than 450 key locations identified by a reactor specialist at MURR by the 23rd cycle following conversion and that afterwards will enable MURR to consistently meet its experimental performance requirements. The proposed transition sequence only requires the fabrication of 34 fresh LEU elements in the first year of operation and does not exceed the anticipated availability of fresh elements that can be produced by the fuel fabricator. By the third year after conversion, 22 fresh LEU elements will be required each year, which is the same as expected for equilibrium LEU operations and the same as current operations with HEU fuel. The proposed transition sequence thus combines a relatively short time period before equilibrium burnup is achieved, a temporary increase of fuel elements needed annually relative to typical operations that are within the production capabilities of the fuel fabricator, and demonstrates comparable experimental performance of the LEU cores relative to current HEU operations. Further measures may be taken to reduce any initial experimental performance penalty even further, where possible, by repositioning certain experiments to leverage the increased performance in the lower axial experimental positions in the initial cycles following conversion or leaving the experiments in the irradiation facilities longer in order to achieve the required neutron fluence. This analysis may require refinement depending on the experimental facilities in use at the time of conversion. Nonetheless, the results presented here, including the experimental performance, core burnup, and critical control blade positions throughout the transition cycles, show that the proposed transition cycle fuel management patterns are consistent with what is expected and desired for MURR operation with LEU U-10Mo fuel. Detailed core power distributions from the neutronics models were also used to evaluate safety margins during steady-state operations for the selected transition cycles and the equilibrium LEU core. It is shown that there are adequate safety margins for both steady-state operations and postulated accident scenarios. For the steady-state operations with the preliminary LEU fuel element design the analysis predicts at least 2.49 MW margin to the onset of flow instability at the LSSS power of 15 MW. Considering the LSSS power is 125% of full license power, the margin to OFI is sufficient. In addition, the critical heat flux ratio at LSSS power is well above the requirement of CHFR > 2.0 from NUREG-1537 for all considered cases. For postulated transient accidents, the minimum margin to the fuel temperature safety limit is at least 109 °C. In summary, the proposed sequence of core loadings for MURR operations following conversion to LEU fuel and a power uprate to 12 MW provides sufficient safety margins for both steady-state operations and postulated transient accidents during a proposed sequence of transition cycles to equilibrium operations. Analysis has shown that there are some local experimental performance penalties during the initial cycles. Although there are local shifts in the experimental performance, on average all LEU cores at 12 MW have equal or higher performance than HEU at 10 MW. Temporary adjustments are being planned that will produce suitable experimental performance during these cycles. The results indicate that for the equilibrium LEU core the experimental performance exceeds that of current HEU operations in all key locations while also demonstrating sufficient safety margins.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1994

Computational prediction of isolated performance of an axisymmetric nozzle at Mach number 0.90

An improved ability to predict external propulsive performance was incorporated into the three-dimensional Navier-Stokes code PAB3D. The improvements are the ability to account for skin friction and external pressure forces. Performance parameters for two axisymmetric supersonic cruise nozzle configurations were calculated to test the improved methodology. Internal and external flow-field regions were computed using a two-equation kappa-epsilon turbulent viscous-stress model. The computed thrust-minus-drag ratios were within 1 percent of the absolute level of experimental data and the trends of data were predicted accurately. The predicted trend of integrated nozzle pressure drag matched the trend of the integrated experimental pressure drag over a range of nozzle pressure ratios, but absolute drag levels were not accurately predicted.

Carlson, John R.↗

NASA NTRS2017

Comprehensive Analysis Modeling of Small-Scale UAS Rotors

Multicopter unmanned aircraft systems (UAS), or drones, have continued their explosive growth in recent years. With this growth comes demand for increased performance as the limits of existing technologies are reached. In order to better design multicopter UAS aircraft, better performance prediction tools are needed. This paper presents the results of a study aimed at using the rotorcraft comprehensive analysis code CAMRAD II to model a multicopter UAS rotor in hover. Parametric studies were performed to determine the level of fidelity needed in the analysis code inputs to achieve results that match test data. Overall, the results show that CAMRAD II is well suited to model small-scale UAS rotors in hover. This paper presents the results of the parametric studies as well as recommendations for the application of comprehensive analysis codes to multicopter UAS rotors.

Analysis↗

NASA NTRSDate not supplied

Environment Adversarial Reinforcement Learning

This paper presents a training method for increasing performance of reinforcement learning agents. The method is named Environment Adversarial Reinforcement Learning. The method requires the reinforcement learning environment to be parameterizeable. Over the course of training, environment parameters are updated in a direction of increasing difficulty for the agent. The direction for these updates is found using a performance prediction network trained on data from tests of the agent under varying environment parameters. The method was tested on a CartPole environment. A 28-58\% improvement in mean return was found when comparing performance to a baseline reinforcement learning algorithm on both easy and hard versions of the task.

machine learning↗

DOE OSTI2020

Hybrid deep learning architecture for general disruption prediction across tokamaks

In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer from existing devices to new ones, thereby predicting disruptions using very limited disruptive data from the new devices. Here, the explorative data analysis conducted via unsupervised clustering techniques confirms that time-sequence data are much better separators of disruptive and non-disruptive behavior than the instantaneous plasma state data with further advantageous implications for a sequence-based predictor. Based on such important findings, we have designed a new algorithm for multi-machine disruption prediction that achieves high predictive accuracy on the C-Mod (AUC=0.801), DIII-D (AUC=0.947) and EAST (AUC=0.973) tokamaks with limited hyperparameter tuning. Through numerical experiments, we show that boosted accuracy (AUC=0.959) is achieved on EAST predictions by including in the training only 20 disruptive discharges, thousands of non-disruptive discharges from EAST, and combining this with more than a thousand discharges from DIII-D and C-Mod. The improvement of predictive ability obtained by combining disruptive data from other devices is found to be true for all permutations of the three devices. Furthermore, by comparing the predictive performance of each individual numerical experiment, we find that non-disruptive data are machine-specific while disruptive data from multiple devices contain device-independent knowledge that can be used to inform predictions for disruptions occurring on a new device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Hybrid deep learning architecture for general disruption prediction across tokamaks

In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer from existing devices to new ones, thereby predicting disruptions using very limited disruptive data from the new devices. The explorative data analysis conducted via unsupervised clustering techniques confirms that time-sequence data are much better separators of disruptive and non-disruptive behavior than the instantaneous plasma state data with further advantageous implications for a sequence-based predictor. Based on such important findings, we have designed a new algorithm for multi-machine disruption prediction that achieves high predictive accuracy on the C-Mod (AUC=0.801), DIII-D (AUC=0.947) and EAST (AUC=0.973). tokamaks with limited hyperparameter tuning. Through numerical experiments, we show that boosted accuracy (AUC=0.959) is achieved on EAST predictions by including in the training only 20 disruptive discharges, thousands of non-disruptive discharges from EAST, and combining this with more than a thousand discharges from DIII-D and C-Mod. The improvement of predictive ability obtained by combining disruptive data from other devices is found to be true for all permutations of the three devices. Furthermore, by comparing the predictive performance of each individual numerical experiment, we find that non-disruptive data are machine-specific while disruptive data from multiple devices contain device-independent knowledge that can be used to inform predictions for disruptions occurring on a new device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1999

Smagglce: Surface Modeling and Grid Generation for Iced Airfoils: Phase 1 Results

SmaggIce (Surface Modeling and Grid Generation for Iced Airfoils) is a software toolkit used in the process of aerodynamic performance prediction of iced airfoils with grid-based Computational Fluid Dynamics (CFD). It includes tools for data probing, boundary smoothing, domain decomposition, and structured grid generation and refinement. SmaggIce provides the underlying computations to perform these functions, a GUI (Graphical User Interface) to control and interact with those functions, and graphical displays of results, it is being developed at NASA Glenn Research Center. This paper discusses the overall design of SmaggIce as well as what has been implemented in Phase 1. Phase 1 results provide two types of software tools: interactive ice shape probing and interactive ice shape control. The ice shape probing tools will provide aircraft icing engineers and scientists with an interactive means to measure the physical characteristics of ice shapes. On the other hand, the ice shape control features of SmaggIce will allow engineers to examine input geometry data, correct or modify any deficiencies in the geometry, and perform controlled systematic smoothing to a level that will make the CFD process manageable.

Vickerman, Mary B.↗

NASA NTRS2008

Optical Performance Modeling for NASA's James Webb Space Telescope

Optical performance modeling for NASA's James Webb Space Telescope is discussed. Alignment drifts, line-of-sight image motion, wavefront sensing, and detector noise are considered in a single model environment for evaluating the predicted performance of the observatory. Parametric sensitivity analyses are performed, and examples presented.

Howard, Joseph M.↗

NASA NTRS2009

Sheet Membrane Spacesuit Water Membrane Evaporator Thermal Test

For future lunar extravehicular activities (EVA), one method under consideration for rejecting crew and electronics heat involves evaporating water through a hydrophobic, porous Teflon(Registered Trademark) membrane. A Spacesuit Water Membrane Evaporator (SWME) prototype using this membrane was successfully tested by Ungar and Thomas (2001) with predicted performance matching test data well. The above referenced work laid the foundation for the design of a compact sheet membrane SWME development unit for use in the Constellation System Spacesuit Element Portable Life Support System (Vogel and et. al., ICES 2008). Major design objectives included minimizing mass, volume, and manufacturing complexity while rejecting a minimum of 810 watts of heat from water flowing through the SWME at 91 kg/hr with an inlet temperature of 291K. The design meeting these objectives consisted of three concentric cylindrical water channels interlaced with four water vapor channels. Two units were manufactured for the purpose of investigating manufacturing techniques and performing thermal testing. The extensive thermal test measured SWME heat rejection as a function of water inlet temperatures, water flow-rates, water absolute pressures, water impurities, and water vapor back-pressures. This paper presents the test results and subsequent analysis, which includes a comparison of SWME heat rejection measurements to pretest predictions. In addition, test measurements were taken such that an analysis of the commercial-off-the-shelf vapor pressure control valve could be performed.

Trevino, Luis A.↗

NASA NTRS1989

Near-field testing of the 15-meter hoop-column antenna

A 15-m-diameter antenna was tested to verify that dimensional tolerances for acceptable performance could be achieved and to verify structural, electromagnetic, and mechanical performance predictions. This antenna utilized the hoop column structure, a gold plated molybdenum mesh reflector, and 96 control cables to adjust the reflector conformance with a paraboloid. The dimensional conformance of the antenna structure and surface was measured with metric camera and theodolites. Near field pattern data were used to assess the electromagnetic performance at five frequencies from 2.225 to 11.6 GHz. The reflector surface was adjusted to greatly improve electromagnetic performance with a finite element model and the surface measurements. Measurement results show that antenna surface figure and adjustments and electromagnetic patterns agree well with predictions.

Schroeder, Lyle C.↗

NASA NTRS1986

Living in contained environments: Research implications from undersea habitats

A cost-reward model is used to frame a discussion of differences in observed behavior of individuals and groups in confined environments. It has been observed that the high cost of functioning in a stressful environment is likely to produce poor performance when anticipated rewards are low but that participants can manage the stress and achieve high performance if they anticipate high rewards. The high-reward environment is exemplified by early undersea habitats such as Sealab and Tektite and by early space missions. Other aspects of behavior occur in all confined environments and point to an important area for future research. Of particular interest are intergroup conflicts arising between the confined group and its external control. Also, individual differences in personality seem always to have an impact in confined environments. Recent research has focused on: (1) predicting performance and adjustment based on instrumental and expressive aspects of the self; (2) the differential predictive power of achievement striving and irritation/irritability in Type A personalities; and (3) the nature and role of leadership in small, isolated groups.

Helmreich, Robert L.↗

NASA NTRS2004

COMSAC: Computational Methods for Stability and Control

The unprecedented advances being made in computational fluid dynamic (CFD) technology have demonstrated the powerful capabilities of codes in applications to civil and military aircraft. Used in conjunction with wind-tunnel and flight investigations, many codes are now routinely used by designers in diverse applications such as aerodynamic performance predictions and propulsion integration. Typically, these codes are most reliable for attached, steady, and predominantly turbulent flows. As a result of increasing reliability and confidence in CFD, wind-tunnel testing for some new configurations has been substantially reduced in key areas, such as wing trade studies for mission performance guarantees. Interest is now growing in the application of computational methods to other critical design challenges. One of the most important disciplinary elements for civil and military aircraft is prediction of stability and control characteristics. CFD offers the potential for significantly increasing the basic understanding, prediction, and control of flow phenomena associated with requirements for satisfactory aircraft handling characteristics.

Fremaux, C. Michael↗

DOE OSTI2022

Longitudinal Trajectories of Memory Performance in Patients with Early-Stage Breast Cancer

Background. While breast cancer and its treatments may affect cognition, the longitudinal trajectories of cognition among those receiving differing cancer treatment types remain poorly understood. Prior research suggests hippocampal-prefrontal cortex network integrity may influence cognition, although how this network predicts performance over time remains unclear. Methods. We conducted a prospective trial including 69 patients with early-stage breast cancer receiving adjuvant therapy and 12 controls. Longitudinal cognitive testing was conducted at four visits: pretreatment-baseline, 6-7 months, 14-15 months, and 23-24 months. Cognitive composite scores of episodic memory, executive functioning, and processing speed were assessed at each timepoint. Baseline structural MRI was obtained in a subset of these participants, and hippocampal and prefrontal cortex regional volumes were extracted. Results. Longitudinal linear mixed modeling revealed significant group by time interactions on memory performance, controlling for age and education. Post hoc analyses revealed this effect was driven by patients treated with chemotherapy or chemotherapy plus hormone therapy, who demonstrated the least improvement in memory scores over time. Treatment group did not significantly influence the relationship between time and processing speed or executive functioning. Neither pretreatment hippocampal nor prefrontal volume differed between groups, and there were no significant group by time by baseline regional volume effects on cognition. Conclusion. Patients with early-stage breast cancer treated with chemotherapy or chemotherapy plus hormone therapy benefit less from practice effects seen in healthy controls on memory tests. Loss of longitudinal practice effect may be a new and clinically relevant measure for capturing patients’ experience of cognitive difficulties after treatment.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1972

Main tank injection pressurization program

Computer program predicts performance of fluorine-hydrogen main tank injection pressurization system for full range of liquid-hydrogen-fueled space vehicles. Analytical model includes provisions for heat transfer, injectant jet penetration, and ullage gas mixing. Analysis predicts GF2 usage, ullage gas and tank wall temperatures, and LH2 evaporation.

Cady, E. C.↗