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DOE OSTI2025

Three-dimensional reconstruction of inertial confinement fusion hot-spot plasma from x-ray and nuclear diagnostics on OMEGA

Multidimensional effects degrade the neutron yield and the compressed areal density of laser-direct-drive inertial confinement fusion implosions of layered deuterium–tritium cryogenic targets on the OMEGA Laser System with respect to 1D radiation-hydrodynamic simulation predictions. A comprehensive physics-informed 3D reconstruction effort is under way to infer hot-spot and shell conditions at stagnation from four x-ray and seven neutron detectors distributed around the OMEGA target chamber. Neutron diagnostics, providing measurements of the neutron yield, hot-spot flow velocity, and apparent ion-temperature distribution, are used to infer the mode-1 perturbation at stagnation. The x-ray imagers record the shape of the hot-spot plasma to diagnose mode-1 and mode-2 perturbations. A deep-learning convolutional neural network trained on an extensive set of 3D radiation-hydrodynamic simulations is used to interpret the x-ray and nuclear measurements to infer the 3D profiles of the hot-spot plasma conditions and the amount of laser energy coupled to the hot-spot plasma. A 3D simulation database shows that larger mode-1 asymmetries are correlated with higher hot-spot flow velocities and reduced laser-energy coupling and neutron yield. Three-dimensional hot-spot reconstructions from x-ray measurements indicate that higher amounts of residual kinetic energy are correlated with higher measured hot-spot flow velocities, consistent with 3D simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Root Cause Analysis of Degradation in Protonic Ceramic Electrochemical Cell with Interfacial Electrical Sensors Using Data‐Driven Machine Learning

Abstract Protonic ceramic electrochemical cells (PCECs) offer promising paths for energy storage and conversion. Despite considerable achievements made, PCECs still face challenges such as physiochemical compatibility between componenets and suboptimal solid–solid contact at the interfaces between the electrolytes and electrodes. In this study, a novel approach is proposed that combines in situ electrochemical characterization of interfacial electrical sensor embedded PCECs and machine learning to quantify the contributions of different cell components to total degradation, as well as to predict the remaining useful life. The experimental results suggest that the overpotential induced by the oxygen electrode is 48% less than that of oxygen electrode/electrolyte interfacial contact for up to 1171 h. The data‐driven machine learning simulation predicts the RUL of up to 2132 h. The root cause of degradation is overpotential increase induced by oxygen electrode, which accounts for 82.9% of total cell degradation. The success of the failure diagnostic model is demonstrated by its consistency with degradation modes that do not manifest in electrolysis fade during early real operations. This synergistic approach provides valuable insights into practical failure diagnosis of PCECs and has the potential to revolutionize their development by enabling improved performance prediction and material selection for enhanced durability and efficiency.

25 ENERGY STORAGE↗

NASA NTRS2019

Health Management and Prognostics for Electric Aircraft Powertrain

W and c Any air borne vehicle needs incorporating safety as key parameter of measure, and inclusion of autonomy raises the critical need for safety under autonomous operations. Management of faults and component degradation is key as complexity in autonomous operations grow over the period of time. Therefore, in addition to basic operational requirements, an autonomous electric vehicle should be able to make accurate estimates of its current system health and take the correct decisions to complete its mission successfully. Real-time safety and state-awareness tools are therefore essential for the vehicle to be able to reach its destination in a safe and successful manner. The need for safety assurance and health management capabilities is particularly relevant for aircraft electric propulsion systems, which are relatively new and with limited historical to learn. They are critical systems requiring high power density along with reliability, resilience, efficient management of weight, and operational costs. A model- based fault diagnosis and prognostics approach of complex critical systems can successfully accomplish the safety and state awareness goal for such electric propulsion systems, enabling autonomous decision making capability for safe and efficient operation. To identify critical components in the system a Qualitative Bayesian approach using FMECA is implemented. This requires the assessment of some quantities representing the state of the electric unmanned aerial systems (e-UAS), as well as look-ahead forecasts of such states during the entire flight, presented in form of safety metrics (SM). In-service data and performance data gathered from degraded components sup- ports diagnostic and prognostic methods for these systems, but this data can be difficult to obtain as weight and packaging restrictions reduce redundancy and instrumentation on-board the vehicle. Therefore, an model-based framework should be capable or operating with limited data. In addition to data scarcity, the variability of such complex critical systems re- quires the model-based framework to reason in the presence of uncertainty, such as sensor noise, and modeling imperfections. Quantification of errors and uncertainties in the measured states and quantities is therefore a fundamental step for a precise estimation of such SMs; un-modeled uncertainty may result in erroneous state assessment and un- reliable predictions of future states of e-UAVs. Typical, centralized model-based schemes suffer from inherent disadvantages such as computational complexity, single point of failure, and scalability issues, and therefore may fail in such a complex scenario. This paper presents a methodology for developing a system level diagnostics and prognostics approach using a Qualitative Bayesian FMECA approach along with a formal uncertainty management framework for an e-UAS. In this work we demonstrate the efficacy of the framework to predict effects of sub-system level degradation on vehicle operation incorporating uncertainty management to predict future behavior under different operating conditions.

Kulkarni, Chetan↗

DOE OSTI2025

Demonstration of a Novel Radiochemical Mix Diagnostic for Fusion Implosions at the National Ignition Facility

Mixing of the ablator material into the fuel of an inertial confinement fusion implosion reduces compression and enhances radiative losses, preventing ignition. Here, we describe a novel use of charged-particle radiochemistry to measure the ablator mix in contact with the fusion hot spot. The capsule uses a graded Be-Cr layer to increase the confinement of the hot spot. 52 Mn and 51 Cr isotopes are collected from the implosion and counted, and the ratio is related to the amount of Cr mixed into the hot spot. Thus, a new diagnostic to determine the degradation due to mix on fusion implosions has been developed.

MacLaren, S. A. [Lawrence Livermore National Labor↗

DOE OSTI2026

Open-Air Manufacturing of Efficient Large-Area Perovskite Solar Cells to Meet Stability and Cost Targets

This SETO-funded project (DE-EE0009516) developed a fully open-air manufacturing pathway for perovskite solar cells and modules, eliminating vacuum-based processing steps while improving device stability. Open-air ultrasonic spray deposition, solution combustion synthesis, rapid thermal processing, and atmospheric plasma curing were developed and optimized for all functional device layers — perovskite absorber, hole transport layers (HTLs), electron transport layers (ETLs), transparent conducting oxides (TCOs), and rear electrodes — without reliance on vacuum. Sprayed organic ETLs preserved perovskite crystal structure and enabled power conversion efficiencies exceeding 20%, and open-air processed TCOs and rear electrodes achieved optoelectronic performance comparable to sputtered alternatives at substantially lower manufacturing cost. Device stability was assessed through accelerated aging protocols aligned with IEC and ISOS standards, combined with high-throughput optical diagnostics that identified key degradation mechanisms and antagonistic interactions among heat, humidity, and illumination stressors. A comprehensive technoeconomic analysis quantified the cost and throughput advantages of open-air manufacturing over conventional vacuum-based processes, identifying vacuum deposition as the dominant cost driver and demonstrating a clear pathway toward the $0.02/kWh target. The project produced five peer-reviewed journal publications, eleven conference presentations, two patents/applications, and five Ph.D. dissertations.

14 SOLAR ENERGY↗

DOE OSTI2021

Degradation mechanisms and partial shading of glass-backsheet and double-glass photovoltaic modules in three climate zones determined by remote monitoring of time-series current–voltage and power datastreams

Degradation and partial shading impact the long-term reliability and power production of photovoltaic (PV) modules and power plants. Time-series power (P mp ) and current–voltage (I-V) curve datastreams from PV modules enable a remote diagnostic approach to quantify active degradation mechanisms and identify partial shading. We study three to nine years of these datastreams, including 3.6 million P mp I-V curves and 36 million values, from eight PV modules, four each of double-glass and glass-backsheet module architectures, located in three distinctly different Köppen-Geiger climate zones, to determine the module’s performance loss rates (PLR), identify active degradation mechanisms and power loss modes, along with partial shading by local objects. Considering both module architectures, PLR results indicate that the BSh climate zone is the most aggressive for module degradation, while the Alpine ET zone is the mildest climate. PLR of double-glass modules located in BWh and BSh climate zones are different due to the significantly greater uniform current loss (ΔP Isc ) for double-glass modules in BSh, at a 5% significance level. Power loss for four out of five modules located in the BWh and BSh climates are dominated by uniform current degradation. Statistical analysis of multistep I-V curves detects partial shading experienced by three studied modules with details of the shading profile, the shading Poynting vector diagram for the obstacle’s relative position, shading scenarios, and duration. Lastly, this work demonstrates how remote monitoring and diagnosis of P mp & I-V time-series of modules can provide quantitative operations and maintenance insights into system performance, degradation mechanisms, and shading.

14 SOLAR ENERGY↗

NASA NTRS2006

Hybrid Kalman Filter: A New Approach for Aircraft Engine In-Flight Diagnostics

In this paper, a uniquely structured Kalman filter is developed for its application to in-flight diagnostics of aircraft gas turbine engines. The Kalman filter is a hybrid of a nonlinear on-board engine model (OBEM) and piecewise linear models. The utilization of the nonlinear OBEM allows the reference health baseline of the in-flight diagnostic system to be updated to the degraded health condition of the engines through a relatively simple process. Through this health baseline update, the effectiveness of the in-flight diagnostic algorithm can be maintained as the health of the engine degrades over time. Another significant aspect of the hybrid Kalman filter methodology is its capability to take advantage of conventional linear and nonlinear Kalman filter approaches. Based on the hybrid Kalman filter, an in-flight fault detection system is developed, and its diagnostic capability is evaluated in a simulation environment. Through the evaluation, the suitability of the hybrid Kalman filter technique for aircraft engine in-flight diagnostics is demonstrated.

Kobayashi, Takahisa↗

NASA NTRS2002

Performance characteristics of the deep space 1 flight spare ion thruster long duration test, the first 21,300 hours of operation

A long duration test of the DSl flight spare ion thruster (FT2) is presently being conducted at the Jet Propulsion Laboratory. To, date the thruster has accumulated over 23,500 hours of operation, and 190 kg of Xenon propellant, over 230% of the initial design life. The primary objectives of the test include the processing of 200 kg of Xenon propellant, the identification of unknown failure modes, the characterization and drivers of these failure modes, and to measure performance degradation as the thruster wears. The test is fitted with an extensive array of diagnostics to measure engine wear and performance degradation. To date the most notable erosion processes include severe discharge cathode keeper erosion, accelerator grid erosion, reduction in electrical isolation of the neutralizer assembly, and deposit formation within the neutralizer orifice, reducing margin from plume mode. Over the past 23,500 hours of operation, performance degradation has been minimal, and it is anticipated that the above erosion processes will not preclude the thruster from processing over 200 kg of Xenon.

ion thrusters deep space one↗

NASA NTRS2012

Saliva Preservative for Diagnostic Purposes

Saliva is an important body fluid for diagnostic purposes. Glycoproteins, glucose, steroids, DNA, and other molecules of diagnostic value are found in saliva. It is easier to collect as compared to blood or urine. Unfortunately, saliva also contains large numbers of bacteria that can release enzymes, which can degrade proteins and nucleic acids. These degradative enzymes destroy or reduce saliva s diagnostic value. This innovation describes the formulation of a chemical preservative that prevents microbial growth and inactivates the degradative enzymes. This extends the time that saliva can be stored or transported without losing its diagnostic value. Multiple samples of saliva can be collected if needed without causing discomfort to the subject and it does not require any special facilities to handle after it is collected.

Pierson, Duane L.↗

DOE OSTI2025

Diagnostic-free onboard battery health assessment

Diverse usage patterns induce complex and variable aging behaviors in lithiumion batteries, complicating accurate health diagnosis and prognosis. Separate diagnostic cycles are often used to untangle the battery’s current state of health from prior complex aging patterns. However, these same diagnostic cycles alter the battery’s degradation trajectory, are time-intensive, and cannot be practically performed in onboard applications. Here, in this work, we leverage portions of operational measurements in combination with an interpretable machine learning model to enable rapid, onboard battery health diagnostics and prognostics without offline diagnostic testing and the requirement of historical data. We integrate mechanistic constraints within an encoder-decoder architecture to extract electrode states in a physically interpretable latent space and enable improved reconstruction of the degradation path. The health diagnosis model framework can be flexibly applied across diverse application interests with slight fine-tuning.

battery aging reconstruction↗

DOE OSTI2020

Improved core-edge compatibility using impurity seeding in the small angle slot (SAS) divertor at DIII-D

Impurity seeding studies in the slot divertor (SAS) at DIII-D have revealed a strong relationship between the detachment onset and pedestal characteristics with both target geometry and impurity species. N 2 seeding in the slot has led to the first simultaneous observation of detachment on the entire suite of boundary diagnostics viewing the SAS without degradation of core confinement. SOLPS-ITER simulations with D+C+N, full cross-field drifts and n-n collisions activated are performed for the first time in DIII-D to interpret the behavior. This illustrates a strong effect of divertor configuration and plasma drifts on the recycling source distribution with significant consequences on plasma flows. Flow reversal is found for both main ions and impurities affecting strongly the impurity transport and providing an explanation for the observed dependence on strike point location of the detachment onset and impurity leakage found in the experiments. Matched discharges with either nitrogen or neon injection show that while nitrogen does not significantly affect the pedestal, neon leads to increased pedestal pressure gradient and improved pedestal stability. Little nitrogen penetrates in the core, but a great amount of neon is found in the pedestal consistent with the different ionization potentials of the two impurities. This research demonstrates that neutral and impurity distributions in the divertor can be controlled through variations in strike point locations in a fixed baffle structure. Divertor geometry combined with impurity seeding enables mitigated divertor heat flux balancing core contamination and thus leading to enhanced divertor dissipation and improved core-edge compatibility which are essential for ITER and for future fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2012

Implementation of an Integrated On-Board Aircraft Engine Diagnostic Architecture

An on-board diagnostic architecture for aircraft turbofan engine performance trending, parameter estimation, and gas-path fault detection and isolation has been developed and evaluated in a simulation environment. The architecture incorporates two independent models: a realtime self-tuning performance model providing parameter estimates and a performance baseline model for diagnostic purposes reflecting long-term engine degradation trends. This architecture was evaluated using flight profiles generated from a nonlinear model with realistic fleet engine health degradation distributions and sensor noise. The architecture was found to produce acceptable estimates of engine health and unmeasured parameters, and the integrated diagnostic algorithms were able to perform correct fault isolation in approximately 70 percent of the tested cases

Armstrong, Jeffrey B.↗

NASA NTRS1993

Ground-based simulation of LEO environment: Investigations of a select LDEF material: FEP Teflon (trademark)

The Long Duration Exposure Facility (LDEF) has produced a wealth of data on materials degradation in the low earth orbit (LEO) space environment and has conclusively shown that surface chemistry (as opposed to surface physics-sputtering) is the key to understanding and predicting the degradation of materials in the LEO environment. It is also clear that materials degradation and spacecraft contamination are closely linked and that the fundamental mechanisms responsible for this linking are in general not well understood especially in the area of synergistic effects. The study of the fundamental mechanisms underlying materials degradation in LEO is hampered by the fact that the degradation process itself is not observed during the actual exposure to the environment. Rather the aftermath of the degradation process is studied, i.e., the material that remains after exposure is observed and mechanisms are proposed to explain the observed results. The EOIM-3 flight experiment is an attempt to bring sophisticated diagnostic equipment into the space environment and monitor the degradation process in real time through the use of mass spectrometry. More experiments of this nature which would include surface sensitive diagnostics (Auger and photoelectron spectroscopes) are needed to truly unravel the basic chemical mechanisms involved in the materials degradation process. Since these in-space capabilities will most likely not be available in the near future, ground-based LEO simulation facilities employing sophisticated diagnostics are needed to further advance the basic understanding of the materials degradation mechanisms. The LEO simulation facility developed at Los Alamos National Laboratory has been used to investigate the atomic oxygen/vacuum ultraviolet (AO/VUV) enhanced degradation of FEP Teflon. The results show that photo-ejection of polymer fragments occur at elevated temperature (200 C), that VUV synergistic rare gas sputtering of polymer fragments occur even at 25 C, and that combined OA/VUV interaction produces a wide variety of gas phase reaction products.

Cross, Jon B.↗

DOE OSTI2020

In situ Diagnostics of Coupled Electrochemical-Mechanical Properties of Solid Electrolyte Interphases on Lithium Metal Rechargeable Batteries (Final Technical Report)

The fundamental understanding of the coupled mechanical/chemical degradation of the SEI layer during lithium cycling will enable the project to identify the desirable mechanical properties on SEI/lithium as a system and the specific transport properties that enable the homogenous lithium stripping/plating while avoiding the mossy structure. Furthermore, it will allow the project to develop a highly impactful strategy to protect lithium metal and achieve dendrite free high cycle efficiency, which can dramatically increase the energy density of lithium batteries for EV applications. During past three years, four coherent steps have been taken to solve the coupled mechanical and electrochemical degradation: (1) Developed a comprehensive set of in-situ diagnostic techniques to investigate the coupled mechanical/chemical properties of SEI layer and its impact on lithium striping/plating. (2) Identified failure mechanisms of SEI/Li as a whole electrode system using in-situ electrochemical tools. (3) Established a design strategy of protective coatings on Li metal to extend the cycle life Li meal electrode. (4) Developed novel surface coatings as the artificial SEI layer to protect Li metal and significantly extend cycle life. During past 3-year budget period, we have published over 16 peer-reviewed paper, filed 7 patents, and given over 30 invited talks. 5 graduated students and 2 postdocs were supported by this project.

36 MATERIALS SCIENCE↗

NASA NTRS1981

CF6 High Pressure Compressor and Turbine Clearance Evaluations

In the CF6 Jet Engine Diagnostics Program the causes of performance degradation were determined for each component of revenue service engines. It was found that a significant contribution to performance degradation was caused by increased airfoil tip radial clearances in the high pressure compressor and turbine areas. Since the influence of these clearances on engine performance and fuel consumption is significant, it is important to accurately establish these relatonships. It is equally important to understand the causes of clearance deterioration so that they can be reduced or eliminated. The results of factory engine tests run to enhance the understanding of the high pressure compressor and turbine clearance effects on performance are described. The causes of clearance deterioration are indicated and potential improvements in clearance control are discussed.

Radomski, M. A.↗

NASA NTRS2004

Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control modes that are selected according to some performance or operational criteria. As the engine degrades, parameters shift from their nominal values. Thus, when a new control mode is swapped in, a variable that is being brought under control might have an excessive initial error. The new adaptive algorithm adjusts the controller gains on the basis of the level of degradation to minimize the disruptive influence of the large error on other variables and to recover the desired thrust response.

Litt, Jonathan S.↗

DOE OSTI2024

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Abstract Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

25 ENERGY STORAGE↗

DOE OSTI2020

Understanding asymmetries using integrated simulations of capsule implosions in low gas-fill hohlraums at the National Ignition Facility

Current capsule implosions at the National Ignition Facility (NIF) using high-density-carbon ablators and laser energies close to 2 MJ have shown neutron yields in excess of 50 kJ. Improving on this performance requires understanding of the different degradation mechanisms. For many NIF implosions, nuclear diagnostic signatures have inferred residual hot-spot velocities that correlate with fuel areal density variations consistent with a low-order mode-1 asymmetry. A current working hypothesis attributes these asymmetries to a combination of beam to beam variations in the laser delivery and possibly coupling to target features, such as the diagnostic holes needed for x-ray imaging. Recently, a new source has been identified, thickness variation in the ablator shell. To gain better understanding and eventually mitigate the causes of <ρR> asymmetries, 3D integrated simulations using the actual delivered laser powers are needed. To capture the effect of the diagnostic holes (DHs) using direct numerical simulation would require significantly large computational resources. Instead, our 3D simulations make use of a subgrid model developed using highly-resolved 2D simulations that include several details of the DH engineering complexity. Simulations of NIF shots using hohlraums without DHs, to isolate the effect of beam-to-beam variations, reproduce fairly well the observed nuclear diagnostic signatures. Similarly, reasonable agreement between data and simulations is also obtained in the presence of diagnostic holes. To account for the remaining discrepancies a sensitivity study of ablator thickness variation showed that 1% thickness asymmetries are comparable in effect to 1% peak drive mode-1 asymmetries. Furthermore, this study identified sensitivity to variations in the imbedded doped layer (needed to shield the DT ice from the high energy x-rays generated in the hohlraum) thickness even when the inner and outer surface of the ablator are perfectly spherical.

radiation hydrodynamics↗