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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Characterization of bioelectric potentials

Method and system for recognizing and characterizing bioelectric potential or electromyographic (EMG) signals associated with at least one of a coarse gesture and a fine gesture that is performed by a person, and use of the bioelectric potentials to enter data and/or commands into an electrical and/or mechanical instrument. As a gesture is performed, bioelectric signals that accompany the gesture are subjected to statistical averaging, within selected time intervals. Hidden Markov model analysis is applied to identify hidden, gesture-related states that are present. A metric is used to compare signals produced by a volitional gesture (not yet identified) with corresponding signals associated with each of a set of reference gestures, and the reference gesture that is closest to the volitional gesture is identified. Signals representing the volitional gesture are analyzed and compared with a database of reference gestures to determine if the volitional gesture is likely to be one of the reference gestures. Electronic and/or mechanical commands needed to carry out the gesture may be implemented at an interface to control an instrument. Applications include control of an aircraft, entry of data from a keyboard or other data entry device, and entry of data and commands in extreme environments that interfere with accurate entry.

Jorgensen, Charles C.↗
NASA NTRS2015

Microstructural Influence on Deformation and Fatigue Life of Composites Using the Generalized Method of Cells

A fully coupled deformation and damage approach to modeling the response of composite materials and composite laminates is presented. It is based on the semi-­‐analytical generalized method of cells (GMC) micromechanics model as well as its higher fidelity counterpart, HFGMC, both of which provide closed-form constitutive equations for composite materials as well as the micro scale stress and strain fields in the composite phases. The provided constitutive equations allow GMC and HFGMC to function within a higher scale structural analysis (e.g., finite element analysis or lamination theory) to represent a composite material point, while the availability of the micro fields allow the incorporation of lower scale sub­‐models to represent local phenomena in the fiber and matrix. Further, GMC's formulation performs averaging when applying certain governing equations such that some degree of microscale field accuracy is surrendered in favor of extreme computational efficiency, rendering the method quite attractive as the centerpiece in a integrated computational material engineering (ICME) structural analysis; whereas HFGMC retains this microscale field accuracy, but at the price of significantly slower computational speed. Herein, the sensitivity of deformation and the fatigue life of graphite/epoxy PMC composites, with both ordered and disordered microstructures, has been investigated using this coupled deformation and damage micromechanics based approach. The local effects of fiber breakage and fatigue damage are included as sub‐models that operate on the microscale for the individual composite phases. For analysis of laminates, classical lamination theory is employed as the global or structural scale model, while GMC/HFGMC is embedded to operate on the microscale to simulate the behavior of the composite material within each laminate layer. A key outcome of this study is the statistical influence of microstructure and micromechanics idealization (GMC or HFGMC) on the overall accuracy of unidirectional and laminated composite deformation and fatigue response.

Microscale Models↗
NASA NTRS1978

A highly accurate method for the determination of mass and center of mass of a spacecraft

An extremely accurate method for the measurement of mass and the lateral center of mass of a spacecraft has been developed. The method was needed for the Voyager spacecraft mission requirement which limited the uncertainty in the knowledge of lateral center of mass of the spacecraft system weighing 750 kg to be less than 1.0 mm (0.04 in.). The method consists of using three load cells symmetrically located at 120 deg apart on a turntable with respect to the vertical axis of the spacecraft and making six measurements for each load cell. These six measurements are taken by cyclic rotations of the load cell turntable and of the spacecraft, about the vertical axis of the measurement fixture. This method eliminates all alignment, leveling, and load cell calibration errors for the lateral center of mass determination, and permits a statistical best fit of the measurement data. An associated data reduction computer program called MASCM has been written to implement this method and has been used for the Voyager spacecraft.

Chow, E. Y.↗
NASA NTRS2018

Influence of Load Profile on Biomechanics of the Squat and Deadlift

Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to assist loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to counteract the effect reduced gravity has on the body. Astronauts will exercise on a flywheel based device on the second Orion Exploration Mission (EM2). The effect that the flywheel load profile has on biomechanics is unknown when compared to free weights or a simulated free weight profile. The purpose of this evaluation is to compare the differences in lower body kinematics and kinetics between the flywheel and free weight profile. Test subjects were instrumented with reflective markers for motion capture data collection while exercising on the Device for Aerobic and Resistive Training (DART) prototype developed by TDA Research, Inc. of Wheat Ridge, CO. Exercises performed were either the squat while wearing a harness or deadlift while grasping a T-bar, both of which interfaced with the DART through a rope cable. The DART, a motorized device controlled via software, is capable of producing different load profiles. Profiles include simulated free weights with adjustable eccentric overload capability and flywheel. Test variables included the applied device load and the load profile, both set through the DART software interface. Motion capture data was collected with a 12 camera system (Smart-DX, BTS Bioengineering, Brooklyn, NY). Bilateral ground reaction force data were collected with force plates (P6000, BTS Bioengineering). DART cable force was recorded through an internal load cell. Data was collected from a total of four test subjects. The three repetition maximum was determined for each test subject for both squat and deadlift. High, medium and low loads were determined based on this maximum. The test subject performed five repetitions of each exercise at each load and each test trial was repeated twice. Cadence was controlled during exercising. Biomechanical data were used to drive the models utilizing the OpenSim software platform. Subject specific models were scaled to match the anthropometrics of the test subjects and used to estimate the peak joint angle, joint range of motion, the peak joint moment and the joint moment impulse of the lower extremity joints and the lumbar joint.These are preliminary results because the data analysis is ongoing. There was a lot of inter-subject variability, however, in general, there was a greater peak lumbar flexion angle for the flywheel squat exercise. There was a trend towards a greater range of motion at the hip for the squat exercise with free weight. There was also a greater hip extension, lumbar extension and ankle plantar flexion impulse moment during the squat exercise with free weight. During the deadlift exercise, the peak knee flexion angle and peak knee extension moment were greater when using the free weight profile. For deadlift, the hip extension, lumbar extension and ankle plantar flexion impulse moment tended to be greater with the free weight profile. Overall, the kinematic and kinetic outcomes for the flywheel profile were either statistically the same as free weight profile in many cases, significantly reduced in a few cases, and rarely higher.

Bioengineering↗
NASA NTRS2002

Evidence for Subauroral Electric Fields from IMAGE EUV

The IMAGE Mission Extreme Ultraviolet Imager routinely provides global snapshots of the plasmasphere from high latitude. In these 10-minute images, intensity edges have been identified with the plasmapause and other strong gradients in plasmaspheric density. In addition to the classic sunward directed convection tail and its entrainment in corotation during storm-time recovery, the plasmapause boundary reveals a wide variety of structures thought to result from penetration of the solar wind induced convection electric field to subauroral latitudes. The so-called shoulder feature has most prominently been discussed in the context of under shielding in response to changes in the convection electric field strength. It is not yet clear whether all of the observed surface structures on the plasmasphere can be explained in this manner. The types of structures observed and their frequency of occurrence will be presented. A statistical view of these structures and associated solar wind conditions will also be presented.

Six, N. Frank↗
NASA NTRS2015

Wear-Out Sensitivity Analysis Project Abstract

During the course of the Summer 2015 internship session, I worked in the Reliability and Maintainability group of the ISS Safety and Mission Assurance department. My project was a statistical analysis of how sensitive ORU's (Orbital Replacement Units) are to a reliability parameter called the wear-out characteristic. The intended goal of this was to determine a worst case scenario of how many spares would be needed if multiple systems started exhibiting wear-out characteristics simultaneously. The goal was also to determine which parts would be most likely to do so. In order to do this, my duties were to take historical data of operational times and failure times of these ORU's and use them to build predictive models of failure using probability distribution functions, mainly the Weibull distribution. Then, I ran Monte Carlo Simulations to see how an entire population of these components would perform. From here, my final duty was to vary the wear-out characteristic from the intrinsic value, to extremely high wear-out values and determine how much the probability of sufficiency of the population would shift. This was done for around 30 different ORU populations on board the ISS.

Harris, Adam↗
NASA NTRS2023

Coronal Heating as Determined by the Solar Flare Frequency Distribution Obtained by Aggregating Case Studies

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counterintuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfvén waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, α = 2 as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed >600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: preflare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that α = 1.63 ± 0.03. This is below the critical threshold, suggesting that Alfvén waves are an important driver of coronal heating.

Astrostatistics distributions↗
DOE OSTI2020

Real-time Intrusion Detection for High-bandwidth Research Networks using Unsupervised Deep Learning

Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks across distributed collaboration sites for processing, storage, and analysis. Like general purpose networks, research networks experience attacks. However, monitoring traffic in such high-bandwidth network environments is challenging with conventional deep packet inspection (DPI)- based network intrusion detection systems (NIDS). Recently, machine learning (ML) algorithms have shown potential in detecting anomalous patterns with better generalizability and faster speed. Compared to the general purpose networks, traffic movement in research network is less volatile and more likely to benefit from the ML-based anomaly analysis. We present ThunderSecure, an efficient AI-powered system for detecting anomalies in 100G research networks. ThunderSecure implements a high-throughput packet processing infrastructure using multi-cores and GPUs. It takes time-series statistics from a variety of network measurements and uses 2D Convolutional Neural Network (CNN) to explore both spatial and temporal dependencies in network data stream. Patterns of science data traffic are learned with a one-class neural network, which blends an Adversarial Autoencoder (AAE) with Gaussian mixture density estimation. Testing traffic flows exhibiting significant deviations from the learned baseline of normality are marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets recorded from a 100G research network at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. To the best of our knowledge, this is the first ML work in the area of network anomaly detection that has been validated on such extreme scale datasets. Results show that ThunderSecure can recognize science data traffic that are captured long after the training and make nearly certain detection on those with anomalous flows injected, even in the case when the anomaly-to-normal mixing ratio is 0.1%.

Gong, Qian↗
DOE OSTI2025

How Representative Are Uncrewed Aircraft System Measurements of the Convective Boundary Layer?

Abstract Uncrewed aircraft systems (UAS) demonstrate significant potential for filling data gaps in the atmospheric boundary layer. However, the extent to which UAS observations—typically vertical profiles taken over 15 min—are representative of the boundary layer as a whole remains poorly characterized. Using large eddy simulations (LES) of the daytime convective boundary layer (CBL), we quantify random errors in UAS measurements that occur due to insufficient statistical convergence of the time average to the true ensemble mean. Random errors in first‐order moments increase as the CBL becomes increasingly unstable, and are largest near the surface for most quantities. Errors are on the order of 2–6 m for wind speed, 15–60 for wind direction, 0.2–3 K for potential temperature, and 0.1–1 g for specific humidity, with errors in turbulent fluxes on the order of 50%–100%. Sampling strategies that mitigate random errors are discussed in light of our results.

Greene, Brian R. [Now at Verisk Extreme Event Solu↗
DOE OSTI2020

Assessing concurrent effects of climate change on hydropower supply, electricity demand, and greenhouse gas emissions in the Upper Yangtze River Basin of China

Hydropower importantly provides flexible low-carbon electricity, however, climate change will affect the hydropower system through altering hydrologic regimes while also affecting electricity demands for heating and cooling that hydropower resources serve. This study assesses the effect of climate change on hydropower and electricity demand in the Upper Yangtze River Basin (UYRB) in China on the regional net electric load and greenhouse gas (GHG) emissions. This is accomplished by using climate projections from five global climate models (GCMs) to simultaneously force (1) a physically-based hydrological model and a statistically-based hydropower model to estimate the future generating capacity of 21 large hydropower plants in the UYRB and (2) an empirical electricity demand model accounting for socioeconomic and climatic factors. Under climate change, the projected hydropower generation in the UYRB tends to increase in the 21st century but is far less than the increase in electricity demand, increasing the gap between demand and supply. Future increases in overall electricity demand are driven by GDP growth, but climate change will alter the distribution of the seasonal electricity demand. Climate warming decreases electricity demand for heating in winter and increases electricity demand for cooling in summer, but ultimately increases demand. Meanwhile, there is an increasing mismatch between electricity demand and hydropower supply associated with inter- and intra-annual variations, owing to the temporal climate change and increase in compound climate extremes (droughts and heatwaves). Finally, meeting the gap between supply and demand due to climate change is estimated to contribute 79.0–184.6 and 50.6–316.2 MMT CO 2e /yr of additional GHG emissions by the mid and end of 21st century, respectively.

13 HYDRO ENERGY↗
DOE OSTI2021

Role of underlying surface, rainstorm and antecedent wetness condition on flood responses in small and medium sized watersheds in the Yangtze River Delta region, China

Floods are becoming more frequent and are hard to control due to the shortage of water conservancy projects in small and medium sized basins, especially in developing regions. Understanding the hydrologic responses and estimated flood characteristics to storm events can help to predict flood disasters and form better effective mitigation and adaptation strategies. Here, using observations of several representative watersheds and Artificial Neural Networks (ANN) and Principal Component Regression (PCR) models, we conducted data-driven analyses to examine the flood responding characteristics. We quantified the relative contributions of the influencing factors to the variation of each flood characteristic. Statistical analysis of the observations shows that the drainage area plays a key role in determining the distribution of lag time and peak discharge. Rainstorm variability has direct influence on floods, and typhoon-induced rainstorms with high total rainfall and rainfall intensity generate higher lag time, flood peak, unit discharge and runoff depth, but lower runoff coefficient. The ANN and PCR models accurately predicted the variations of flood features using the driving factors including physical geographical characteristics, rainstorm features, and antecedent condition. Physical geographic characteristics are key influential factors of lag time, flood peak and runoff coefficient, while the rainstorm features control the magnitude of unit discharge and runoff depth. These results indicate that floods are mainly affected by rainstorm features and physical geographic characteristics in the Yangtze River delta, and it might become more damaging with the increasing rainfall extremes and sprawling impervious surfaces in a changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks

ABSTRACT The problem of anomaly detection in astronomical surveys is becoming increasingly important as data sets grow in size. We present the results of an unsupervised anomaly detection method using a Wasserstein generative adversarial network (WGAN) on nearly one million optical galaxy images in the Hyper Suprime-Cam (HSC) survey. The WGAN learns to generate realistic HSC-like galaxies that follow the distribution of the data set; anomalous images are defined based on a poor reconstruction by the generator and outlying features learned by the discriminator. We find that the discriminator is more attuned to potentially interesting anomalies compared to the generator, and compared to a simpler autoencoder-based anomaly detection approach, so we use the discriminator-selected images to construct a high-anomaly sample of ∼13 000 objects. We propose a new approach to further characterize these anomalous images: we use a convolutional autoencoder to reduce the dimensionality of the residual differences between the real and WGAN-reconstructed images and perform UMAP clustering on these. We report detected anomalies of interest including galaxy mergers, tidal features, and extreme star-forming galaxies. A follow-up spectroscopic analysis of one of these anomalies is detailed in the Appendix; we find that it is an unusual system most likely to be a metal-poor dwarf galaxy with an extremely blue, higher-metallicity H ii region. We have released a catalogue with the WGAN anomaly scores; the code and catalogue are available at https://github.com/kstoreyf/anomalies-GAN-HSC; and our interactive visualization tool for exploring the clustered data is at https://weirdgalaxi.es.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

ENSO Effect on East Asian Tropical Cyclone Landfall via Changes in Tracks and Genesis in a Statistical Model

Improvements on a statistical tropical cyclone (TC) track model in the western North Pacific Ocean are described. The goal of the model is to study the effect of El Nino-Southern Oscillation (ENSO) on East Asian TC landfall. The model is based on the International Best-Track Archive for Climate Stewardship (IBTrACS) database of TC observations for 1945-2007 and employs local regression of TC formation rates and track increments on the Nino-3.4 index and seasonally varying climate parameters. The main improvements are the inclusion of ENSO dependence in the track propagation and accounting for seasonality in both genesis and tracks. A comparison of simulations of the 1945-2007 period with observations concludes that the model updates improve the skill of this model in simulating TCs. Changes in TC genesis and tracks are analyzed separately and cumulatively in simulations of stationary extreme ENSO states. ENSO effects on regional (100-km scale) landfall are attributed to changes in genesis and tracks. The effect of ENSO on genesis is predominantly a shift in genesis location from the southeast in El Nino years to the northwest in La Nina years, resulting in higher landfall rates for the East Asian coast during La Nina. The effect of ENSO on track propagation varies seasonally and spatially. In the peak activity season (July-October), there are significant changes in mean tracks with ENSO. Landfall-rate changes from genesis- and track-ENSO effects in the Philippines cancel out, while coastal segments of Vietnam, China, the Korean Peninsula, and Japan show enhanced La Nina-year increases.

simulation↗
DOE OSTI2021

Identification of Life Models for Li-Ion Batteries Using Penalized Regression and Bilevel Optimization

Reduced-order physics-based life models are extremely useful for rapidly predicting battery state-of-health and for simulating battery lifetime in arbitrary aging conditions. However, identification of well-parameterized models is difficult. This is because, for maximum usefulness in predicting lifetime under a variety of conditions, aging test data exhibits many degradation mechanisms, which all need to be accurately modeled. However, because aging tests are time-consuming and expensive, especially for large-format batteries, a minimum of tests are conducted while probing many stress factors. Building a well-parameterized model is then very challenging: an under-parameterized model will neglect critical degradation modes, and an over-parameterized model will extrapolate poorly to new testing conditions. To complicate this matter, the functional form of the model for any individual degradation rate can be very difficult to identify. In this work, the statistical tools of penalized regression and bilevel optimization are used to help identify both the functional forms of and optimize the parameters of reduced-order life models, accelerating identification of robust models. Model robustness is demonstrated through traditional statistics methods of cross-validation and sensitivity analysis, uncertainty quantification through bootstrap resampling and Monte-Carlo simulation, and simulation of real-world use cases.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

40 MHz Level-1 Trigger Scouting for CMS

The CMS experiment will be upgraded for operation at the HighLuminosity LHC to maintain and extend its physics performance under extreme pileup conditions. Upgrades will include an entirely new tracking system, supplemented by a track finder processor providing tracks at Level-1, as well as a high-granularity calorimeter in the endcap region. New front-end and back-end electronics will also provide the Level-1 trigger with high-resolution information from the barrel calorimeter and the muon systems. The upgraded Level-1 processors, based on powerful FPGAs, will be able to carry out sophisticated feature searches with resolutions often similar to the offline ones, while keeping pileup effects under control. In this paper, we discuss the feasibility of a system capturing Level-1 intermediate data at the beam-crossing rate of 40 MHz and carrying out online analyzes based on these limited-resolution data. This 40 MHz scouting system would provide fast and virtually unlimited statistics for detector diagnostics, alternative luminosity measurements and, in some cases, calibrations. It has the potential to enable the study of otherwise inaccessible signatures, either too common to fit in the Level-1 accept budget, or with requirements which are orthogonal to “mainstream” physics, such as long-lived particles. We discuss the requirements and possible architecture of a 40 MHz scouting system, as well as some of the physics potential, and results from a demonstrator operated at the end of Run-2 using the Global Muon Trigger data from CMS. Plans for further demonstrators envisaged for Run-3 are also discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Solar+Storage for Household Back-up Power: Implications of building efficiency, load flexibility, and electrification for backup during long-duration power interruptions [Slides]

The study analyzes the evolving role of solar+storage for home backup power during long-duration power interruptions. In particular, it evaluates how required storage sizing is impacted as homes become more efficient, flexible, and electrified. The study relies on NREL’s ResStock building modeling platform to create statistically representative distributions of the existing building stock in ten locations across the United States. It then shows how the amount battery storage required for backup power rises or falls as a series of building envelope efficiency, load flexibility, and electrification measures are applied across the building stock in each region. The study also includes sensitivities to show how backup power requirements are impacted by the timing and duration of power interruptions, and explores variation in backup power requirements across the building stock within each study location. The results demonstrate the value of pairing solar+storage with efficiency upgrades, smart home controls, and (in mild winter climates) efficient heat pump retrofits. That value comes in the form of reducing the amount of storage required and/or extending the range of interruption conditions over which a given system can provide backup power (i.e., more extreme weather and/or longer interruptions). Heat pumps in cold-weather climates can pose a challenge for solar+storage backup power, given the amount of storage required, though are a vast improvement over electric-resistance heating. Retaining existing fossil-based heating systems for occasional use during power interruptions, as either the primary or supplementary source of heat, can mitigate this challenge. Other forms of building electrification (e.g., cooking and water heating) generally have marginal impacts on backup battery sizing, given their relatively small energy demand.

14 SOLAR ENERGY↗
NASA NTRS1997

Physiological and Thermal Responses of MS Patients to Head and Vest Cooling: A Case Study

Personal cooling systems are used to alleviate symptoms of multiple sclerosis (MS) and to prevent increased core temperature during daily activities. The objective of this study was to determine the operating characteristics and the physiologic changes produced by short term application of the stationary thermal control system used by most clinical institutions. The Life Enhancement Tech (LET) Mark VII portable cooling system and a lightweight Head-vest active cooling garment were used to cool the head and chest regions of 4 male and 3 female MS patients (30 to 66 yrs. old) in this study. The subjects, seated in an upright position at normal room temperature (approx. 24 C), were tested for 60 min. with the liquid cooling garment (LCG) operated at 50 F. Oral, right and left ear temperatures and cooling system parameters were logged manually every 5 min. Arm, leg, chest and rectal temperatures, heart rate, respiration, and an activity index were recorded continuously on a U.F.I., Inc., Biolog ambulatory monitor. All temperature responses showed extreme variation among subjects. The cold-sensitive subject's rectal temperature increased initially in response to cooling; the heat sensitive subject's rectal temperature decreased. After 40 min. of cooling and during recovery, all subjects'rectal temperatures decreased. Oral temperatures began to decrease after 30 min. of cooling. After 60 min. of cooling, temperature drops ranged from approx. 0.3 - 0.8 C. Oral temperatures continued to decrease during recovery (approx. 0.2 C). The car temperature of the heat sensitive subject was increased after cooling, other subjects exhibited an ear temperature decrease (0.0 - 0.5 C). These data indicate that head and vest cooling may be used to reduce the oral temperatures of MS patients by the approximate amount needed for symptomatic relief as shown by other researchers. The combination of a small subject population and a large subject variance does not permit us to draw statistical conclusions about the temperature response of MS patients. An individual's heat or cold sensitivity may influence their thermal response to cooling. This factor should be considered in the prescribed use of liquid cooling garments in the therapeutic management of MS.

Luna, Bernadette↗
DOE OSTI2021

Equilibrium distribution of point defects in Fe-Y-O as a typical representative of nanocluster-strengthened alloys

The statistical mechanic approach has been used to estimate the equilibrium defect distribution in a multiphase system by minimizing its free energy using microstructural characteristics and a finite set of defects obtained by first-principles calculations. Recently the approach was extended to take in consideration defects at the interface of the precipitate and matrix. Herein we apply the developed approach to the investigation of the stability of bcc Fe containing yttria, Y 2 O 3 , nanoclusters as a prototype of nanostructured ferritic alloys. It has been obtained that (100)Fe-O interface is unstable with respect to vacancies production. In a contrast to (100)Fe-O interface, the so called Klim interface is stable, i.e. local vacancy concentration at this interface at 600 K is below 10 -12 . It has been demonstrated that due to large defect formation energies the ODS particles are extremely stable and the main defect corresponds to Fe atoms substitute Y in Y 2 O 3 precipitate. Moreover, under thermodynamic equilibrium condition, the preexist vacancies in bulk Fe do not accumulate oxygen atom. The later observation not necessarily forbid the existence of a large amount of preexisting Fe vacancy - oxygen atom clusters at the initial stages of alloy formation far from equilibrium.

36 MATERIALS SCIENCE↗