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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 451 records · Page 25

Science Issues Associated with the Use of a Microfluidic Chip Designed Specifically for Protein Crystallization

The Iterative Biological Crystallization team in partnership with Caliper Technologies has produced a prototype microfluidic chip for batch crystallization that has been designed and tested. The chip is designed for the mixing and dispensing of up to five solutions with possible variation of the recipe being delivered to two growth wells. Developments that have led to the successful on-chip crystallization of a few model proteins have required investigative insight into many different areas, including fluid mixing dynamics, surface treatments, quantification and fidelity of reagent delivery. This presentation will encompass the ongoing studies and data accumulated toward these efforts.

Holmes, Anna M.↗

Aerocapture navigation at Neptune

A proposed Neptune orbiter Aerocapture mission will use solar electric propulsion to send an orbiter to Neptune. Navigation feasibility of direct-entry aerocapture for orbit insertion at Neptune is shown. The navigation strategy baselines optical imaging and (delta)VLBI measurement in order to satisfy the flight system's atmosphere entry flight path angle, which is targeted to enter Neptune with an entry flight path angle of -11.6 . Error bars on the entry flight path angle of plus/minus0.55 (3(sigma)) are proposed. This requirement can be satisfied with a data cutoff 3.2 days prior to arrival. There is some margin in the arrival template to tighten (i.e. reduce) the entry corridor either by scheduling a data cutoff closer to Neptune or alternatively, reducing uncertainties by increasing the fidelity of the optical navigation camera.

interplanetary navigation↗

Implementation of In-Situ Impedance Techniques on a Full Scale Aero-Engine System

Determination of acoustic liner impedance for jet engine applications remains a challenge for the designer. Although suitable models have been developed that take account of source amplitude and the local flow environment experienced by the liner, experimental validation of these models has been difficult. This is primarily due to the inability of researchers to faithfully mimic the environment in jet engine nacelles in the laboratory. An in-situ measurement technique, one that can be implemented in an actual engine, is desirable so an accurate impedance can be determined for future modeling and quality control. This paper documents the implementation of such a local acoustic impedance measurement technique that is used under controlled laboratory conditions as well as on full scale turbine engine liner test article. The objective for these series of in-situ measurements is to substantiate treatment design, provide understanding of flow effects on installed liner performance, and provide modeling input for fan noise propagation computations. A series of acoustic liner evaluation tests are performed that includes normal incidence tube, grazing incidence tube, and finally testing on a full scale engine on a static test stand. Lab tests were intended to provide insight and guidance for accurately measuring the impedance of the liner housed in the inlet of a Honeywell Tech7000 turbofan. Results have shown that one can acquire very reasonable liner impedance data for a full scale engine under realistic test conditions. Furthermore, higher fidelity results can be obtained by using a three-microphone coherence technique that can enhance signal-to-noise ratio at high engine power settings. This research has also confirmed the limitations of this particular type of in-situ measurement. This is most evident in the installation of instrumentation and its effect on what is being measured.

Gaeta, R. J.↗

Base Heating Sensitivity Study for a 4-Cluster Rocket Motor Configuration in Supersonic Freestream

In support of launch vehicle base heating and pressure prediction efforts using the Loci-CHEM Navier-Stokes computational fluid dynamics solver, 35 numerical simulations of the NASA TND-1093 wind tunnel test have been modeled and analyzed. This test article is composed of four JP-4/LOX 500 lbf rocket motors exhausting into a Mach 2 - 3.5 wind tunnel at various ambient pressure conditions. These water-cooled motors are attached to a base plate of a standard missile forebody. We explore the base heating profiles for fully coupled finite-rate chemistry simulations, one-way coupled RAMP (Reacting And Multiphase Program using Method of Characteristics)-BLIMPJ (Boundary Layer Integral Matrix Program - Jet Version) derived solutions and variable and constant specific heat ratio frozen flow simulations. Variations in turbulence models, temperature boundary conditions and thermodynamic properties of the plume have been investigated at two ambient pressure conditions: 255 lb/sq ft (simulated low altitude) and 35 lb/sq ft (simulated high altitude). It is observed that the convective base heat flux and base temperature are most sensitive to the nozzle inner wall thermal boundary layer profile which is dependent on the wall temperature, boundary layer s specific energy and chemical reactions. Recovery shock dynamics and afterburning significantly influences convective base heating. Turbulence models and external nozzle wall thermal boundary layer profiles show less sensitivity to base heating characteristics. Base heating rates are validated for the highest fidelity solutions which show an agreement within +/-10% with respect to test data.

Mehta, Manish↗

The Mars Science Laboratory (MSL) MMRTG In-Flight: A Power Update

The MSL Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) was fueled on October 28, 2008 by the Department Of Energy (DOE) in preparation for a late 2009 launch. Shortly after, the MSL launch was delayed approximately 2 years until 2011. The fueled MMRTG was placed in storage to await the new date for liftoff. Occasional measurements of the MMRTG's power output were taken and compared with power predictions that pre-dated fueling. An error in the predictive models was quickly recognized and remedied. The predictions, while improved, carried significant uncertainty. This uncertainty did not deter the launch of MSL, but did alter the planned mission on the surface of Mars. Once launched, the MSL spacecraft provided a hi-fidelity telemetry stream measuring the generator's electrical and thermal performance. These data were used to update the predictive models and a new prediction of the performance of the MMRTG on the surface of Mars was run just before Entry, Descent, and Landing (EDL) at Mars. The MSL MMRTG is working extremely well, providing power above predictions and operating within its flight allowable temperature limits. The generator was producing approximately 114 W at the beginning of the surface mission. This paper will elaborate on power modeling for the MSL MMRTG along with a review of some of the data recorded from the MSL cruise to Mars, EDL, and the early days of the surface mission.

thermoelectric generator↗

The Mars Science Laboratory (MSL) MMRTG In-Flight: A Power Update

The MSL Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) was fueled on October 28, 2008 by the Department Of Energy (DOE) in preparation for a late 2009 launch. Shortly after, the MSL launch was delayed approximately 2 years until 2011. The fueled MMRTG was placed in storage to await the new date for liftoff. Occasional measurements of the MMRTG's power output were taken and compared with power predictions that pre-dated fueling. An error in the predictive models was quickly recognized and remedied. The resultant predictions, while improved, carried significant uncertainty. This uncertainty did not deter the launch of MSL, but did alter the planned mission on the surface of Mars. Once launched, the MSL spacecraft provided a hi-fidelity telemetry stream measuring the generator's electrical and thermal performance. These data were used to update the predictive models and a new prediction of the performance of the MMRTG on the surface of Mars was run just before Entry, Descent, and Landing (EDL) at Mars. The MSL MMRTG is working extremely well, providing power above predictions and operating within its flight allowable temperature limits. The generator was producing approximately 114 W at the beginning of the surface mission. This paper will elaborate on power modeling for the MSL MMRTG along with a review of some of the data recorded from the MSL cruise to Mars, EDL, and the early days of the surface mission.

thermoelectric↗

Landsat 8 Remote Sensing Reflectance (Rrs) Products: Evaluations, Intercomparisons, and Enhancements

The Operational Land Imager (OLI) onboard Landsat-8 is generating high-quality aquatic science products, the most critical of which is the remote sensing reflectance (Rrs), defined as the ratio of water-leaving radiance to the total downwelling irradiance just above water. The quality of the Rrs products has not, however, been extensively assessed. This manuscript provides a comprehensive evaluation of Level-1B, i.e., top of atmosphere reflectance, and Rrs products available from OLI imagery under near-ideal atmospheric conditions in moderately turbid waters. The procedure includes a) evaluations of the Rrs products at sites included in the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), b) intercomparisons and cross-calibrations against other ocean color products, and c) optimizations of vicarious calibration gains across the entire OLI observing swath. Results indicate that the near-infrared and shortwave infrared (NIR-SWIR) band combinations yield the most robust and stable Rrs retrievals in moderately turbid waters. Intercomparisons against products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer onboard the Aqua platform (MODISA) indicate slight across-track non-uniformities (<1%) associated with OLI scenes in the blue bands. In both product domains (TOA and Rrs), on average, the OLI products were found larger in radiometric responses in the blue channels. Following the implementation of updated vicarious calibration gains and accounting for across-track non-uniformities, matchup analyses using independent in-situ validation data confirmed improvements in Rrs products. These findings further support high-fidelity OLI-derived aquatic science products in terms of both demonstrating a robust atmospheric correction method and providing consistent products across OLI's imaging swath.

Pahlevan, Nima↗

Evolving Storage and Cyber Infrastructure at the NASA Center for Climate Simulation

This talk will describe recent developments at the NASA Center for Climate Simulation, which is funded by NASAs Science Mission Directorate, and supports the specialized data storage and computational needs of weather, ocean, and climate researchers, as well as astrophysicists, heliophysicists, and planetary scientists. To meet requirements for higher-resolution, higher-fidelity simulations, the NCCS augments its High Performance Computing (HPC) and storage retrieval environment. As the petabytes of model and observational data grow, the NCCS is broadening data services offerings and deploying and expanding virtualization resources for high performance analytics.

Cyberinfrastructure↗

Integrated System for Autonomous and Adaptive Caretaking (ISAAC): Phase 1 Low-Fidelity Demo

This presentation describes the ISAAC phase 1 low-fidelity demonstration results. The demonstration satisfied the milestone from the Gateway-ISAAC Memorandum of Understanding to "Demonstrate spatial and logical data registration between robotics and spacecraft". It integrated many new ISAAC components, including a spatially linked model, Astrobee multi-sensor mapping, and an integrated data interface. It advanced ISAAC key performance parameters related to mapping, in a lab setting. Areas for phase 1 forward work include: improve maturity toward the high-fidelity demo on the ISS; demonstrate mapping with more sensor modalities; expand initial anomaly detection implementation into a flexible framework with multiple detection algorithms for different tasks; begin open source software release process for releasable ISAAC components.

robotics↗

VSLAM and Coplanar POSIT for Advanced Air Mobility Approach and Landing

Advanced Air Mobility (AAM) aircraft have many challenges for landing accurately and safely in urban, suburban, and rural environments. Localization in large and open rural environments could utilize GPS, but AAM aircraft in urban environments will encounter GPS degradation. Another challenge involves flight operation time, i.e., flying during the day or at night. There are different types of guidelines and landmarks at runways, heliports, and vertiports for daytime and nighttime applications. Tailoring feature detection methods for AAM approach and landing during the day and night pose different issues and challenges. It is easier to detect edges, lines, and other runway markers during the day than at night. Conversely, it is easier to detect landing light configurations and patterns at nighttime than daytime. Consequently, utilizing the same feature detector for daytime and nighttime operations may not be feasible. This paper focuses on vision-based precision approach and landing (PAL) and builds on previous work by comparing ORB SLAM, custom VSLAM, and coplanar pose from orthography and scaling with iterations (POSIT) for daytime and nighttime operations. Implementing high fidelity simulations with computer graphics and extracting video frames from flight test data provide promising results for AAM PAL applications.

Evan Kawamura↗

From Simulation to Reality With Random Noise

The challenging environment of autonomous vehicle (AV) navigation necessitates certain functions be performed by deep neural networks. Optimizing these models involves collecting vast quantities of domain-specific training data and ensuring that the dataset is representative of expected conditions. High-fidelity simulation plays a vital role in making this process feasible, allowing a wide range of scenarios to be explored at low cost. However, learning from simulation introduces subtle biases into models, which can degrade real-world performance in unpredictable ways. This effect can be mitigated with learning schemes specialized to bridge distributional shifts (transfer learning). Given the complex nature of these methods, the underlying models, and their environments, meaningfully evaluating performance is notstraight forward. Many unrelated factors can effect an improvement in generalization accuracy, but a full ablation analysis is often difficult. To tease out signal from noise, it is necessary to understand how transfer learning performance is affected by noise itself. The goals of this paper are (i) to establish a domain randomization baseline for a simple classification transfer learning task and (ii) to validate the RRAV testbed as a platform for further research in sim-to-real learning. We generate imagery from a simulation of NASA Ames Research Center and train a small convolutional neural network (ConvNet) to classify position relative to a centerline. Further models are trained with different types of noise progressively added to the data. The models are deployed aboard the on-site test vehicle to test real-world performance. In our experiments, we find that such naive domain randomization raises sim-to-real accuracy from 64% to 79%, while training directly on real data yields an 89% accuracy ceiling. These results suggest that the isolated mechanism of domain randomization can significantly improve generalization.

simulation↗

Comparing Simulation Results from CHARM and RotCFD to the Multirotor Test Bed Experimental Data

Advanced multirotor vertical flight aircraft concepts are emerging faster than rigorous individualized tests can investigate their utility and performance. There are several analysis tools that predict multirotor performance and flow characteristics, but the accuracy of these predictions is still being debated due to lack of experimental data from multirotor tests that are needed to validate the analyses. The objective of this paper is to simulate multirotor configurations using two different mid-fidelity rotorcraft analysis tools, Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM) and Rotorcraft Computational Fluid Dynamics (RotCFD), and compare the simulation results to experimental data from a wind tunnel test of the Multirotor Test Bed (MTB). The MTB, developed by NASA Ames Research Center, is a new capability for testing a wide array of advanced vertical take-off and landing (VTOL) rotor configurations, with a primary focus on testing in the U.S. Army 7-by 10-Foot Wind Tunnel at NASA Ames Research Center. The MTB was designed to allow adjustment of the vertical, lateral, and longitudinal placement of up to six rotors, as well as allow tilt adjustment of each rotor and pitch adjustment of the whole assembly. The six-axis load cells under each rotor give the MTB the capability of measuring the rotor performance in a wide array of configurations. The overall goal of the MTB project is to help gain a better understanding of the performance, control, interactional aerodynamics, and acoustics of multirotor and tilting-rotor systems. For the work presented here, the MTB data were used to validate RotCFD and CHARM results for several multirotor test configurations. With confidence in both analyses established by the validation exercise, additional simulations were performed to explore quadrotor configurations that will be tested during the MTB’s second wind tunnel entry planned for 2022. This second tunnel entry will examine quadrotor configurations that represent published NASA reference designs for urban air mobility concept vehicles. Results from this paper confirm the ability of RotCFD and CHARM to simulate multirotor aerodynamic interactions on individual rotor performance under edgewise forward-flight conditions.

CHARM↗

Model-Based Systems Engineering, Real-Time Operations, and Autonomy

Model-Based Systems Engineering has been enabled by the development of the SysML language and software tools to create systems models. Systems models described in SysML incorporate frames (Diagrams) that represent behaviors (activities, sequences, state machines, use cases), requirements, and structure (definitions, internal structure, parametric formulation, and packaging). The SysML models are, in turn, used by applications to do analysis and studies of the designs and operational capabilities. These uses of the model are based on simulations, and do not include hardware. This paper presents a software environment and processes that enables more comprehensive systems models for MBSE, and use of these rich models for real-time operations. The paper describes a software platform that enables creation of comprehensive models, beyond what is now possible with SysML and related software tools, called the NASA Platform for Autonomous Systems (NPAS). The platform encapsulates a paradigm and infrastructure for creating systems models with complexity levels comparable to the ones handled by SysML software tools, but with additional fidelity that includes detailed design diagrams encompassing sensors, components, and design topologies. Furthermore, NPAS enables incorporation of data, information, and knowledge (DIaK) to implement autonomy and Integrated System Health Management (ISHM) and the inherent integration of content encompassing SysML structure and behavior diagrams throughout the NPAS modelAnd lastly, the NPAS models are used in real-time operations, taking advantage of the fidelity and complexity encompassed in the models in order to implement “thinking” ISHM and/or autonomous operations. . Incorporation of SysML model content into an NPAS model is briefly discussed.

MBSE↗

Challenges in Qualification of Thermal Protection Systems for Extreme Entry Environments

Planetary entry vehicles employ ablative TPS materials to shield the aeroshell from entry aeroheating environments. To ensure mission success, it must be demonstrated that the heatshield system, including local features such as seams, does not fail at conditions that are suitably margined beyond those expected in flight. Furthermore, its thermal response must be predictable, with acceptable fidelity, by computational tools used in heatshield design. Mission assurance is accomplished through a combination of ground testing and material response modelling. A material's robustness to failure is verified through arcjet testing while its thermal response is predicted by analytical tools that are verified against experimental data. Due to limitations in flight-like ground testing capability and lack of validated high-fidelity computational models, qualification of heatshield materials is often achieved by piecing together evidence from multiple ground tests and analytical simulations, none of which fully bound the flight conditions and vehicle configuration. Extreme heating environments (>2000 W/cm2 heat flux and >2 atm pressure), experienced during entries at Venus, Saturn and Ice Giants, further stretch the current testing and modelling capabilities for applicable TPS materials. Fully-dense Carbon Phenolic was the material of choice for these applications; however, since heritage raw materials are no longer available, future uses of re-created Carbon Phenolic will require re-qualification. To address this sustainability challenge, NASA is developing a new dual-layer material based on 3D weaving technology called Heatshield for Extreme Entry Environments (HEEET) [1]. Regardless of TPS material, extreme environments pose additional certification challenges beyond what has been typical in recent NASA missions.Scope of this presentation: This presentation will give an overview of challenges faced in verifying TPS performance at extreme heating conditions.

Mahzari, Milad↗

Validation of Machine Learning Algorithms for Hyperspectral Inversion of Common Water Quality Indicators

The upcoming transition to a diverse suite hyperspectral airborne and orbiting optical sensors will provide an unprecedented opportunity to measure inland water quality characteristics at a fidelity not previously achievable. This presentation will assess prototype deep learning models trained on synthetic hyperspectral data and validated with collocated in-situ measurements. Synthesized data is becoming increasingly popular for use in data-driven approaches to complex problems, and can compliment real data to increase performance on complex and unusual phenomenon, reduce or test bias, and experiment to demonstrate explainability. We will present insights from hyperspectral inversions of Chlorophyl-a, Phycocyanin, and concentration of non-algal particles using selected orbiting and airborne sensors over diverse, optically complex aquatic scenarios. We analyze how various optical water types affect fidelity of results and where improvements can be made as we prototype for globally operational water quality algorithms which can be leveraged by upcoming hyperspectral missions such as the Surface Biology and Geology (SBG) mission.

Surface Biology and Geology (SBG)↗

Airflow Hazard Visualization for Helicopter Pilots: Flight Simulation Study Results

Airflow hazards such as vortices or low level wind shear have been identified as a primary contributing factor in many helicopter accidents. US Navy ships generate airwakes over their decks, creating potentially hazardous conditions for shipboard rotorcraft launch and recovery. Recent sensor developments may enable the delivery of airwake data to the cockpit, where visualizing the hazard data may improve safety and possibly extend ship/helicopter operational envelopes. A prototype flight-deck airflow hazard visualization system was implemented on a high-fidelity rotorcraft flight dynamics simulator. Experienced helicopter pilots, including pilots from all five branches of the military, participated in a usability study of the system. Data was collected both objectively from the simulator and subjectively from post-test questionnaires. Results of the data analysis are presented, demonstrating a reduction in crash rate and other trends that illustrate the potential of airflow hazard visualization to improve flight safety.

Aragon, Cecilia R.↗

High Fidelity Surface Charging and Magnetic Noise Analysis of the Juno Magnetometer

During Earth flyby of NASA’s Juno spacecraft, unexpected noise was observed in magnetometer data. The noise is attributed to surface currents sourced from ionospheric plasma and directed through the magnetometer boom structure by a vxB electric field. Approximate hand calculations under-predicted the severity of the noise by an order of magnitude. In response, a high fidelity analysis was performed to assess confidence in our model and risk to magnetometer science at Jupiter. Combining NASCAP2k with commercial FEA software, and using detailed inputs from a variety of environment models and CAD tools, the observed effect at Earth was replicated with agreement to a factor of 2. Extending the model to the Jovian environment, we predict a signal-to-noise ratio that is more favourable than at Earth and acceptable to magnetometer science.

Chinn, James↗

Practical model reduction for flexible structures

The most accepted methods for developing models of flexible structures for the analysis, design and simulation of control systems are finite element methods and extraction from experimental data. Using either of these methods, models are often produced with modes that do not significantly add to the fidelity of the model. This paper presents techniques for eliminating these modes. Particular attention is paid to multiple-input, multiple-output systems. First, control system models developed for flexible structures, using finite element methods and experimental data, are briefly discussed. the shortcomings of using models with unnecessary and/or residual modes are delineated. Then, two techniques for reducing the order of models are presented; the first is applicable to single-input, single-output systems and the second for multiple-input, multiple-output systems. Finally, both are illustrated using model data from the proposed NASA Shuttle-C.

Mitchell, Jerrel R.↗