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At least 541 records · Page 30

Cruise Propulsion System Thermal Analysis for NASA’s X-57 “Maxwell” Mod II Configuration

The X-57 “Maxwell” is NASA’s flight demonstrator for distributed electric propulsion technologies. The X-57 Mod II configuration is designed to test the electric cruise propulsion system for X-57 and features an electric cruise motor mounted in an integral nacelle on each wing. The electric motors and associated control equipment for X-57 Mod II are air-cooled; therefore, they require adequate cooling airflow to stay within temperature limits in all relevant flight conditions within the operational ambient temperature limits set by the X-57 project. A computational flow analysis was conducted to estimate the internal flow properties of the X-57 Mod II cruise nacelles in three critical flight conditions. These flow properties were then used to determine the boundary conditions for individual component thermal models, which were used to estimate individual component operating temperatures. The results indicated that the low-speed, low-altitude initial takeoff climb during hot day conditions was the sizing condition from a cooling perspective. The analysis found that the cooling flowpaths in the X-57 Mod II cruise nacelles are adequate to provide cooling to all components with the appropriate amount of thermal margin except two of the low-voltage control boards in the cruise motor controller. These components would violate required thermal margins by less than two degrees Celsius in the Project Hot Day reference atmosphere.

Nicholas K Borer↗

Dynamic Modeling of Power Conversion Stages for an Exascale Supercomputer

In this paper a power conversion and energy consumption model for an exascale supercomputer is investigated. Power consumption, energy loss and efficiency are derived for the 27.2 MW liquid-cooled, centralized, High Performance Computing (HPC) power system, which is supplied directly from the 480 V three-phase mains. Two energy conversion stages are analyzed, measured and modeled. The model is developed in order to be adapted and implemented in a digital twin platform utilizing a Resource Allocator and Power Simulator (RAPS) module. RAPS enables estimation of potential energy savings in the direct AC power supply architecture via both conventional rectifier load sharing (commonly used in HPC systems), as well as smart rectifier load sharing. Moreover, besides the direct AC supply architecture analysis, the full direct DC supply architecture with with 1 kV DC bus were also studied. Comparison of 10 hour time frame operation of the system, with direct 480 V AC voltage supply with conventional and smart load sharing and medium dc voltage supply were done. For the direct AC supply architecture, with conventional and smart load sharing the predicted power loss was approximately 840 kW and 820 kW, respectively and the predicted total system efficiency was 92.87% and 93.05%, respectively. For the direct DC supply architecture with the 1000 V DC supply bus power loss was approximately 340 kW and the predicted total system efficiency was 97.02%.

Wojda, Rafal↗

The Value of Increased HVDC Capacity Between Eastern and Western U.S. Grids: The Interconnections Seam Study

The Interconnections Seam Study examines the potential economic value of increasing electricity transfer between the Eastern and Western Interconnections using high-voltage direct-current (HVDC) transmission and cost-optimizing both generation and transmission resources across the United States, proposing, assessing, justifying, and illustrating a major infrastructure change involving two of the worlds largest power grids. The study conducted a multi-model analysis that used co-optimized generation and transmission expansion planning and production cost modeling. Four transmission designs under eight scenarios were developed and studied to estimate costs and potential benefits. The results show benefit-to-cost ratios that reach as high as 2.5, indicating significant value to increasing the transmission capacity between the interconnections under the cases considered, realized through sharing generation resources and flexibility across regions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thin-film chemical expansion of ceria based solid solutions: laser vibrometry study

The chemical expansion of Pr 0.1 Ce 0.9 O 2-δ (PCO) and CeO 2-δ thin films is investigated in the temperature range between 600 °C and 800 °C by laser Doppler vibrometry (LDV). It enables non-contact determination of nanometer scale changes in film thickness at high temperatures. The present study is the first systematic and detailed investigation of chemical expansion of doped and undoped ceria thin films at temperatures above 650 °C. The thin films were deposited on yttria stabilized zirconia substrates (YSZ), operated as an electrochemical oxygen pump, to periodically adjust the oxygen activity in the films, leading to reversible expansion and contraction of the film. This further leads to stresses in the underlying YSZ substrates, accompanied by bending of the overall devices. Film thickness changes and sample bending are found to reach up to 10 and several hundred nanometers, respectively, at excitation frequencies from 0.1 to 10 Hz and applied voltages from 0–0.75 V for PCO and 0–1 V for ceria. At low frequencies, equilibrium conditions are approached. As a consequence maximum thin-film expansion of PCO is expected due to full reduction of the Pr ions. The lower detection limit for displacements is found to be in the subnanometer range. At 800 °C and an excitation frequency of 1 Hz, the LDV shows a remarkable resolution of 0.3 nm which allows, for example, the characterization of materials with small levels of expansion, such as undoped ceria at high oxygen partial pressure. As the correlation between film expansion and sample bending is obtained through this study, a dimensional change of a free body consisting of the same material can be calculated using the high resolution characteristics of this system. A minimum detectable dimensional change of 5 pm is estimated even under challenging high-temperature conditions at 800 °C opening up opportunities to investigate electro-chemo-mechanical phenomena heretofore impossible to investigate. The expansion data are correlated with previous results on the oxygen nonstoichiometry of PCO thin films, and a defect model for bulk ceria solid solutions is adopted to calculate the cation and anion radii changes in the constrained films during chemical expansion. The constrained films exhibit anisotropic volume expansion with displacements perpendicular to the substrate plane nearly double that of bulk samples. The PCO films used here generate high total displacements of several 100 nm’s with high reproducibility. Consequently, PCO films are identified to be a potential core component of high-temperature actuators. They benefit not only from high displacements at temperatures where most piezoelectric materials no longer operate while exhibiting, low voltage operation and low energy consumption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ARPA-E PNDIODES "PN Junctions by Ion Implantation" Project (Final Report)

Electricity accounts for nearly 40% of the energy generated in the United States, of which 65% is lost to electrical system inefficiency before reaching end-use sectors. Power electronics will play a growing role in this distribution and end-use, with up to 80% of electricity estimated to pass through power electronics from generation to consumption by 2030. This gives technical improvements in power electronics enormous potential to drive efficiency gains throughout the U.S. economy. Current Si-based power architectures including MOSFETs and IGBTs are limited by high losses, low switching frequency, and poor high-temperature performance. Given the material properties of GaN, devices can exhibit a given turn-on resistance and breakdown voltage with a minute fraction of the area of a Si device—all with higher switching speeds. While n-type doping of III-nitrides has reached a high level of maturity and integration into commercialized products, p-type doping presents distinct challenges that requires continued research. The success of the next generation of GaN-based power devices depends in large part on the ability to form selective-area p-type regions, which can be accomplished by ion implantation of the prevailing acceptor dopant, Mg. This approach is relatively inexpensive and is a fab-ready processing step for creation of current-generation power electronic devices including BJTs, IGBTs, and diode rectifiers. However, ion implantation induces lattice damage and creates point defects within the material, which negatively impacts dopant activation annealing. These forms of damage may be removed by high-temperature annealing, however short annealing time and higher pressures are required to prevent decomposition of the material. We approach this challenge through an innovative combination of approaches toward obtaining high-conductivity p-type GaN. By the novel employment of a gyrotron, a microwave source that can be shaped into a highly localized beam to dissipate very high power in a semiconductor target, a wafer of GaN can be annealed in short (<2 s) ‘pulses’ at temperatures of 1450 °C (2640 °F) to achieve p-type activation without appreciable surface degradation. The p-type activation of Mg-implanted GaN can be further aided by co-implantation with N, believed to enhance the removal of point defects that compensate the acceptors dopant. Elevation to such high temperatures for even a short time induces degradation of GaN-to overcome, we have implemented additional measures to retain high-quality crystalline GaN while removing implant damage and activating Mg dopant. A bilayer cap of AlN is deposited by a combination of chemical and physical vapor deposition to protect the GaN surface. To prevent decomposition of GaN loss of N during annealing, a custom vessel—to contain pressurized N while allowing injection of microwave energy—is employed. By detailed study of the interaction of various measures that are implemented to protect the sample surface (GaN), activate the implanted dopants, and mitigate damage of the lattice heating damage during annealing, we are able to achieve p-type GaN and observe recovery of the crystal and removal of substantial density of defects created during the implantation process.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cost estimates of production scale semitransparent organic photovoltaic modules for building integrated photovoltaics

Building integrated photovoltaics (BIPVs) are attached to commercial and residential structures to enable solar energy harvesting. While conventional Si photovoltaics (PVs) are dominant in the current market, second and third generation thin film solar cells based on amorphous Si, CdTe, CIGS, perovskites or organic photovoltaics (OPVs) are often considered as an alternative for BIPV applications since they may offer reduced costs compared to Si PVs. Indeed, recent advances in performance suggest that lightweight, flexible and visibly transparent OPVs can potentially be integrated into windows or other applications to which Si PVs are less well suited. Here, we estimate the cost of high efficiency, semitransparent OPVs (ST-OPVs) based on solution processing in a roll-to-roll (R2R) manufacturing line. Assuming modules with 10% power conversion efficiency (PCE), a 70% geometric fill factor (GFF), and 95% inverter efficiency, we anticipate a %1.6 per Wp module manufacturing cost that includes the cost of the microinverter to condition the OPV dc output to be compatible with the ac line voltage of the building. The materials and inverter cost comprise ~90% of the total module cost. Hence, with simplified material synthesis and a lower inverter cost, including marginally improved PCE and GFF, we expect the cost can be as low as $0.47 per Wp. Here, while the module costs ~60% of the average (uninstalled) double-pane window, we expect the payback period can be as short as 2 to 6 years, suggesting that OPVs can be an economic and attractive candidate for BIPV applications.

14 SOLAR ENERGY↗

Portable Soft X-Ray Diagnostics for Transformative Fusion-Energy Concepts (Final Scientific/Technical Report)

A time-gated extreme-ultraviolet spectrometer was fielded on a transformative fusion-energy device, FuZE-Q at Zap Energy, Inc. (ZEI), a sheared-flow-stabilized z-pinch. Plasma emission spectra were collected in the 5–40 nm wavelength (30–250 eV) range. This was the first time a direct-vacuum-coupled, high-voltage, deposition-sensitive diagnostic was fielded on this type of dense-plasma fusion device. To overcome the special challenges of such a coupling, a unique, highly effective implementation was developed, with fast (10-ns risetime) pulsed high-voltage electronics and a multi-stage differential pumping system. This enabled the UNR spectrometer to collect three independently timed spectra per FuZE-Q shot while also protecting sensitive internal components. Analysis of line emission identified oxygen (N-, C-, B-, Be-, Li-, and He-like O), peaking in intensity shortly after maximum current (>500 kA). Spectral databases and collisional-radiative modeling have been used to identify impurities and estimate edge-plasma temperatures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Applying Particle Swarm Optimization and Extended Kalman Filtering to Model Kaplan Generation Dynamics for Hydropower Systems

Variable renewable generation is increasing the need for hydropower plants to provide fast and flexible grid support, which places new demands on plant-level dynamic models used for monitoring, control, and operational decision-making. This need is especially important for hydroelectric systems, where turbine and generator dynamics are strongly coupled, nonlinear, and time-varying, making accurate real-time representation difficult. To address this problem, this paper develops a digital twin (DT) framework for a synchronous generator–Kaplan turbine system using an explicit separation of slow turbine dynamics and fast generator dynamics. The turbine subsystem is represented by a six-coefficient model, whose parameters are identified offline using particle swarm optimization, while the generator subsystem is updated online through an extended Kalman filter for real-time state and parameter estimation. These models are integrated within a closed-loop simulation that includes a proportional–integral–derivative–double-derivative governor and excitation system, allowing the DT to track plant behavior under realistic operating conditions. Unlike prior studies that treat turbine and generator modeling separately or rely mainly on simulated inputs, the proposed framework is validated using real operational data from a hydropower plant. Results show that the DT reproduces terminal voltage, active power, and reactive power with a normalized root mean square error of approximately 5%. This hybrid offline–online formulation constitutes the main contribution of the work, providing an adaptive and practically deployable DT for hydropower systems with direct relevance to control improvement, performance monitoring, and grid-support applications under high renewable penetration.

13 HYDRO ENERGY↗

Three dimensional space charge model for large high voltage satellites

High power solar arrays for satellite power systems with dimensions of kilometers, and with tens of kilovolts distributed over their surface face many plasma interaction problems that must be properly anticipated. In most cases, the effects cannot be adequately modeled without detailed knowledge of the plasma sheath structure and space charge effects. Two computer programs were developed to provide fully self consistent plasma sheath models in three dimensions as a result of efforts to model the experimental plasma sheath studies at NASA/JSC. Preliminary results indicate that for the conditions considered, the Child-Langmuir diode theory can provide a useful estimate of the plasma sheath thickness. The limitations of this conclusion are discussed. Some of the models presented exhibit the strong ion focusing observed in the JSC experiments.

Cooks, D.↗

New Technique of High-Performance Torque Control Developed for Induction Machines

Two forms of high-performance torque control for motor drives have been described in the literature: field orientation control and direct torque control. Field orientation control has been the method of choice for previous NASA electromechanical actuator research efforts with induction motors. Direct torque control has the potential to offer some advantages over field orientation, including ease of implementation and faster response. However, the most common form of direct torque control is not suitable for the highspeed, low-stator-flux linkage induction machines designed for electromechanical actuators with the presently available sample rates of digital control systems (higher sample rates are required). In addition, this form of direct torque control is not suitable for the addition of a high-frequency carrier signal necessary for the "self-sensing" (sensorless) position estimation technique. This technique enables low- and zero-speed position sensorless operation of the machine. Sensorless operation is desirable to reduce the number of necessary feedback signals and transducers, thus improving the reliability and reducing the mass and volume of the system. This research was directed at developing an alternative form of direct torque control known as a "deadbeat," or inverse model, solution. This form uses pulse-width modulation of the voltage applied to the machine, thus reducing the necessary sample and switching frequency for the high-speed NASA motor. In addition, the structure of the deadbeat form allows the addition of the high-frequency carrier signal so that low- and zero-speed sensorless operation is possible. The new deadbeat solution is based on using the stator and rotor flux as state variables. This choice of state variables leads to a simple graphical representation of the solution as the intersection of a constant torque line with a constant stator flux circle. Previous solutions have been expressed only in complex mathematical terms without a method to clearly visualize the solution. The graphical technique allows a more insightful understanding of the operation of the machine under various conditions.

Kenny, Barbara H.↗

Design Optimization Tool for Synthetic Jet Actuators Using Lumped Element Modeling

The performance specifications of any actuator are quantified in terms of an exhaustive list of parameters such as bandwidth, output control authority, etc. Flow-control applications benefit from a known actuator frequency response function that relates the input voltage to the output property of interest (e.g., maximum velocity, volumetric flow rate, momentum flux, etc.). Clearly, the required performance metrics are application specific, and methods are needed to achieve the optimal design of these devices. Design and optimization studies have been conducted for piezoelectric cantilever-type flow control actuators, but the modeling issues are simpler compared to synthetic jets. Here, lumped element modeling (LEM) is combined with equivalent circuit representations to estimate the nonlinear dynamic response of a synthetic jet as a function of device dimensions, material properties, and external flow conditions. These models provide reasonable agreement between predicted and measured frequency response functions and thus are suitable for use as design tools. In this work, we have developed a Matlab-based design optimization tool for piezoelectric synthetic jet actuators based on the lumped element models mentioned above. Significant improvements were achieved by optimizing the piezoceramic diaphragm dimensions. Synthetic-jet actuators were fabricated and benchtop tested to fully document their behavior and validate a companion optimization effort. It is hoped that the tool developed from this investigation will assist in the design and deployment of these actuators.

Gallas, Quentin↗

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.

rassor↗

Experimental Aging and Lifetime Prediction in Grid Applications for Large-Format Commercial Li-Ion Batteries

Due to the growth of electric vehicle and stationary energy storage markets, the production and use of lithium-ion batteries has grown exponentially in recent years. For many of these applications, large-format lithium-ion batteries are being utilized, as large cells have less inactive material relative to their energy capacity and require fewer electrical connections to assemble into packs. And especially for stationary energy storage systems, where energy delivered is the only revenue source, the economics of these battery systems is highly dependent on cell lifetime. However, testing of large-format lithium-ion batteries is time consuming and requires high current channels and large testing chambers, making information on the performance of commercial, large-format lithium-ion batteries hard to come by. Here, accelerated aging test data from four commercial large-format lithium-ion batteries is reported. These batteries span both NMC-Gr and LFP-Gr cell chemistries, pouch and prismatic formats, and a range of cell designs with varying power capabilities. Accelerated aging test results are analyzed to examine both cell performance, in terms of efficiency and thermal response under load, as well as cell lifetime. Cell thermal response is characterized by measuring temperature during cycle aging, which is used to calculated a normalized thermal resistance value that may help estimate both cell cooling needs or to help extrapolate aging test results to different thermal environments. Cell lifetime is evaluated qualitatively, considering simply the average calendar and cycle life across a range of conditions, as well as quantitatively, using statistical modeling and machine-learning methods to identify predictive aging models from the accelerated aging data. These predictive aging models are then used to investigate cell sensitivities to stressors, such as cycling temperature, voltage window, and C-rate, as well as to predict cell lifetime in various stationary storage applications. Results from this work show that cell lifetime and sensitivity to aging conditions varies substantially across commercial cells, necessitating testing for specific cell formats to make quantitative lifetime predictions. That being said, all commercial cells tested here are predicted to reach at least 10-year lifetimes for stationary storage applications. Based on the aging test results and modeling, some cells are expected to be relatively insensitive to temperature and use-case, making them suited for simple use cases with little or no thermal management and simple controls, while the lifetime of other cells could be extended to 20+ years if operated with thermal management and degradation-aware controls.

battery↗

NASA Physics of Failure (PoF) for Reliability

An item’s reliability or longevity is dependent not only on its design but also on how it is used, manufactured, tested, and the stresses it has or will experience. Stresses include operational and environmental exposures to thermal, voltage, current, age/exposure, mechanical, and radiation mechanisms. Therefore, in reliability analysis, it is important to consider the contributions of all these factors when predicting the failure rates of components. Historically, there has been a reliance on handbook data (e.g., MIL-HDBK-217), but experience has shown that these values and distributions are not representative of actual performance. Therefore, to make more credible reliability and risk assessments for its missions, NASA must transition to estimating likelihoods of failure based on an item’s reliability or longevity factors (or the physical susceptibilities and strengths impacting the design’s performance) has or will experience, whenever possible. To facilitate this transition, a Handbook on Methodology for Physics of Failure Based Reliability Assessments has been developed by NASA to assist in applying physics experiences or experimental physics for empirical analysis and conceptualized physics exposures or theoretical physics for deterministic analysis, to develop and aggregate realistic likelihoods of failure leading to more credible forecasts of item performance and longevity. In addition, since it is NASA’s intention that this document continues to evolve based on community lessons learned and the introduction of new assessment methodologies, NASA is encouraging and appreciates the contributions of current and future authors to maintain and enhance this handbook and its supporting case studies.

PoF↗

In-situ Testing to Acquire HR-EBSD and DIC Strain Data Within a Coincident Domain

For this project, an inked rubber stamp was applied to a small Inconel 625 specimen. The stamp transferred a thin pattern with microscale features for digital image correlation (DIC). The pattern is easily visible at lower voltages and thin enough to not obstruct backscattered electrons. The unique characteristics of the pattern enabled the concurrent acquisition of DIC and high-resolution electron backscatter diffraction (HR-EBSD) data while the specimen was loaded in-situ. The challenges of in-situ testing and combining EBSD with DIC measurements are discussed. By combining the elastic strains (from HR-EBSD) and total strains (from DIC) the result of this approach is an estimate of stress- strain behavior at points across the specimen surface. This combined dataset can then be used as higher-fidelity data in the calibration of crystal plasticity models.

Will Gilliland↗

Construction of Cryogen-Free 4.3T Superconducting Wiggler for NSLS-II Ring

With the 3 GeV electron beam energy for the National Synchrotron Light Source II (NSLS-II) ring, only superconducting wigglers (SCW) producing greater than 4T peak field can cover the photon energy range of 20 keV and 200 keV with sufficient number of photons. The High energy Engineering X-ray (HEX) Diffraction beamline, which is primarily funded by the New York State Energy Research and Development Authority (NYSERDA) and NSLS-II, will be equipped with a 1.2m-long SCW with 70 mm period length and 4.3 T on-axis field. This SCW is free from the use of liquid Helium and is cooled only with cryo-coolers. The Electron Beam Chamber (EBC) with vertical aperture of 8 mm is made from 316LN stainless steel and copper plating is applied both surface and +-12.5mm wide from the center in the inner surface. The expected heat load from the electron beam of the NSLS-II ring is estimated to be 10 W/m. Here, we describe the design principles and engineering challenges for the device.

36 MATERIALS SCIENCE↗

Generalized and Mechanistic PV Module Performance Prediction From Computer Vision and Machine Learning on Electroluminescence Images

Electroluminescence (EL) imaging of photovoltiac (PV) modules offers high-speed, high-resolution information about device performance, affording opportunities for greater insight and efficiency in module characterization across manufacturing, research and development, and power plant operations and management. Predicting module electrical properties from EL image features is a critical step toward these applications. In this article, we demonstrate quantification of both generalized and performance mechanism-specific EL image features, using pixel intensity-based and machine learning classification algorithms. From EL image features, we build predictive models for PV module power and series resistance, using time-series current-voltage (I-V) and EL data obtained stepwise on five brands of modules spanning three Si cell types through two accelerated exposures: damp heat (DH) (85°C/85% RH) and thermal cycling (TC) (IEC 61215). Overall, 195 pairs of EL images and I-V characteristics were analyzed, yielding 11700 individual PV cell images. A convolutional neural network was built to classify cells by the severity of busbar corrosion with high accuracy (95%). Generalized power predictive models estimated the maximum power of PV modules from EL images with high confidence and an adjusted-R 2 of 0.88, across all module brands and cell types in extended DH and TC exposures. Mechanistic degradation prediction was demonstrated by quantification of busbar corrosion in EL images of three module brands in DH, and subsequent modeling of series resistance using these mechanism-specific EL image features. For modules exhibiting busbar corrosion, we demonstrated series resistance predictive models with adjusted-R 2 of up to 0.73.

14 SOLAR ENERGY↗

NASA Physics of Failure (PoF) for Reliability

An item’s reliability or longevity is dependent not only on its design but also on how it is used, manufactured, tested, and the stresses it has or will experience. Stresses include operational and environmental exposures to thermal, voltage, current, age/exposure, mechanical, and radiation mechanisms. Therefore, in reliability analysis, it is important to consider the contributions of all of these factors when predicting the failure rates of components. Historically, there has been a reliance on handbook data (e.g., MIL-HDBK-217), but experience has shown that these values and distributions are not representative of actual performance (1,2). Therefore, to make more credible reliability and risk assessments for its missions, NASA must transition to estimating likelihoods of failure based on an item’s reliability/longevity factors (or the physical susceptibilities and strengths impacting the design’s performance) has or will experience, whenever possible. To facilitate this transition a “Handbook on Methodology for Physics of Failure Based Reliability Assessments” has been developed by NASA to assist in applying physics experiences or experiment physics for empirical analysis and conceptualized physics exposures or theoretical physics for deterministic analysis, to develop and aggregate realistic likelihoods of failure leading to more credible forecasts of item performance and longevity. In addition, since it is NASA’s intention that this document continues to evolve based on community lessons learned and the introduction of new assessment methodologies, NASA is encouraging and appreciates the contributions of current and future authors to maintain and enhance this handbook and its supporting case studies.

Physics of Failure↗