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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Control System of Multi-Port Autonomous Reconfigurable Solar Power Plant (MARS) & HIL Platforms for Design

Multi-port autonomous reconfigurable solar power plant (MARS) provides an attractive alternative to connect photovoltaic (PV) and energy storage systems (ESSs) to high-voltage direct current (HVdc) links and high-voltage alternating current (ac) grids. In this paper, a unique hierarchical control system of MARS is proposed and evaluated. To evaluate the control system and associated algorithms in early-stage research of complex architectures like MARS, it is important to develop unique suitable hardware-in-the-loop (HIL) platforms. In this paper, the HIL platforms for MARS to evaluate the performance of the hierarchical control system and the control algorithms implemented are presented. Further, they help with the design process of control systems. The real-time simulation models and algorithms that are utilized for MARS in the HIL platforms are also discussed in the paper. The HIL experiments of the control system of MARS showcase the capability to provide continuity of operation under faults and frequency support to the power grid during loss of generation. They also showcase the stability of the proposed hierarchical control system of MARS.

14 SOLAR ENERGY↗
DOE OSTI2022

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Programmable hydrogels by combining persistent and transient dynamic bonds

Out-of-equilibrium chemistry is currently being applied to polymer systems to mimic the autonomous behavior of biological materials. In this study, hydrogels with self-healing properties were developed that combine persistent crosslinks from dynamic metal-ligand coordination with transient crosslinks from dynamic anhydride bonds. Polymers containing terpyridine ligands and carboxylic acid groups were synthesized and crosslinked with divalent metal ions (Fe 2+ , Ni 2+ , Co 2+ , Zn 2+ , Cu 2+ ). The coordination bonds from terpyridine–metal coordination impart persistent stability, while transient anhydrides formed on treatment with 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) temporarily increase crosslink density. Distinct behaviors are observed depending on the choice of metal, with Ni 2+ forming robust, stable networks; Zn 2+ creating moderately dynamic gels; and Cu 2+ yielding highly dynamic, soft materials. Treatment with EDC increased storage moduli significantly, with transient effects lasting up to 280 min depending on the metal ion. Self-healing experiments demonstrated independent contributions from metal coordination and transient anhydrides, enabling recovery of stress and strain under varying conditions. Additionally, complex and reversible 2D stiffness patterns were generated by spatially controlled EDC treatment of Zn 2+ and Cu 2+ hydrogel films, demonstrating programmability and reusability.

Rajawasam, Chamoni W. H. [Miami University, Oxford↗
DOE OSTI2025

Integrating Machine-learning-assisted Computer Vision with RICH System

Developments in artificial intelligence have vastly expanded the capabilities of robots. Currently, the Spallation Neutron Source (SNS) beamlines at Oak Ridge National Lab (ORNL) have robotic sample loaders to increase the efficiency of running experiments. However, they require retraining if anything about the situation changes, e.g., where the samples are, and cannot notice if errors occur. So, the viability of using computer vision and machine learning to enhance these sample loaders’ functionality was investigated. In this project, the RICH system with a Dobot CR3 6-axis robot present at the VULCAN beamline assisted by an Intel Realsense D435i camera, a unique camera that enables convenient translation of 2D pixel coordinates to 3D world points, was programmed to load ceramic crucibles into a thermogravimetric analyzer (TGA) furnace. An algorithm was constructed in Python with three major phases planned: (1) obtaining a sample, (2) moving it to the target location, and then (3) bringing the sample back to its original location once the experiment finished. In the first phase, the algorithm would dynamically detect sample locations using ArUco markers to recognize the samples’ general location and a custom-trained yolov5 object detection model to locate the crucibles’ centers. Afterward, the robot would be directed to pick up samples based on the crucibles’ calculated positions. In the second phase, the robot would move the sample to a secondary point, reorient its grip, and place the sample at the target location. In the final phase, the robot would determine whether the sample was intact and would bring it back to its original place if it was or raise an alarm. Using this algorithm, the robot was able to pick up different types of crucibles at varying positions. These results indicate that integrating machine-learning-assisted computer vision with robotic sample loaders can result in effective autonomous detection of samples.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Detecting Volcanic Co2 Emissions Hidden in Tropical Volcanic Forests Using Fixed-Wing sUAS

CO2 emissions are among the earliest indicators of subsurface state change and reactivation of volcanic systems and these deep signals reflect in faint diffuse emissions variations on volcanic flanks. Monitoring vast areas of rainforests covering tropical volcanoes is challenging, and space-borne sensors like OCO-2 are not sensitive enough. Fortunately, trees exposed to mild enhancements of CO2 may experience fertilization and build excess CO2 into excess biomass (Cawse-Nicholson, et al. 2018, Biogeosciences). They also process excess CO2 through photosynthesis, measurable by fluorescence (Bogue et al., 2019, Biogeosciences). Furthermore, spaceborne remote sensing instruments have demonstrated increasing NDVI months to years before eruptions, unexplained by other factors (e.g., Houlie et al. 2006, EPSL; Seiler et al. 2017, PLoS One). By providing a means to map large areas of above-canopy CO2 variations over tropical rainforest on the flanks of actively degassing volcanoes, we enable to interpret the signals plants provide in response to excess CO2 with airborne and spaceborne hyperspectral remote sensing methods, including a possible future Surface Biology and Geology (SBG) NASA satellite mission.As a critical step to mature and test this concept, we deployed small unmanned aerial systems (sUAS) using a fixed-wing sUAS designed for autonomous operations and long endurance in extreme environments, without causing significant disturbance of the sampled air. We integrated an in-situ sensor to record the CO2 enhancement field above the forest canopy. Test flight results on the flanks of Turrialba volcano in Costa Rica above forest canopies covering known moderate gas seeps demonstrate the sUAS-borne detection and mapping capabilities of above-canopy elevated CO2 gradients. The strong detection capabilities and high detector signal stability resulted from key system design elements including RF shielding, mechanical stabilization, and calibration procedures. This highly robust system is readily applied for diffuse volcanic CO2 emission studies on active volcanoes covered by dense vegetation.

Volcanic↗
NASA NTRS2010

Plans for the Meter Class Autonomous Telescope and Potential Coordinated Measurements with Kwajalein Radars

The National Aeronautics and Space Administration's (NASA) Orbital Debris Program Office is teaming with the US Air Force Research Laboratory's (AFRL) Maui Optical Site to deploy a moderate field-of-view, 1.3 m aperture, optical telescope for orbital debris applications. The telescope will be located on the island of Legan in the Kwajalein Atoll and is scheduled for completion in the Spring of 2011. The telescope is intended to sample both low inclination/high eccentricity orbits and near geosynchronous orbits. The telescope will have a 1 deg diagonal field-of-view on a 4K x 4K CCD. The telescope is expected to be able to detect 10-cm diameter debris at geosynchronous altitudes (5 sec exposure assuming a spherical specular phase function w/ albedo =0.13). Once operational, the telescope has the potential of conducting simultaneous observations with radars operated by the US Army at Kwajalein Atoll (USAKA) and located on the island of Roi-Namur, approximately 55 km to the north of Legan. Four radars, representing 6 frequency bands, are available for use: ALTAIR (ARPA-Long Range Tracking and Instrumentation Radar) operating at VHF & UHF, TRADEX (Target Resolution and Discrimination Experiment) operating at L-band and S-band, ALCOR (ARPA-Lincoln C-band Observables Radar) operating at S-band, and MMW (Millimeter Wave) Radar operating at Ka-band. Also potentially available is the X-band GBRP (Ground Based Radar-Prototype located 25 km to the southeast of Legan on the main island of Kwajalein.

Stansberry, Gene↗
DOE OSTI2024

A Vision–based Robust $\mathcal{H}$ ∞ Gain Scheduling Longitudinal and Lateral Following Controller for Autonomous Vehicles on Urban Curved Roads

Implementing advanced driver assistance systems (ADAS) in congested and intricate urban traffic scenarios poses significant challenges. To address the frequent stop–and–go motions exhibited by autonomous vehicles (AVs) navigating urban roads with changes in curvature, we propose a vision–based robust $\mathcal{H}$ ∞ adaptive cruise control system (ACC) for longitudinal control, plus a lane keeping assist system (LKAS) for lateral control. For the vision-based ACC, a weighted probability objective function for the vehicle following behavior is formulated. We incorporate $\mathcal{H}$ ∞ performance and gain scheduling techniques to mitigate the impact of uncertainty in visual sensor measurements. Furthermore, the optimal time headway is scheduled based on the velocity to ensure traffic flow efficiency and safety during the vehicle following process. For the LKAS, we introduce a road curvature estimation method that integrates lane and vehicle dynamics information to obtain the lateral and heading offsets. Next, the design criterion of the observer–based robust gain scheduling lateral motion controller is established by linear matrix inequality (LMI). Here, a series of experiments conducted within a camera–in–loop platform validate the proposed method.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1989

Control of intelligent robots in space

In view of space activities like International Space Station, Man-Tended-Free-Flyer (MTFF) and free flying platforms, the development of intelligent robotic systems is gaining increasing importance. The range of applications that have to be performed by robotic systems in space includes e.g., the execution of experiments in space laboratories, the service and maintenance of satellites and flying platforms, the support of automatic production processes or the assembly of large network structures. Some of these tasks will require the development of bi-armed or of multiple robotic systems including functional redundancy. For the development of robotic systems which are able to perform this variety of tasks a hierarchically structured modular concept of automation is required. This concept is characterized by high flexibility as well as by automatic specialization to the particular sequence of tasks that have to be performed. On the other hand it has to be designed such that the human operator can influence or guide the system on different levels of control supervision, and decision. This leads to requirements for the hardware and software concept which permit a range of application of the robotic systems from telemanipulation to autonomous operation. The realization of this goal requires strong efforts in the development of new methods, software and hardware concepts, and the integration into an automation concept.

Freund, E.↗
NASA NTRS1990

Kalman filter based range estimation for autonomous navigation using imaging sensors

Rotorcraft operating in high-threat environments fly close to the surface of the earth to utilize surrounding terrain, vegetation, or man-made objects to minimize the risk of being detected by the enemy. Two basic requirements for obstacle avoidance are detection and range estimation of the object from the current rotorcraft position. There are many approaches to the estimation of range using a sequence of images. The approach used in this analysis differes from previous methods in two significant ways: an attempt is not made to estimate the rotorcraft's motion from the images; and the interest lies in recursive algorithms. The rotorcraft parameters are assumed to be computed using an onboard inertial navigation system. Given a sequence of images, using image-object differential equations, a Kalman filter (Sridhar and Phatak, 1988) can be used to estimate both the relative coordinates and the earth coordinates of the objects on the ground. The Kalman filter can also be used in a predictive mode to track features in the images, leading to a significant reduction of search effort in the feature extraction step of the algorithm. The purpose is to summarize early results obtained in extending the Kalman filter for use with actual image sequences. The experience gained from the application of this algorithm to real images is very valuable and is a necessary step before proceeding to the estimation of range during low-altitude curvilinear flight. A simple recursive method is presented to estimate range to objects using a sequence of images. The method produces good range estimates using real images in a laboratory set up and needs to be evaluated further using several different image sequences to test its robustness. The feature generation part of the algorithm requires further refinement on the strategies to limit the number of features (Sridhar and Phatak, 1989). The extension of the work reported here to curvilinear flight may require the use of the extended Kalman filter.

Sridhar, Banavar↗
DOE OSTI2021

Harnessing autocatalytic reactions in polymerization and depolymerization

Abstract Autocatalysis and its relevance to various polymeric systems are discussed by taking inspiration from biology. A number of research directions related to synthesis, characterization, and multi-scale modeling are discussed in order to harness autocatalytic reactions in a useful manner for different applications ranging from chemical upcycling of polymers (depolymerization and reconstruction after depolymerization), self-generating micelles and vesicles, and polymer membranes. Overall, a concerted effort involving in situ experiments, multi-scale modeling, and machine learning algorithms is proposed to understand the mechanisms of physical and chemical autocatalysis. It is argued that a control of the autocatalytic behavior in polymeric systems can revolutionize areas such as kinetic control of the self-assembly of polymeric materials, synthesis of self-healing and self-immolative polymers, as next generation of materials for a sustainable circular economy. Graphic Abstract

36 MATERIALS SCIENCE↗
NASA NTRS2001

A Study on a Microwave-Driven Smart Material Actuator

NASA s Next Generation Space Telescope (NGST) has a large deployable, fragmented optical surface (greater than or = 2 8 m in diameter) that requires autonomous correction of deployment misalignments and thermal effects. Its high and stringent resolution requirement imposes a great deal of challenge for optical correction. The threshold value for optical correction is dictated by lambda/20 (30 nm for NGST optics). Control of an adaptive optics array consisting of a large number of optical elements and smart material actuators is so complex that power distribution for activation and control of actuators must be done by other than hard-wired circuitry. The concept of microwave-driven smart actuators is envisioned as the best option to alleviate the complexity associated with hard-wiring. A microwave-driven actuator was studied to realize such a concept for future applications. Piezoelectric material was used as an actuator that shows dimensional change with high electric field. The actuators were coupled with microwave rectenna and tested to correlate the coupling effect of electromagnetic wave. In experiments, a 3x3 rectenna patch array generated more than 50 volts which is a threshold voltage for 30-nm displacement of a single piezoelectric material. Overall, the test results indicate that the microwave-driven actuator concept can be adopted for NGST applications.

Choi, Sang H.↗
NASA NTRSDate not supplied

Crew Autonomy through Self-Scheduling: Guidelines for Crew Scheduling Performance Envelope and Mitigation Strategies

As NASA considers long-duration exploration missions, it is envisioned that crews will behave more autonomously as compared to low-Earth orbit missions. When considering long duration exploration missions, Flight Operations Directorate (FOD) identified the following benefits and challenges presented on this slide. As missions operate further from Earth, the communication latency between the spacecraft and Mission Control Center will increase requiring the crew to take a more active role in reacting to daily planning. However, one of the key challenges for crew self-scheduling is that we do not want to overwhelm astronauts who are not expert mission planners. This leads to our primary research objective: to first, characterize the human performance envelope for the task of planning and scheduling in the context of human spaceflight operations, then, develop countermeasure aids to mitigate adverse performance effects due to plan complexity, and finally, inform performance standards and guidelines based on research results. Our next steps are to finish summarizing our findings from the experiment in conference papers and our upcoming yearly report. In the upcoming year, we will continue to collect data in analog missions and begin summarizing our recommended standards and guidelines.

user experience↗
DOE OSTI2023

Optimizing Perovskite Thin‐Film Parameter Spaces with Machine Learning‐Guided Robotic Platform for High‐Performance Perovskite Solar Cells

Abstract Simultaneously optimizing the processing parameters of functional thin films remains a challenge. The design and utilization of a fully automated platform called SPINBOT is presented for the engineering of solution‐processed functional thin films. The SPINBOT is capable of performing experiments with high sampling variability through the unsupervised processing of hundreds of substrates with exceptional experimental control. Through the iterative optimization process enabled by the Bayesian optimization (BO) algorithm, the SPINBOT explores an intricate parameter space, continuously improving the quality and reproducibility of the produced thin films. This machine learning (ML)‐guided reliable SPINBOT platform enables the acceleration of the optimization process of perovskite solar cells via a simple photoluminescence characterization of films. As a result, this study arrives at an optimal film that, when processed into a solar cell in an ambient atmosphere, immediately yields a champion power conversion efficiency (PCE) of 21.6% with satisfactory performance reproducibility. The unsealed devices retain 90% of their initial efficiency after 1100 h of continuous operation at 60–65 °C under metal‐halide lamps. It is anticipated that the integration of robotic platforms with the intelligent algorithm will facilitate the widespread adoption of effective autonomous experimentation to address the evolving needs and constraints within the materials science research community.

14 SOLAR ENERGY↗
DOE OSTI2024

A Neural Network-Based Power Mismatch Elimination Strategy for Integrated Solar and ESS AC/DC Systems (MARS)

The multiport autonomous reconfigurable solar power plant (MARS) is a promising concept for the integration of photovoltaic (PV) and energy storage system (ESS) to the transmission ac grid and a high-voltage direct current (HVdc) link. The presence of PV and ESS in each arm of the MARS results in uneven distribution of active power among different submodules (SMs), thereby leading to unbalanced SM capacitor voltages and potentially compromising the system stability. Moreover, in the case of partial shadings, shaded PV SMs will suffer from decreased power injections causing power mismatch in the MARS system. To address this issue, a neural-network-based power mismatch elimination (NNPME) strategy is proposed in this article. The proposed NNPME strategy optimizes ESS usage and leverages both dc and ac circulating currents to facilitate power transfer among the SMs, arms, and phases of the MARS system. Simulation and control hardware-in-the-loop (cHIL) experiments demonstrate the effectiveness of the proposed NNPME strategy. Compared with the traditional approaches, the proposed NNPME strategy can significantly enhance system efficiency and ensure stable and continuous operation, even in the presence of uneven power distribution within the MARS system.

14 SOLAR ENERGY↗
NASA NTRS2013

The ISIS Mission Concept: An Impactor for Surface and Interior Science

The Impactor for Surface and Interior Science (ISIS) mission concept is a kinetic asteroid impactor mission to the target of NASA's OSIRIS-REx (Origins-Spectral Interpretation-Resource Identification-Security-Regolith Explorer) asteroid sample return mission. The ISIS mission concept calls for the ISIS spacecraft, an independent and autonomous smart impactor, to guide itself to a hyper-velocity impact with 1999 RQ36 while the OSIRIS-REx spacecraft observes the collision. Later the OSIRIS-REx spacecraft descends to reconnoiter the impact site and measure the momentum imparted to the asteroid through the impact before departing on its journey back to Earth. In this paper we discuss the planetary science, human exploration and impact mitigation drivers for mission, and we describe the current mission concept and flight system design.

cratering experiment↗
NASA NTRS2014

BioSentinel: Monitoring DNA Damage Repair Beyond Low Earth Orbit on a 6U Nanosatellite

We are designing and developing a 6U nanosatellite as a secondary payload to fly aboard NASAs Space Launch System (SLS) Exploration Mission (EM) 1, scheduled for launch in late 2017. For the first time in over forty years, direct experimental data from biological studies beyond low Earth orbit (LEO) will be obtained during BioSentinels 12- to 18-month mission. BioSentinel will measure the damage and repair of DNA in a biological organism and allow us to compare that to information from onboard physical radiation sensors. This data will be available for validation of existing models and for extrapolation to humans.The BioSentinel experiment will use the organism Saccharomyces cerevisiae (yeast) to report DNA double-strand-break (DSB) events that result from space radiation. DSB repair exhibits striking conservation of repair proteins from yeast to humans. The flight strain will include engineered genetic defects that prevent growth and division until a radiation-induced DSB activates the yeasts DNA repair mechanisms. The triggered culture growth and metabolic activity directly indicate a DSB and its repair. The yeast will be carried in the dry state in independent microwells with support electronics. The measurement subsystem will sequentially activate and monitor wells, optically tracking cell growth and metabolism. BioSentinel will also include TimePix radiation sensors implemented by JSCs RadWorks group. Dose and Linear Energy Transfer (LET) data will be compared directly to the rate of DSB-and-repair events measured by the S. cerevisiae biosentinels. BioSentinel will mature nanosatellite technologies to include: deep space communications and navigation, autonomous attitude control and momentum management, and micropropulsion systems to provide an adaptable nanosatellite platform for deep space uses.

cosmic rays↗
NASA NTRS1974

Vectorcardiographic results from Skylab medical experiment M092: Lower body negative pressure

Vectorcardiograms were recorded via a modified Frank lead system from all crewmen of the three Skylab missions in conjuction with the Lower Body Negative Pressure - M092 Experiment. Data were analyzed by a specially developed computer program (VECTAN). Design of the test sequences allowed direct comparisons of supine resting, Earth based (reference) vectorcardiograms with those taken during lower body negative pressure stress and those obtained at rest in orbit, as well as combinations of these conditions. Results revealed several statistically significant space flight related changes; namely, increased testing and lower body negative pressure stressed heart rates, modestly increased PR interval and corrected QTC interval, and greatly increased P and QPS loop maximal amplitudes. In addition, orientation changes in the QRS maximum vector and the J-vector at rest in space seem quite consistent among crewmen and different from those caused by the application of lower body negative pressure. No clinical abnormalities were observed. Etiology of these findings is conjectured to be, at least in part, related to fluid mass shifts occurring in weightlessness and attendant alterations in cardiovascular dynamics and myocardial autonomic control mechanisms.

Hoffler, G. W.↗
NASA NTRS1997

A Generative Control Capability for a Model-based Executive

This paper describes Burton, a core element of a new generation of goal-directed model-based autonomous executives. This executive makes extensive use of component-based declarative models to analyze novel situations and generate novel control actions both at the goal and hardware levels. It uses an extremely efficient online propositional inference engine to efficiently determine likely states consistent with current observations and optimal target states that achieve high level goals. It incorporates a flexible generative control sequencing algorithm within the reactive loop to bridge the gap between current and target states. The system is able to detect and avoid damaging and irreversible situations, After every control action it uses its model and sensors to detect anomalous situations and immediately take corrective action. Efficiency is achieved through a series of model compilation and online policy construction methods, and by exploiting general conventions of hardware design that permit a divide and conquer approach to planning. The paper presents a formal characterization of Burton's capability, develops efficient algorithms, and reports on experience with the implementation in the domain of spacecraft autonomy. Burton is being incorporated as one of the key elements of the Remote Agent core autonomy architecture for Deep Space One, the first spacecraft for NASA's New Millenium program.

Williams, Brian C.↗