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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 217 records · Page 12

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NASA NTRS2009

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Knox, W. Bradley↗

NASA NTRS2019

NASA Platform for Autonomous Systems (NPAS)

Autonomous operations are critical for the success, safety and crew survival of NASA deep space missions beyond low Earth orbit, including Gateway. For the past 10 years, Stennis Space Center (SSC) has been developing, and has demonstrated an innovative software platform, along with expertise and processes for implementation of autonomous operations.

Integrated Power Avionics and Software↗

NASA NTRS2010

Two-Phase Thermal Switching System for a Small, Extended Duration Lunar Surface Science Platform

This paper describes a novel thermal control system for the Warm Electronics Box (WEB) on board a small lunar surface lander intended to support science activities anywhere on the lunar surface for an extended duration of up to 6 years. Virtually all lander electronics, which collectively dissipate about 60 W in the reference mission, are contained within the WEB. These devices must be maintained below 323 K (with a goal of 303 K) during the nearly 15-earth-day lunar day, when surface temperatures can reach 390K, and above 263 K during the nearly 15-earth-day lunar night, when surface temperatures can reach 100K. Because of the large temperature swing from lunar day-to-night, a novel thermal switching system was required that would be able to provide high conductance from WEB to radiator(s) during the hot lunar day and low (or negligible) conductance during the cold lunar night. The concept that was developed consists of ammonia variable conductance heat pipes (VCHPs) to collect heat from WEB components and a polymer wick propylene loop heat pipe (LHP) to transport the collected heat to the radiator(s). The VCHPs autonomously maximize transport when the WEB is warm and autonomously shut down when the WEB gets cold. The LHP autonomously shuts down when the VCHPs shut down. When the environment transitions from lunar night to day, the VCHPs and LHP autonomously turn back on. Out of 26 analyzed systems, this novel arrangement was able to best achieve the combined goals of zero control power, autonomous operation, long life, low complexity, low T, and landed tilt tolerance.

Bugby, David C.↗

DOE OSTI2024

Physics-informed State-space Neural Networks for transport phenomena

This work introduces Physics -informed State -space neural network Models (PSMs), a novel solution to achieving real-time optimization, flexibility, and fault tolerance in autonomous systems, particularly in transportdominated systems such as chemical, biomedical, and power plants. Traditional data -driven methods fall short due to a lack of physical constraints like mass conservation; PSMs address this issue by training deep neural networks with sensor data and physics -informing using components' Partial Differential Equations (PDEs), resulting in a physics -constrained, end -to -end differentiable forward dynamics model. Further, through two in silico experiments - a heated channel and a cooling system loop - we demonstrate that PSMs offer a more accurate approach than a purely data -driven model. In the former experiment, PSMs demonstrated significantly lower average root -mean -square errors across test datasets compared to a purely data -driven neural network, with reductions of 44 %, 48 %, and 94 % in predicting pressure, velocity, and temperature, respectively. Beyond accuracy, PSMs demonstrate a compelling multitask capability, making them highly versatile. In this work, we showcase two: supervisory control of a nonlinear system through a sequentially updated state -space representation and the proposal of a diagnostic algorithm using residuals from each of the PDEs. The former demonstrates PSMs' ability to handle constant and time -dependent constraints, while the latter illustrates their value in system diagnostics and fault detection.

42 ENGINEERING↗

NASA NTRS2010

Distributed Disdrometer and Rain Gauge Measurement Infrastructure Developed for GPM Ground Validation

Global Precipitation Mission (GPM)retrieval algorithm validation requires datasets characterizing the 4-D structure, variability, and correlation properties of hydrometeor particle size distributions (PSD) and accumulations over satellite fields of view (FOV;<10 km). Collection of this data provides a means to assess retrieval errors related to beam filling and algorithm PSD assumptions. Hence, GPM Ground Validation is developing a deployable network of precipitation gauges and disdrometers to provide fine-scale measurements of PSD and precipitation accumulation variability. These observations will be combined with dual-frequency, polarimetric, and profiling radar data in a bootstrapping fashion to extend validated PSD measurements to a large coverage domain. Accordingly, a total of 24 Parsivel disdrometers(PD), 5 3rd-generation 2D Video Disdrometers (2DVD), 70 tipping bucket rain gauges (TBRG),9 weighing gauges, 7 Hot-Plate precipitation sensors (HP), and 3 Micro Rain Radars (MRR) have been procured. In liquid precipitation the suite of TBRG, PD and 2DVD instruments will quantify a broad spectrum of rain rate and PSD variability at sub-kilometer scales. In the envisioned network configuration 5 2DVDs will act as reference points for 16 collocated PD and TBRG measurements. We find that PD measurements provide similar measures of the rain PSD as observed with collocated 2DVDs (e.g., D0, Nw) for rain rates less than 15 mm/hr. For heavier rain rates we will rely on 2DVDs for PSD information. For snowfall we will combine point-redundant observations of SWER distributed over three or more locations within a FOV. Each location will contain at least one fenced weighing gauge, one HP, two PDs, and a 2DVD. MRRs will also be located at each site to extend the measurement to the column. By collecting SWER measurements using different instrument types that employ different measurement techniques our objective is to separate measurement uncertainty from natural variability in SWER and PSD. As demonstrated using C3VP polarimetric radar, gauge, and 2DVD/PD datasets these measurements can be combined to bootstrap an area wide SWER estimate via constrained modification of density-diameter and radar reflectivity-snowfall relationships. These data will be combined with snowpack, airborne microphysics, radar, radiometer, and tropospheric sounding data to refine GPM snowfall retrievals. The gauge and disdrometer instruments are being developed to operate autonomously when necessary using solar power and wireless communications. These systems will be deployed in numerous field campaigns through 2016. Planned deployment of these systems include field campaigns in Finland (2010), Oklahoma (2011), Canada (2012) and North Carolina (2013). GPM will also deploy 20 pairs of TBRGs within a 25 km2 region along the Virginia coast under NASA NPOL radar coverage in order to quantify errors in point-area rainfall measurements.

Petersen, Walter A.↗

NASA NTRSDate not supplied

The Light Bender Concept for Power Distribution on a Lunar Base

Power generation and distribution is a challenge for a future lunar base. A promising concept for lunar power distribution is the light bender—a system that utilizes autonomously deployed mirrors to reflect sunlight to shaded regions on the lunar surface. The light bender system consists of two components: tandem reflector mirrors (TRM) which reflect sunlight to a permanently shaded region and the Cassegrain Fresnel distribution optics (CFDO) which collects the reflected light from the TRM and redirects light to local consumer nodes. This paper describes the light bender system concepts and the associated system analysis and technology development performed as part of a 2021 NASA Innovative Advanced Concepts (NIAC) phase I award.

Bradford Robertson↗

NASA NTRSDate not supplied

The Light Bender Concept for Power Distribution on a Lunar Base

Bradford Robertson↗

DOE OSTI2023

Autonomous Restoration of Networked Microgrids Using Communication-Free Smart Sensing and Protection Units

Here this paper presents autonomous restoration of networked microgrids using distributed energy resources (DERs), inverter-based resources (IBRs) in general, and controllable assets of intelligence without communication to achieve a extremely resilient power system restoration. The main innovation of this work lies in use of real-time smart sensing and decision making that enable autonomous recombination of islanded microgrids, which are individually black-started by local grid-forming (GFM) inverter units. The smart circuit breakers (SCBs) designed and demonstrated here play critical roles in the restoration process to achieve autonomy; the autonomous restoration scheme is not pre-engineered and may be subject to encounter overloading, live or downed segments as the boundary of the microgrids dynamically expands without prior knowledge and only with local measurement. We demonstrate autonomous microgrid restoration both in simulation of a modified IEEE 13-bus system, and in a hardware testbed comprising 24 GFM-IBRs and 6-SCBs, depicting several scenarios to evaluate their functionalities and interoperability. This work validates high potential of extremely resilient microgrid using novel approaches for inverter-based bottom-up system restoration in a communication-free paradigm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Autonomous Energy Systems: Building Reliable, Resilient, and Secure Electrified Communities

Technological changes across energy systems are forcing utilities and operators to reconsider their methods for managing power delivery, but few operators have adopted advanced controls and operational software. Their challenge is that every system has peculiar requirements, and the available solutions are relatively new, untested, and difficult to integrate into an operational environment. Through extensive collaboration with utilities and cooperatives, the National Renewable Energy Laboratory has realized the need for autonomous and optimized management of energy resources, leading to the development of Autonomous Energy Systems, a packaged set of controls that is ready to be integrated into existing control rooms.

automation↗

NASA NTRS1977

Conceptual definition of Automated Power Systems Management

Automated Power Systems Management (APSM) is defined as the capability of a spacecraft power system to automatically perform monitoring, computational, command, and control functions without ground intervention. Power systems for future planetary spacecraft must have this capability because they must perform up to 10 years, and accommodate real-time changes in mission execution autonomously. Specific APSM functions include fault detection, isolation, and correction; system performance and load profile prediction; power system optimization; system checkout; and data storage and transmission control. This paper describes the basic method of implementing these specific functions. The APSM hardware includes a central power system computer and a processor dedicated to each major power system subassembly along with digital interface circuitry. The major payoffs anticipated are in enhancement of spacecraft reliability and life and reduction of overall spacecraft program cost.

Imamura, M. S.↗

DOE OSTI2023

Sensor Anomaly Detection for Nuclear Reactor Systems Utilizing Linear Regression and K-Means Unsupervised Machine Learning

Nuclear reactors and related systems are becoming increasingly complex due to advancing technologies in next-generation power reactors. This increased complexity necessitates enhanced automation and data management capabilities. To successfully realize autonomous systems, methods must be developed to handle vast volumes of data and effectively distinguish anomalous data from noise and expected data. While impressive models utilizing digital twins and similar approaches are under development, here we propose a simplified model for analyzing fundamental methods and techniques. Initially, we created a general dataset by using initial data from PCTRAN in order to represent ideal steady-state conditions. We then inserted anomalies based on prevalent sensor anomaly types (e.g., point anomalies, linear drift, and downward deviations), along with unusual anomalies such as exponential drift and upward deviations. To detect anomalies, we developed a program that employs data partitioning and linear regression to preprocess and filter the anomalous data. A K-Means machine learning (ML) method was then applied to separate and count the data within the anomalous partition. The results from all datasets—apart from exponential growth—demonstrated positive outcomes, with each returning multiple instances of greaterthan-95% accuracy. We conducted further investigations using Idaho National Laboratory’s RAVEN software to perform a sensitivity analysis on the input variables (R 2 Tolerance, Slope Tolerance, and Window Size) and found that the output variables (Accuracy and Time) were most sensitive to the Window Size. Despite the promising results published, further development is required to effectively apply these methods to nuclear systems. Nevertheless, the strengths of this approach are evident and hold promise for future applications in the field.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2020

EPRI Demonstration of an Autonomous Site Characterization Vehicle - 20523

A substantial effort is applied in performing radiological characterization of structures and land areas during decommissioning of a nuclear facility. This includes multiple surveys of land areas and large structures to support eventual site release under the Multi Agency Survey and Site Investigation Manual (MARSSIM, Reference 1). These surveys are typically performed using manually delivered systems, which is time consuming and labor intensive. Radiological surveys intentionally follow a prescribed protocol with respect to areas covered, scan speeds, responses to elevated readings, required detector offsets, the need for repeat measurements, etc. Based on these attributes, combined with the repetitive effort of performing surveys over large areas, automation of radiological characterization techniques has a high potential to be successful and promises substantial benefit. EPRI has performed a project that resulted in the development and demonstration of an autonomous site characterization system. This EPRI project focused on building surfaces and the surfaces of large land areas as these configurations lend themselves more readily to automated survey. The project included: - Identification of the requirements for an autonomous site characterization system; - A survey of existing control systems that use automation to conduct characterization of structures and land areas. - As no fully adequate systems were identified, a complete system was developed that utilized commercially available detection and analysis systems and a self driving vehicle owned by EPRI. The system was demonstrated at the Kewaunee nuclear power plant site in the fall of 2019. The demonstration included: - Autonomous surveys of floor areas inside the Auxiliary Building at Kewaunee after manually controlled mapping of the survey areas. - For land areas, the vehicle autonomously surveyed areas using travel paths had been preprogrammed onto an internet available map of area. In this case, GPS coordinates from the preprogramming were used for navigation by the vehicles guidance system. This paper summarizes the characterization system development and system demonstration which will also be published in an EPRI report in the first half of 2020. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2000

Nanotechnology at NASA Ames

Advanced miniaturization, a key thrust area to enable new science and exploration missions, provides ultrasmall sensors, power sources, communication, navigation, and propulsion systems with very low mass, volume, and power consumption. Revolutions in electronics and computing will allow reconfigurable, autonomous, 'thinking' spacecraft. Nanotechnology presents a whole new spectrum of opportunities to build device components and systems for entirely new space architectures: (1) networks of ultrasmall probes on planetary surfaces; (2) micro-rovers that drive, hop, fly, and burrow; and (3) collections of microspacecraft making a variety of measurements.

Srivastava, Deepak↗

DOE OSTI2025

Power Quality and Load Capacity Evaluations of an Electric Vehicle for Multi-Robot System Applications

This paper evaluates the capability of a fully electric pickup truck, using the Ford F-150 Lightning as an example, to provide power to the circuit of a multi-robot system. The case study was conducted on a simulated INL Autonomous Pit Exploration System (APES) designed for the inspection of nuclear waste tank pits. Through a series of controlled tests, the vehicle’s power delivery consistency, load-handling capability, and battery performance were assessed under various conditions. First of all, the load test demonstrated that the vehicle provided stable power with low distortion and no unexpected interruptions. Second, during the operational limit test, the 240V system sustained loads up to 7.4 kW before tripping, providing insights into its operational limits. Last but not least, during a simulated full-scale APES operation, the vehicle’s battery depleted by only 6% over an hour, indicating sufficient capacity for extended use while retaining reserve power for transportation needs. This study highlights the potential of electric vehicles as reliable power sources for field operations, contributing to the advancement of sustainable technologies by reducing reliance on traditional fossil fuel generators and promoting the integration of clean energy solutions in remote and challenging environments.

Electric vehicle↗

DOE OSTI2025

IEEE SusTech 2025 Presentation

This paper evaluates the capability of a fully electric pickup truck, using the Ford F-150 Lightning as an example, to provide power to the circuit of a multi-robot system. The case study was conducted on a simulated INL Autonomous Pit Exploration System (APES) designed for the inspection of nuclear waste tank pits. Through a series of controlled tests, the vehicle’s power delivery consistency, load-handling capability, and battery performance were assessed under various conditions. First of all, the load test demonstrated that the vehicle provided stable power with low distortion and no unexpected interruptions. Second, during the operational limit test, the 240V system sustained loads up to 7.4 kW before tripping, providing insights into its operational limits. Last but not least, during a simulated full-scale APES operation, the vehicle’s battery depleted by only 6\% over an hour, indicating sufficient capacity for extended use while retaining reserve power for transportation needs. This study highlights the potential of electric vehicles as reliable power sources for field operations, contributing to the advancement of sustainable technologies by reducing reliance on traditional fossil fuel generators and promoting the integration of clean energy solutions in remote and challenging environments.

42 - ENGINEERING↗

DOE OSTI2024

Low-Flow Marine Hydrokinetic Turbine for Small Autonomous Unmanned Mobile Recharge Stations

A prototype low-flow marine current turbine for deployment from a small unmanned mobile floating platform has been developed for autonomously seeking and harnessing tidal/coastal currents. The support platform is an unmanned surface vehicle (USV), in the form of a catamaran with two electric outboard motors and with capabilities for autonomous navigation. The USV utilized is a WAM-V 16 vehicle that has been developed separately with support from the Office of Naval Research (ONR) [1]. The marine current turbine is based on a freestream waterwheel (FSWW), also known as an undershot waterwheel (FSWW), mounted on the stern of the USV. The concept of operation involves the USV autonomously navigating to a designated marine current resource. Upon arrival, the USV anchors itself, aligns with the current, and deploys the FSWW turbine using a custom cable-lift mechanism. The turbine harnesses the local current, and an onboard power-take-off (PTO) device converts the mechanical energy into electricity, which is stored in an onboard battery bank. When energy harvesting is completed, the turbine and the anchor are retrieved and the USV navigates to a selected location. These unmanned at-sea platforms can provide power to other unmanned maritime systems. Specifically, in this project, the power generated onboard can be used to charge aerial drones via a custom flight deck that has been developed for the USV. The recharging capabilities offered by a fleet of such strategically placed recharging stations can significantly benefit aerial drones operating in the maritime domain by eliminating the need to travel back and forth to land or ship based charging stations. The project has resulted in the development of subcomponents, including the FSWW turbine, a novel PTO, an automated anchoring system for the USV, an automated turbine deployment system, and a flight deck with capabilities onboard the USV for landing, direct-contact charging and takeoff of aerial drones. The design and development of these subsystems have culminated in the overall prototype marine hydrokinetic platform (MHK Platform, Fig. 1). Comprehensive lab and field testing have been conducted to validate the functionality and performance of the platform and its components. The project demonstrates the potential for autonomous, unmanned systems to harness renewable energy from marine currents, and provide sustainable power solutions for maritime applications such as coastal surveillance and environmental monitoring; shoreline mapping; search and rescue; oceanographic research; inspection and maintenance of offshore energy installations like wind turbines and oil rigs; oil spill response; maritime disaster response; and aerial surveys, as well as facilitation of data transfer drones and shore stations.

16 TIDAL AND WAVE POWER↗

DOE OSTI2020

Good Grids Make Good Neighbors

It's great to have neighbors you can depend on, whether you're borrowing a cup of sugar or you need someone to walk your dog while you're out of town. In the western Colorado neighborhood of Basalt Vista, the residents are even closer than most: They share their electricity. But unlike your neighbor with the sugar, the residents of Basalt Vista may not even know when they're being generous. The energy exchanges happen automatically, behind the scenes. What residents do know is how inexpensive, reliable, and renewable their electricity is.

autonomous energy grids↗

DOE OSTI2021

Overcoming Communications Outages in Inverter Downtime Analysis

This paper presents two methods of detecting inverter downtime and estimating lost production from downtime events using timeseries system production measurements. The methods focus on distinguishing communications interruptions from true production outages and are successful in most cases. To enable fleet-scale analysis of inverter availability, the methods are designed to be semi-autonomous. The first method uses only inverter and system meter AC power measurements while the second uses cumulative production and expected energy data to classify outages and estimate lost production. The methods are demonstrated using real field data and the results are discussed.

41 EE - Solar Energy Technologies Office (EE-4S)↗