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DOE OSTI2022

Integration of Wireless Sensor Networks and Battery-free RFID for Advanced Reactors

To address an important need for Nuclear Power Plants (NPPs) to significantly reduce the amount of the required cables for sensor data communications, this Phase I SBIR effort successfully developed and demonstrated a novel low-cost proof-of-concept prototype of a secure wireless sensor network backbone communications system. This system combines commercially available low power, low cost XBEE wireless communications network and passive (battery-free) Radio Frequency Identification (RFID) systems to report individual sensor data and their location through the containment wall for rapid response to anomalies in nuclear facilities. This WIreless Sensing and Locating (WISLO) system network architecture allows non-intrusive wireless collection of sensor data with the sensor’s accurate location information from inside of the instrumentation or containment area with minimal need for power sources. The multi-node sensor data in the containment area is wirelessly transmitted to outside through the metal reinforced concrete walls without the need for any batteries. The WISLO system could be readily used in current reactor fleet and future advanced reactors, as well as in small modular reactors (SMR). The WISLO system is the first dual frequency battery-free trough the wall communications backbone system developed specifically for use in nuclear power plants. It not only can modernize the sensor monitoring practices in the existing reactor fleet, but also offers a secure, low-cost solution to advanced reactors and SMRs by removing cables and issues related to them such as cable integrity, reporting delays, and installation and maintenance costs. The intent is to improve process safety, reliability, efficiency, and cost effectiveness to the monitoring and maintenance process in current and future plants. As we address the next productization and manufacturing capabilities in the next phase, this system will serve the needs of many commercial and government applications in remote monitoring of sensor data that demand battery-free transmission of sensor data such as Internet-of-Things (IOT).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Cyber-Physical Event Emulation-Based Transmission-and-Distribution Co-Simulation for Situational Awareness of Grid Anomalies (SAGA)

Energy management of transmission and distribution networks (T&D) is becoming more challenging with the accelerated adoption of distributed energy resources (DERs)-such as distributed photovoltaic generation and battery energy storage systems (BESS)-on the electric grid. To better analyze the impacts of DERs on both transmission and distribution systems, a comprehensive T&D co-simulation platform is developed. Further, with DERs more actively participating in system operation-e.g., by providing real-time grid services-their cyber vulnerability needs to be better understood to maintain system reliability. This paper discusses a cyber-physical events emulation-based T&D co-simulation platform to perform comprehensive cyber events emulations, physical simulation, and analysis of interdependent impacts. Results from the case studies-which show how cyber events on a synthetic distribution network can impact operations on the transmission and distribution network-validate that the proposed T&D cosimulation platform can perform cyber-physical events emulation and produce response in near realtime; therefore, with extensive simulation using the proposed co-simulation platform, the system operators can accumulate adequate training data for system situational awareness of grid anomalies.

anomalies detection↗

NASA NTRSDate not supplied

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries↗

NASA NTRS2015

Solar Alpha Rotary Joint (SARJ) Lubrication Interval Test and Evaluation (LITE). Post-Test Grease Analysis

The Solar Alpha Rotary Joint (SARJ) is a mechanism of the International Space Station (ISS) that orients the solar power generating arrays toward the sun as the ISS orbits our planet. The orientation with the sun must be maintained to fully charge the ISS batteries and maintain all the other ISS electrical systems operating properly. In 2007, just a few months after full deployment, the starboard SARJ developed anomalies that warranted a full investigation including ISS Extravehicular Activity (EVA). The EVA uncovered unexpected debris that was due to degradation of a nitride layer on the SARJ bearing race. ISS personnel identified the failure root-cause and applied an aerospace grease to lubricate the area associated with the anomaly. The corrective action allowed the starboard SARJ to continue operating within the specified engineering parameters. The SARJ LITE (Lubrication Interval Test and Evaluation) program was initiated by NASA, Lockheed Martin, and Boeing to simulate the operation of the ISS SARJ for an extended time. The hardware was designed to test and evaluate the exact material components used aboard the ISS SARJ, but in a controlled area where engineers could continuously monitor the performance. After running the SARJ LITE test for an equivalent of 36+ years of continuous use, the test was opened to evaluate the metallography and lubrication. We have sampled the SARJ LITE rollers and plate to fully assess the grease used for lubrication. Chemical and thermal analysis of these samples has generated information that has allowed us to assess the location, migration, and current condition of the grease. The collective information will be key toward understanding and circumventing any performance deviations involving the ISS SARJ in the years to come.

Golden, Johnny L.↗

NASA NTRS1992

On-orbit deployment anamolies: What can be done?

Modern communications satellites rely heavily upon deployable appendage (i.e., solar arrays, communications antennas, etc.) to perform vital functions that enable the spacecraft to effectively conduct mission objectives. Communications and telemetry antennas provide the radio-frequency link between the spacecraft and the earth ground station, permitting data to be transmitted and received from the satellite. Solar arrays serve as the principle source of electrical energy to the satellite, and re-charge internal batteries during operation. However, since satellites cannot carry back-up systems, if a solar array fails to deploy, the mission is lost. The subject of on-orbit anomalies related to the deployment of spacecraft appendage, and possible causes of such failures are examined. Topics discussed include mechanical launch loading, on-orbit thermal and solar concerns, reliability of spacecraft pyrotechnics, and practical limitations of ground-based deployment testing. Of particular significance, the article features an in-depth look at the lessons learned from the successful recovery of the Telesat Canada Anik-E2 satellite in 1991.

Freeman, Michael↗

DOE OSTI2022

On ( g – 2) μ from gauged $\mathrm{U(1)_X}$

We investigate an economical explanation for the (g – 2) μ anomaly with a neutral vector boson from a spontaneously broken U(1) X gauge symmetry. The Standard Model fermion content is minimally extended by 3 right-handed neutrinos. Using a battery of complementary constraints, we perform a thorough investigation of the renormalizable, quark flavor-universal, vector-like U(1) X models, allowing for arbitrary kinetic mixing. Out of 419 models with integer charges not greater than ten, only 7 models are viable solutions, describing a narrow region in model space. These are either L μ – L τ or models with a ratio of electron to baryon number close to –2. The key complementary constraints are from the searches for nonstandard neutrino interactions. Furthermore, we comment on the severe challenges to chiral U(1) X solutions and show the severe constraints on a particularly promising such candidate.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Cluster Expansion Analysis of Atomic Order in Li-Ion Battery Cathode Material LiCo y Ni 1-y O 2

A modified cluster-expansion treatment was developed recently to analyze atomic order in LiCo y Ni 1-y O 2 , a model cathode material for Li-ion batteries. In this treatment, referred to as a “spin-atom” cluster expansion, the occupant of a lattice site is identified by its spin state as well as its atomic species. Further, Effective Cluster Interaction (ECI) coefficients are derived from a large training data set (i.e., the set of atomic arrangements for which DFT calculations are performed) which is filtered by an anomaly detection algorithm to eliminate poorly converged DFT calculations. The cluster expansion incorporates Li-Ni (LN) exchange as well as intralayer Co-Ni (CN) exchange. Monte Carlo simulations based on the cluster expansion were applied to the Ni-rich part of the phase diagram. The simulations predict a miscibility gap between y = 0.05 and y = 0.65.

25 ENERGY STORAGE↗

NASA NTRS2026

The Operational NASA Anomaly Gas Analyzer and Exploration Follow-Ons

The NASA Anomaly Gas Analyzer (AGA) is the culmination of nearly ten years of advancement of core technology originally developed by Vista Photonics through the Small Business Innovation Research (SBIR) program and expanded using NASA program funding. The AGA is a portable, battery operated, optical gas detection instrument for continuous monitoring of H 2 O, CO 2 , O 2 , CO, NH 3 , HCN, HF, HCl in the spacecraft environment. Real time, in-situ monitored, gas concentrations are communicated at 1 Hz through a built-in display on-orbit and additionally through a serial interface on the ground. The instruments function over the typical range of temperatures and pressures required for the spacecraft environment. A ten-year operational life is targeted. Seven AGA instruments are currently deployed on the International Space Station and two Orion-specific units are manifested for Artemis 2. A variation of the operational AGA is under development for lunar Human Landing Systems. A wider calibrated operating pressure envelope is required in this application. Otherwise, the instruments straightforwardly address lessons learned from the original AGA by improving aspects of thermal control, ruggedness, and ease-of-use. A subset of AGA-developed sensed gases (H 2 O, CO 2 , O 2 ) is the subject of the Primary Constituent Monitor (PCM) development for the Habitation and Logistics Outpost (HALO) destined for lunar orbit. Two PCMs will be installed in HALO as part of the environmental control loop where they will interface with vehicle power and communications. While the basic sensor techniques are unchanged from the AGA, these instruments have been radiation hardened to survive for many years in the harsh target environment. Current development status for these instruments will be presented along with recent developments of a naval submarine variant.

Air Monitoring↗

NASA NTRS2026

The Operational NASA Anomaly Gas Analyzer and Exploration Follow-Ons

ECLSS↗

DOE OSTI2021

Fictitious phase separation in Li layered oxides driven by electro-autocatalysis

Layered oxides widely used as lithium-ion battery electrodes are designed to be cycled under conditions that avoid phase transitions. Although the desired single-phase composition ranges are well established near equilibrium, operando diffraction studies on many-particle porous electrodes have suggested phase separation during delithiation. Notably, the separation is not always observed, and never during lithiation. These anomalies have been attributed to irreversible processes during the first delithiation or reversible concentration-dependent diffusion. However, these explanations are not consistent with all experimental observations such as rate and path dependencies and particle-by-particle lithium concentration changes. Here, we show that the apparent phase separation is a dynamical artefact occurring in a many-particle system driven by autocatalytic electrochemical reactions, that is, an interfacial exchange current that increases with the extent of delithiation. We experimentally validate this population-dynamics model using the single-phase material L ix (Ni 1/3 Mn 1/3 Co 1/3 )O 2 (0.5 < x < 1) and demonstrate generality with other transition-metal compositions. Operando diffraction and nanoscale oxidation-state mapping unambiguously prove that this fictitious phase separation is a repeatable non-equilibrium effect. We quantitatively confirm the theory with multiple-datastream-driven model extraction. More generally, our study experimentally demonstrates the control of ensemble stability by electro-autocatalysis, highlighting the importance of population dynamics in battery electrodes (even non-phase-separating ones).

36 MATERIALS SCIENCE↗

NASA NTRS2024

Testing of Advanced Capabilities to Enable In-time Safety Management and Assurance for Future Flight Operations

In order to refine an initial Concept of Operations, explore Concepts of Use, and expose/validate requirements for future In-Time Aviation Safety Management Systems (IASMS), testing architectures were created, along with a set of capabilities and underlying information exchange protocols. These systems were conceived and developed based on hazards associated with two envisioned urban area flight domains: (1) highly autonomous small uncrewed aerial systems (sUAS) operating at low altitudes, and (2) highly autonomous air taxis. The initial scope of this development is described in [1]; this report provides an update, focusing on the subsequent developments and test activities. As stated in [1], it is important to note that there are many capabilities already in use by the industry (or soon to be in use) that will play critical roles in future IASMS designs. Those reported here were developed to address a gap in the current state-of-the-art regarding specific hazards/risks, and/or to allow for investigation of the interplay between and across hazard types — particularly regarding how overall safety risk can be reduced or managed effectively. Results of testing and development activities are organized by the operational phase wherein a particular capability would be employed (i.e., preflight, in-flight, and post-flight/off-line). Pre-flight: A set of capabilities were developed to help mitigate safety risk prior to flight (e.g., during flight and mission planning). Results of testing summarize (1) validation activities to raise the Technology Readiness Level (TRL) and (2) evaluation activities where the capabilities were applied to flight/mission planning procedures and used by operators/pilots. For the latter, flight plans were automatically assessed, and operators/pilots were notified of hazardous flight segments so as to enable adjustment of the flight plan and re-evaluation, and/or to better inform go/no-go decisions. Capabilities addressed hazards associated with power consumption, third-party risk, wind, navigation system performance, radiofrequency interference, and proximity to geo-spatial threats (e.g., buildings, trees, and no-fly zones). In-flight: Flight experiments tested capabilities that detect and respond to hazards encountered during flight. In the first series, safety hazards were monitored and assessed onboard, and system-generated mitigation maneuvers were recorded (but not acted upon by the vehicle). In the second series, mitigation maneuver commands directed the aircraft in response to safety hazards (i.e., auto-mitigation). The sUAS used for testing is described in full, as is the test architecture, which included commercial avionics, research avionics, and onboard software designed to detect, assess, and respond to hazards. The onboard system was designed as a run-time assurance framework, consistent with [2] and supportive of both supervisory and automated modes. The primary functions included: real-time risk assessment (RTRA), auto-pilot monitoring, constraint monitoring, and contingency select/triggering. RTRA performs integrated risk assessment considering data from several hazard-related monitors (e.g., battery, motors, navigation, communications, population density, and loss-of-control). Post-flight/off-line: Data monitored and recorded during flights can enable IASMS capabilities that execute after flights have completed (or “off-line”). These include: (1) the ability to identify anomalies and trends that may only be observable when comparing data spanning a number of similar flights; (2) the ability to update and validate pre-flight and in-flight capabilities and any underlying models to improve their performance; (3) the ability to report anomalies/off-nominals that may indicate design changes or maintenance actions are needed; and (4) the ability for humans involved in operations to report safety-relevant observations to help in understanding the flight data and/or the operational context of a flight. Progress on three such capabilities is summarized; the first investigates anomaly detection given a limited set of flight logs and applies an approach previously used for space operations. The second explores what could be identified using a larger set of flight logs, including from web-based forums where flight logs are posted by sUAS autopilot users. The third creates a new means of collecting information on UAS incidents and accidents via the Aviation Safety Reporting System (ASRS).

sUAS↗

NASA NTRS2001

Chandra Space Flight Software: Using Software to Autonomously Operation the Largest and Most Sensitive X-Ray Telescope in the World

Chandra is the world's largest and most sensitive X-ray telescope. The Chandra X-ray Observatory is the third in NASA's family of "Great Observatories." The Chandra X-ray Observatory, launched by Space Shuttle Columbia on July 23, 1999, is NASA's newest Great Observatory. The Chandra space flight software is the operational software, which controls and directs the Chandra X-ray Observatory. The Chandra flight software has executed faultlessly for over 13,000 hours on-orbit. The Chandra flight software directly controls the Pointing, Aspect Determination, Electrical Power Subsystem, Propulsion system, and the Command, Communications, and Data Management subsystems. The software controls the spacecraft operations during all phases of the mission. The software also performs thermal control of the telescope to maintain pointing accuracy and monitors radiation levels throughout the orbit so that the Science Instruments can be safed if radiation thresholds are exceeded. The efficient operation of Chandra flight software has enabled the gathering of crucial science data. The Chandra flight software fault protection is the key to early detection and prevention of science instrument or spacecraft damage in an operating platform/environment, which is completely unforgiving. Permanently open Sun Shade Door and ACIS focal plane radiator sensitivity exposes science instruments and mirrors to damage for pointing anomalies causing an attitude excursion. The Chandra flight software must prevent these attitude excursions from occurring for ANY failure. Another example is that the power system has an unregulated bus, which imposes severe operating requirements on Chandra flight software to control array pointing and battery connection/disconnect using a unique algorithmic and logic approach. The Chandra flight software has enabled a truly autonomous vehicle with greater than 99% of all mission data collected as planned. Less than 15% of spacecraft operations are conducted in view (1 hour out of 8) leading to very extended periods without ground contact. The Chandra flight software implements the flexible mission plan during this out of view period, manages the solid state recorder capacity, controls all pointing and maneuvers, provides fault detection for all satellite subsystems, and initiates communications with the ground at the appropriate time. This paper will describe the software architecture features, key design elements and software testing techniques that have facilitated Chandra's success.

Crumbley, Tim↗

NASA NTRS1990

Primary lithium cell life studies

One solution for providing a truly independent power source is to package, within the critical subsystem element, a primary battery that can remain dormant for time periods as long as the mission life, which can be 10-15 years, maximum. When primary power from the spacecraft solar array/battery system is interrupted, the backup battery system, which is connected through a diode to the power input line, would automatically support the load to avoid a power interruption to the critical load for a time period long enough to ensure that ground control could access the satellite and correct the anomaly by sending appropriate commands to the spacecraft. Critical subsystems identified for the application are telemetry and command circuits, volatile computer memory, attitude control circuits, and some critical payloads. Due to volume packaging and weight restrictions that exist on most spacecraft, coupled with the long storage periods required, lithium cell technology was selected for the backup power source. Because of the high energy density (200-400 Wh/kg), long shelf life, and load capability, soluble cathode primary lithium technology was chosen. The most important lithium cell properties that require detail characterization for this application are capacity loss, shelf life, and the voltage delay mechanism. These are functions of storage time and temperature. During storage, a passive film builds up on the lithium electrode. The film protects the lithium electrode from progressive capacity decay but requires time to break down when a load is applied. This phenomenon results in a depressed voltage during the period of film breakdown which can last from fractions of a second to minutes.

Capulli, John↗

DOE OSTI2021

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRSDate not supplied

Firmware Architecture of the ARMADAS Bolting Robot

The Automated Reconfigurable Mission Adaptive Digital Assembly Systems (ARMADAS) project, under development at NASA Ames Research Center, has demonstrated on-ground autonomous robotic assembly of extensive digital structures, and it is now moving forward towards in-space demonstration. The ARMADAS system comprises of the operation software, the operation user interface (opsUI), and a swarm of robots. The robotic system consists of a multitude of collaborative agents specifically designed to transport, place and bolt the building blocks, called voxels (volumetric pixels). This paper focuses on the bolting robot, referred to as Mobile Metamaterial Internal Co-Integrator (MMIC-I). MMIC-I is a battery-powered crawling robot. It navigates the structure through extension, contraction and gripping. Two distinct controller boards operate the robot's two symmetric modules, referred to as module A and B. Board A is the master board: it coordinates motion planning and motion primitives execution, hosts the WiFi client, performs periodic self-assessment and system idle check and triggers faults if anomalies are detected. Board B periodically sends a heartbeat to board A, through a wired communication channel that uses the Serial protocol. Additionally, board A's WiFi client receives heartbeat packet requests or motion/bolting commands from a dedicated server board, and acknowledges reception sending back a response heartbeat packet containing information about the overall robot status, e. g. electrical current and voltage values, target and actual angles, operating mode, fault status. Whenever a motion command is sent, the motion planning section of the firmware determines the current robot configuration, using Inertial Measurement Unit readings and the motors Pulse Width Modulation values. Afterwards, it calculates the list of primitives needed to reach the target state, and controls their execution in the proper order. MMIC-I can receive and execute motion and bolting commands only when it is in operational mode. MMIC-I has three operating modes: standby, operational and safed. Standby mode is automatically entered upon startup. While in standby mode, all motors are powered off, and the only accepted commands are the ones relative to a change of mode and heartbeat packet request. Fault detection causes the robot to automatically enter safed or standby mode. Whenever the detected fault occurs within a motion and requires immediate intervention, e. g. an over-current situation, the robot enters safed mode. Safed mode powers off all motors except for the locomotion module, thus preventing the robot from collapsing. Conversely, when the detected fault doesn't require immediate intervention (low battery warning, for instance), the robot enters standby mode after completing the ongoing motion. This paper provides a detailed discussion of MMIC-I's firmware architecture. It accurately describes the implementation approach for each module: sensor data reading, motor control and actuation, WiFi server-client communication, intra-boards Serial communication, operating modes and autonomous fault detection, motion planning, coordination and execution, etc. Moreover, in support of the software description, this paper includes a thorough characterization of MMIC-I's hardware and avionics.

In-space assembly↗

NASA NTRS1974

MSFC Skylab Apollo Telescope Mount thermal control system mission evaluation

The Skylab Saturn Workshop Assembly was designed to expand the knowledge of manned earth orbital operations and accomplish a multitude of scientific experiments. The Apollo Telescope Mount (ATM), a module of the Skylab Saturn Workshop Assembly, was the first manned solar observatory to successfully observe, monitor, and record the structure and behavior of the sun outside the earth's atmosphere. The ATM contained eight solar telescopes that recorded solar phenomena in X-ray, ultraviolet, white light, and hydrogen alpha regions of the electromagnetic spectrum. In addition, the ATM contained the Saturn Workshop Assembly's pointing and attitude control system, a data and communication system, and a solar array/rechargeable battery power system. This document presents the overall ATM thermal design philosophy, premission and mission support activity, and the mission thermal evaluation. Emphasis is placed on premission planning and orbital performance with particular attention on problems encountered during the mission. ATM thermal performance was satisfactory throughout the mission. Although several anomalies occurred, no failure was directly attributable to a deficiency in the thermal design.

Hueter, U.↗

NASA NTRS1991

Thermal control surfaces experiment (SOO69) flight systems performance

The thermal control surfaces experiment (TCSE) was the most complex hardware system aboard the Long Duration Exposure Facility (LDEF). The TCSE system consists of a scanning spectroreflectometer that measured test samples mounted on a rotatable carousel assembly. A microprocessor based data system controlled all aspects of TCSE system operation. Power was provided by four primary batteries. Flight measurement and housekeeping data were stored on a tape recorder for postflight analysis. The TCSE is a microcosm of complex electro-optical payloads being developed by NASA, DoD, and the aerospace community. The TCSE provides valuable data on the performance of these systems in space. The TCSE flight system and its excellent performance on the LDEF mission are described. A few operational anomalies were encountered and are discussed. Initial post-flight tests show that the TCSE system remains functional although some degradation in the optical measurements were observed. The results of these tests are also presented.

Wilkes, Donald R.↗

NASA NTRSDate not supplied

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

In engineering and aerospace applications, it is vital to operational success to have insight into the expected performance and health of physical systems. The field of prognostics and health management provides quantitative methods for monitoring, predicting, and managing system health. Prognostics algorithms can be employed to assess the current state of a system, propagate the system throughout time, and predict potential anomalies or failures that may occur. While they can provide accurate prediction results, effective prognostics algorithms can be challenging to use in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for future remaining useful life predictions. In this work, we implement new algorithmic approaches for prediction, quantitatively compare them via a battery degradation use-case, and provide recommendations of potential improvements to a prognostics framework. One approach to prediction is through sampling, whereby the current state of a physical system is sampled many times and each sample is propagated forward until failure is reached, resulting in a distribution of failure values. To improve the efficiency of this process, we implemented five new algorithmic approaches to prediction, including three distinct sampling methods (standard Monte Carlo, Quasi-Monte Carlo, and Latin Hypercube Sampling), a variable time step algorithm, and a variable sample size algorithm. To compare the algorithms, we employ a variety of metrics designed specifically to analyze both computational efficiency and model accuracy. Our metrics include accuracy to compare the average predicted value to ground truth, mean absolute deviation to illustrate dispersion, specific percentile error to describe accuracy within a user-defined risk tolerance, and code run-time. To quantitatively analyze our results, we employ a use-case of degradation of a Lithium-ion battery. We use an electrochemistry-based model to describe the current health state of the battery, and implement our prediction algorithms to propagate forward in time until end-of-discharge (EOD) is reached. Notably, through this work it was found that none of our sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. We find that while the sampling methods are unique, the distributions they generate are similar, ultimately producing final predictions that are nearly identical. In exploring the effect of the time step within the prediction algorithm, we found that prediction accuracy was highly dependent on the time step used, and that implementing a variable time step within a particular prediction may provide an increase in computational efficiency while also maintaining prediction accuracy. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment can result in improved computation speed and maintained prediction accuracy. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency.

prognostics↗