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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 865 records · Page 48

Ozone profiling from backscattered UV radiance measurements A new procedure

This paper presents a data analysis technique that has been developed to support a stratospheric ozone measurement and profiling program. The data consist of solar backscattered UV radiation monitored by a spacecraft. The output consists of ozone mixing ratio profiles complete with error bars throughout the atmosphere. The technique is based upon principles of nonlinear optimal estimation. It provides a number of desirable features that have not been available together in any previously constructed technique for the problem. Iteration on both radiation measurements and total ozone measurements is among these features.

Whitney, C. K.↗

MHD channel performance for potential early commercial MHD power plants

The commercial viability of full and part load early commercial MHD power plants is examined. The load conditions comprise a mass flow of 472 kg/sec in the channel, Rosebud coal, 34% by volume oxygen in the oxidizer preheated to 922 K, and a one percent by mass seeding with K. The full load condition is discussed in terms of a combined cycle plant with optimized electrical output by the MHD channel. Various electrical load parameters, pressure ratios, and magnetic field profiles are considered for a baseload MHD generator, with a finding that a decelerating flow rate yields slightly higher electrical output than a constant flow rate. Nominal and part load conditions are explored, with a reduced gas mass flow rate and an enriched oxygen content. An enthalpy extraction of 24.6% and an isentropic efficiency of 74.2% is predicted for nominal operation of a 526 MWe MHD generator, with higher efficiencies for part load operation.

Swallom, D. W.↗

A comprehensive method for preliminary design optimization of axial gas turbine stages

A method is presented that performs a rapid, reasonably accurate preliminary pitchline optimization of axial gas turbine annular flowpath geometry, as well as an initial estimate of blade profile shapes, given only a minimum of thermodynamic cycle requirements. No geometric parameters need be specified. The following preliminary design data are determined: (1) the optimum flowpath geometry, within mechanical stress limits; (2) initial estimates of cascade blade shapes; (3) predictions of expected turbine performance. The method uses an inverse calculation technique whereby blade profiles are generated by designing channels to yield a specified velocity distribution on the two walls. Velocity distributions are then used to calculate the cascade loss parameters. Calculated blade shapes are used primarily to determine whether the assumed velocity loadings are physically realistic. Model verification is accomplished by comparison of predicted turbine geometry and performance with four existing single stage turbines.

Jenkins, R. M.↗

An improved computer model for prediction of axial gas turbine performance losses

The calculation model performs a rapid preliminary pitchline optimization of axial gas turbine annular flowpath geometry, as well as an initial estimate of blade profile shapes, given only a minimum of thermodynamic cycle requirements. No geometric parameters need be specified. The following preliminary design data are determined: (1) the optimum flowpath geometry, within mechanical stress limits; (2) initial estimates of cascade blade shapes; and (3) predictions of expected turbine performance. The model uses an inverse calculation technique whereby blade profiles are generated by designing channels to yield a specified velocity distribution on the two walls. Velocity distributions are then used to calculate the cascade loss parameters. Calculated blade shapes are used primarily to determine whether the assumed velocity loadings are physically realistic. Model verification is accomplished by comparison of predicted turbine geometry and performance with an array of seven NASA single-stage axial gas turbine configurations.

Jenkins, R. M.↗

Stimulated Raman shifting of the Nd:YAG fourth harmonic (266 nm) in H2, HD, and D2

The dependence of the first Stokes stimulated Raman conversion efficiency of fourth-harmonic radiation from a Nd:YAG laser at 266 nm has been studied for the isotopic species H2, HD, and D2 as a function of gas pressure and laser energy using a low numerical aperture (about 0.0045) pumping geometry. While the laser energy threshold for first Stokes conversion varies significantly among the species, photon conversion efficiencies of at least 50 percent can be achieved for all of them for laser pump energies at 266 nm of 50 mJ/pulse or less. This study provides a new measurement of the differential cross section for stimulated Raman scattering in HD of 8.1 + or - 2.4 x 10 to the -29th sq cm/sr at 266 nm and at high pressures, and agreement is found with previous measurements of the cross sections for H2 and D2. The results have been used to optimize the laser transmitter system for a differential-absorption lidar to measure tropospheric ozone concentration profiles.

Haner, David A.↗

An investigation of bleed configurations and their effect on shock wave/boundary layer interactions

The design of high efficiency supersonic inlets is a complex task involving the optimization of a number of performance parameters such as pressure recovery, spillage, drag, and exit distortion profile, over the flight Mach number range. Computational techniques must be capable of accurately simulating the physics of shock/boundary layer interactions, secondary corner flows, flow separation, and bleed if they are to be useful in the design. In particular, bleed and flow separation, play an important role in inlet unstart, and the associated pressure oscillations. Numerical simulations were conducted to investigate some of the basic physical phenomena associated with bleed in oblique shock wave boundary layer interactions that affect the inlet performance.

Hamed, Awatef↗

A Study of Upgraded Phenolic Curing for RSRM Nozzle Rings

A thermochemical cure model for predicting temperature and degree of cure profiles in curing phenolic parts was developed, validated and refined over several years. The model supports optimization of cure cycles and allows input of properties based upon the types of material and the process by which these materials are used to make nozzle components. The model has been refined to use sophisticated computer graphics to demonstrate the changes in temperature and degree of cure during the curing process. The effort discussed in the paper will be the conversion from an outdated solid modeling input program and SINDA analysis code to an integrated solid modeling and analysis package (I-DEAS solid model and TMG). Also discussed will be the incorporation of updated material properties obtained during full scale curing tests into the cure models and the results for all the Reusable Solid Rocket Motor (RSRM) nozzle rings.

Smartt, Ziba↗

Multi-Window Controllers for Autonomous Space Systems

Multi-window controllers select between elementary linear controllers using nonlinear windows based on the amplitude and frequency content of the feedback error. The controllers are relatively simple to implement and perform much better than linear controllers. The commanders for such controllers only order the destination point and are freed from generating the command time-profiles. The robotic missions rely heavily on the tasks of acquisition and tracking. For autonomous and optimal control of the spacecraft, the control bandwidth must be larger while the feedback can (and, therefore, must) be reduced.. Combining linear compensators via multi-window nonlinear summer guarantees minimum phase character of the combined transfer function. It is shown that the solution may require using several parallel branches and windows. Several examples of multi-window nonlinear controller applications are presented.

Lurie, B, J.↗

Evolution and Impact of Saturn V on Space Launch System from a Guidance, Navigation, and Mission Analysis Perspective

The Saturn V launch vehicle represented a jump in capability for heavy lift launch vehicles, enabling the Lunar Orbit Rendezvous approach to planetary exploration employed by the Apollo program 50 years ago. Following Apollo, and the development of the Space Transportation System, the NASA space exploration program shifted focus from lunar exploration to long-term, sustained, re-usable access to Low Earth Orbit. With the recent focus of NASA on the Artemis program and continued exploration of cislunar space as a precursor to Martian exploration, the shift has swung back to heavy lift capability. To meet this need, NASA has developed the Space Launch System. While the vehicle is a new design, it is heavily influenced by the engineering solutions and approach used on the Saturn V while taking advantage of the state of the art of launch vehicle design. The approach to abort, for example, shares many familiarities with the triggers and concept of operations used on Saturn V. Analysis approaches to dispersed trajectory performance are also very similar, but advances in computing technology have enabled a much more expanded set of inputs that can be modelled and assessed in a rapid manner. Additionally, guided flight algorithms share similar first principles but have expanded to include day of launch wind information. Trajectory optimization has also advanced significantly due to the availability of computing resources, but similar maneuvers and profiles are flown across both vehicles. Also, while the approach of onboard inertial navigation has been maintained between the two programs, the shift from platform to strapdown systems enables reduced complexity in the system design while maintaining required performance. As described, the Space Launch System is the evolution of NASA launch vehicle designs, owing a large heritage to the Saturn vehicle program and incorporating advances in propulsion systems, avionics, computing, and sensor technology over the past 50 years.

Ahmad, Naeem↗

The Integrated Medical Model: A Risk Assessment and Decision Support Tool for Space Flight Medical Systems

The Integrated Medical Model (IMM) is a decision support tool that is useful to mission planners and medical system designers in assessing risks and designing medical systems for space flight missions. The IMM provides an evidence based approach for optimizing medical resources and minimizing risks within space flight operational constraints. The mathematical relationships among mission and crew profiles, medical condition incidence data, in-flight medical resources, potential crew functional impairments, and clinical end-states are established to determine probable mission outcomes. Stochastic computational methods are used to forecast probability distributions of crew health and medical resource utilization, as well as estimates of medical evacuation and loss of crew life. The IMM has been used in support of the International Space Station (ISS) medical kit redesign, the medical component of the ISS Probabilistic Risk Assessment, and the development of the Constellation Medical Conditions List. The IMM also will be used to refine medical requirements for the Constellation program. The IMM outputs for ISS and Constellation design reference missions will be presented to demonstrate the potential of the IMM in assessing risks, planning missions, and designing medical systems. The implementation of the IMM verification and validation plan will be reviewed. Additional planned capabilities of the IMM, including optimization techniques and the inclusion of a mission timeline, will be discussed. Given the space flight constraints of mass, volume, and crew medical training, the IMM is a valuable risk assessment and decision support tool for medical system design and mission planning.

Kerstman, Eric↗

Computational Process Modeling for Additive Manufacturing

Computational Process and Material Modeling of Powder Bed additive manufacturing of IN 718. Optimize material build parameters with reduced time and cost through modeling. Increase understanding of build properties. Increase reliability of builds. Decrease time to adoption of process for critical hardware. Potential to decrease post-build heat treatments. Conduct single-track and coupon builds at various build parameters. Record build parameter information and QM Meltpool data. Refine Applied Optimization powder bed AM process model using data. Report thermal modeling results. Conduct metallography of build samples. Calibrate STK models using metallography findings. Run STK models using AO thermal profiles and report STK modeling results. Validate modeling with additional build. Photodiode Intensity measurements highly linear with power input. Melt Pool Intensity highly correlated to Melt Pool Size. Melt Pool size and intensity increase with power. Applied Optimization will use data to develop powder bed additive manufacturing process model.

Bagg, Stacey↗

BuildingIQ Technology Field Validation

This document describes a field validation and verification of the BuildingIQ Predictive Energy Optimization (PEO) technology based on a five-site study. BuildingIQ describes its PEO technology as a software-as-a-service (SaaS) platform that optimizes commercial building HVAC control for system efficiency, occupant comfort, and cost. It is targeted for use in large, complex buildings, and integrates with the building automation system (BAS) to conduct supervisory control. The PEO algorithm defines optimal space air temperature setpoints that are automatically implemented at the variable air volume (VAV) terminal units when possible, or through supply air temperature and duct static pressure setpoints at the air handling unit (AHU) level. The optimization is built upon a learned predictive model that provides a 24-hour ahead forecast of the building’s power profile, using weather forecasts and historical operational data; this model is updated every 4 to 6 hours. Demand-responsive load reductions may also be implemented.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Charge Management for an Inductively Charged On-Demand Battery-Electric Shuttle Service with High Penetration of Renewable Energy

This paper presents a charge management control strategy for an on-demand battery-electric shuttle van operating at the National Renewable Energy Laboratory (NREL) campus and supported by day-time inductive charging at the vehicle's waiting spot. A new control algorithm has been proposed for reducing the demand charge costs incurred from wireless charging of the on-demand shuttle. A custom controller has been developed to monitor the shuttle, wireless charger, renewable energy generation, and various loads at NREL's campus, and regulate charging behavior for demand response. The intermittent renewable generation and sporadic operation of the on-demand shuttle service contribute to a high level of uncertainty in expected campus load profile, which must be carefully managed. The control algorithm predicts energy profile to estimate the mobility needs of the vehicle and maintain uninterrupted service during operation while still minimizing peak demand. The proposed controller has been designed and optimized using a Simulink model for the entire system. Next, it has been implemented and tested in real-time on the NREL campus. Two primary vehicle-use cases, charge sustaining and charge depletion operation, are tested under different load profiles and drive cycles to assess the controller's effectiveness at reducing peak demand and therefore demand charges. The proposed controller showed robust performance under different driving scenarios with high correlation between simulated and experimental data. The results showed that proper demand response can be achieved with an average of 94% reduction of charging loads during peak demand events.

ADVANCED PROPULSION SYSTEMS,ENERGY STORAGE↗

A Contextually Supervised Optimization-Based HVAC Load Disaggregation Methodology

This paper presents a novel contextually supervised optimization-based approach for disaggregating heating, ventilation, and air-conditioning (HVAC) loads using smart meter or Supervisory Control and Data Acquisition data. To disaggregate the load into HVAC loads, large and infrequently used loads (LIUL), and base loads, we formulate an optimization problem to minimize a set of five loss terms, consisting of the reconstruction errors of the overall load profile, the ramp rate losses, and three distinct loss functions linked with the HVAC load, base load, and LIUL, respectively. To enhance accuracy, we incorporate two forms of contextual information into the problem formulation. First, we utilize mutual information to estimate HVAC energy consumption. Second, we employ a base load dictionary to constrain HVAC load estimation errors. The obtained HVAC load profiles are fine-tuned by abnormal ramp detection followed by binary hypothesis testing. Here, the proposed method is developed and tested using sub-metered residential and commercial building data. Simulation results show that the proposed method outperforms existing methods across various data resolutions and load aggregation levels, showing excellent transferability and generalizability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Two-well injector direct-phonon terahertz quantum cascade lasers

We present an experimental study on a terahertz quantum cascade laser (THz QCL) design that combines both two-well injector and direct-phonon scattering schemes, i.e., a so-called two-well injector direct-phonon design. As a result of the two-well injector direct-phonon scheme presented here, the lasers benefit from both a direct phonon scattering scheme for the lower laser level depopulation and a setback for the doping profile that reduces the overlap of the doped region with active laser states. Additionally, our design also has efficient isolation of the active laser levels from excited and continuum states as indicated by negative differential resistance behavior all the way up to room temperature. This scheme serves as a good platform for improving the temperature performance of THz QCLs as indicated by the encouraging temperature performance results of the device with a relatively high doping level of 7.56 × 10 10 cm −2 and T max ∼ 167 K. With the right optimization of the molecular beam epitaxy growth and interface quality, the injection coupling strength, and the doping density and its profile, the device could potentially reach higher temperatures than the latest records reached for the maximum operating temperature (T max ) of THz QCLs.

47 OTHER INSTRUMENTATION↗

Overcoming Metastable CO 2 Adsorption in a Bulky Diamine-Appended Metal-Organic Framework

We report carbon capture at fossil fuel-fired power plants is a critical strategy to mitigate anthropogenic contributions to global warming, but widespread deployment of this technology is hindered by a lack of energy-efficient materials that can be optimized for CO 2 capture from a specific flue gas. As a result of their tunable, step-shaped CO 2 adsorption profiles, diamine-functionalized metal-organic frameworks (MOFs) of the form diamine-Mg 2 (dobpdc) (dobpdc 4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) are among the most promising materials for carbon capture applications. Here, we present a detailed investigation of dmen-Mg 2 (dobpdc) (dmen = 1,2-diamino-2-methylpropane), one of only two MOFs with an adsorption step near the optimal pressure for CO 2 capture from coal flue gas. While prior characterization suggested that this material only adsorbs CO 2 to half capacity (0.5 CO 2 per diamine) at 1 bar, we show that the half-capacity state is actually a metastable intermediate. Under appropriate conditions, the MOF adsorbs CO 2 to full capacity, but conversion from the half-capacity structure happens on a very slow time scale, rendering it inaccessible in traditional adsorption measurements. Data from solid-state magic angle spinning nuclear magnetic resonance spectroscopy, coupled with van der Waals-corrected density functional theory, indicate that ammonium carbamate chains formed at half capacity and full capacity adopt opposing configurations, and the need to convert between these states likely dictates the sluggish post-half-capacity uptake. By use of the more symmetric parent framework Mg 2 (pc-dobpdc) (pc-dobpdc 4- = 3,3'-dioxidobiphenyl-4,4'-dicarboxylate), the metastable trap can be avoided and the full CO 2 capacity of dmen-Mg 2 (pc-dobpdc) accessed under conditions relevant for carbon capture from coal-fired power plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reinforcement Learning Applied to Cognitive Space Communications

The future of space exploration depends on robust, reliable communication systems. As the number of such communication systems increase, automation is fast becoming a requirement to achieve this goal. A reinforcement learning solution can be employed as a possible automation method for such systems. The goal of this study is to build a reinforcement learning algorithm which optimizes data throughput of a single actor. A training environment was created to simulate a link within the NASA Space Communication and Navigation (SCaN) infrastructure, using state of the art simulation tools developed by the SCaN Center for Engineering, Networks, Integration, and Communications (SCENIC) laboratory at NASA Glenn Research Center to obtain the closest possible representation of the real operating environment. Reinforcement learning was then used to train an agent inside this environment to maximize data throughput. The simulation environment contained a single actor in low earth orbit capable of communicating with twenty-five ground stations that compose the Near-Earth Network (NEN). Initial experiments showed promising training results, so additional complexity was added by augmenting simulation data with link fading profiles obtained from real communication events with the International Space Station. A grid search was performed to find the optimal hyperparameters and model architecture for the agent. Using the results of the grid search, an agent was trained on the augmented training data. Testing shows that the agent performs well inside the training environment and can be used as a foundation for future studies with added complexity and eventually tested in the real space environment.

Schubert, Carson D.↗

Optimization of Second Fault Detection Thresholds to Maximize Mission Probability of Success

In order to support manned spaceflight safety requirements, the Space Launch System (SLS) has defined program-level requirements for key systems to ensure successful operation under single fault conditions. The SLS program has also levied requirements relating to the capability of the Inertial Navigation System to detect a second fault. This detection functionality is required in order to feed abort analysis and ensure crew safety. Increases in navigation state error due to sensor faults in a purely inertial system can drive the vehicle outside of its operational as-designed environmental and performance envelope. As this performance outside of first fault detections is defined and controlled at the vehicle level, it allows for the use of system level margins to increase probability of mission success on the operational edges of the design. A top-down approach is utilized to assess vehicle sensitivity to second sensor faults. A wide range of failure scenarios in terms of both fault magnitude and time is used for assessment. The approach also utilizes a schedule to change fault detection thresholds autonomously. These individual values are optimized along a nominal trajectory in order to maximize probability of mission success in terms of system-level insertion requirements while minimizing the probability of false positives. This paper will describe an approach integrating Genetic Algorithms and Monte Carlo analysis to tune the threshold parameters to maximize vehicle resilience to second fault events over an ascent mission profile. The analysis approach and performance assessment and verification will be presented to demonstrate the applicability of this approach to second fault detection optimization to maximize mission probability of success through taking advantage of existing margin.

Anzalone, Evan J.↗