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At least 577 records · Page 32

A real-time diagnostic and performance monitor for UNIX

There are now over one million UNIX sites and the pace at which new installations are added is steadily increasing. Along with this increase, comes a need to develop simple efficient, effective and adaptable ways of simultaneously collecting real-time diagnostic and performance data. This need exists because distributed systems can give rise to complex failure situations that are often un-identifiable with single-machine diagnostic software. The simultaneous collection of error and performance data is also important for research in failure prediction and error/performance studies. This paper introduces a portable method to concurrently collect real-time diagnostic and performance data on a distributed UNIX system. The combined diagnostic/performance data collection is implemented on a distributed multi-computer system using SUN4's as servers. The approach uses existing UNIX system facilities to gather system dependability information such as error and crash reports. In addition, performance data such as CPU utilization, disk usage, I/O transfer rate and network contention is also collected. In the future, the collected data will be used to identify dependability bottlenecks and to analyze the impact of failures on system performance.

Dong, Hongchao↗

Habituation and adaptation of the vestibuloocular reflex: a model of differential control by the vestibulocerebellum

We habituated the dominant time constant of the horizontal vestibuloocular reflex (VOR) of rhesus and cynomolgus monkeys by repeated testing with steps of velocity about a vertical axis and adapted the gain of the VOR by altering visual input with magnifying and reducing lenses. After baseline values were established, the nodulus and ventral uvula of the vestibulocerebellum were ablated in two monkeys, and the effects of nodulouvulectomy and flocculectomy on VOR gain adaptation and habituation were compared. The VOR time constant decreased with repeated testing, rapidly at first and more slowly thereafter. The gain of the VOR was unaffected. Massed trials were more effective than distributed trials in producing habituation. Regardless of the schedule of testing, the VOR time constant never fell below the time constant of the semicircular canals (approximately 5 s). This finding indicates that only the slow component of the vestibular response, the component produced by velocity storage, was habituated. In agreement with this, the time constant of optokinetic after-nystagmus (OKAN) was habituated concurrently with the VOR. Average values for VOR habituation were obtained on a per session basis for six animals. The VOR gain was adapted by natural head movements in partially habituated monkeys while they wore x 2.2 magnifying or x 0.5 reducing lenses. Adaptation occurred rapidly and reached about +/- 30%, similar to values obtained using forced rotation. VOR gain adaptation did not cause additional habituation of the time constant. When the VOR gain was reduced in animals with a long VOR time constant, there were overshoots in eye velocity that peaked at about 6-8 s after the onset or end of constant-velocity rotation. These overshoots occurred at times when the velocity storage integrator would have been maximally activated by semicircular canal input. Since the activity generated in the canals is not altered by visual adaptation, this finding indicates that the gain element that controls rapid changes in eye velocity in the VOR is separate from that which couples afferent input to velocity storage. Nodulouvulectomy caused a prompt and permanent loss of habituation, returning VOR time constants to initial values. VOR gain adaptation, which is lost after flocculectomy, was unaffected by nodulouvulectomy. Flocculectomy did not alter habituation of the VOR or of OKAN. Using a simplified model of the VOR, the decrease in the duration of vestibular nystagmus due to habituation was related to a decrement in the dominant time constant of the velocity storage integrator (1/h0).(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗

VTO_2021_APR_LLNL_Ye

Traditional batteries are composed of two-dimensional films that are stacked and/or rolled. Thin film batteries display high power density while their thick film counterparts show good energy density, but it has proven difficult to concurrently achieve both within these planar form factors. In addition, conventional Li-ion batteries based on liquid organic electrolytes or gel polymer electrolytes have raised severe safety concerns due to the intrinsic flammable properties of the organic electrolytes. They are also not ideal for the use of high energy density metallic lithium (Li) anodes due to Li dendrite growth, or sulfur cathodes due to shuttling effects that result in fast capacity fade. There is an urgent need to develop safe, high-performance solid-state batteries (SSBs) with advanced electrolyte and separator technologies. Although in recent years a series of superionic conductors have been developed for electrolytes and separators, their performance does not satisfy demanding criteria due to large impedance from poor solid electrolyte-electrode contact and questionable electrochemical and mechanical stability. Unlike the well-established roll-to-roll fabrication of conventional Li-ion batteries, the processing of SSBs is unique due to the brittleness of solid-state electrolytes (SSEs). The commercially available or lab-developed SSE discs are usually very thick (hundreds of micrometers to millimeters) to overcome their brittle nature, which unfortunately increases the cell impedance and accounts for the majority of the overall cell weight and volume, leading to dramatically decreased power and energy densities. In this project, we will investigate 3D printing techniques to overcome safety, fabrication, mechanical, and electrochemical issues in SSBs. 3D printing builds complex structures in a layer-by-layer fashion, which allows rapid production of hierarchical architectures, gradient and multi-material structures, and multi-component assemblies. 3D printing is an emerging area that could fundamentally transform energy storage devices. For example, 3D printing can produce batteries with arbitrary form factors to fit a product’s specific volume requirements and can create interwoven electrode arrangements over a wide range of length scales to improve transport and increase power density for a given energy density. For SSBs, 3D printing may dramatically reduce the separator thickness from ~1 mm (by hydraulic pressing) to tens of micrometers or less. In addition, the interfacial contact area between the electrolyte and the electrode may be increased via 3D interdigitated designs. Hence, we expect a significant reduction of the overall cell impedance and enhancement of both energy and power densities of SSBs by harnessing an array of 3D printing technologies being developed at Lawrence Livermore National Laboratory (LLNL).

25 ENERGY STORAGE↗

Thresholds for detection of constant rotary acceleration during vibratory rotary acceleration

The effects of vibratory angular acceleration on detection thresholds for constant angular acceleration in a dynamic flight simulator are reported in three experiments. Detection thresholds were determined for 10 pilots and four nonpilots using a random, double-staircase procedure while the subjects sat erect in a device which rotated about an earth-vertical axis. Constant angular acceleration were presented for 0.5 and 1.0 s with concurrent, vibratory angular acceleration at 1 and 5 Hz, and thresholds with no vibratory angular acceleration were established. The thresholds were obtained while the subjects observed a visual reference in the enclosed cockpit in two experiments and in total darkness in a third. The results confirmed earlier experiments showing an inverse relationship between the duration of constant angular acceleration and detection threshold and showed that the detection thresholds in darkness were higher than with a visual reference present. Two analyses of variance revealed no significant differences in thresholds across the three vibration conditions. These results indicate that vibratory angular acceleration of fairly high levels can be present in a dynamic flight simulator without masking the pilot's ability to detect either maneuver or disturbance motions.

Clark, B.↗

Performance of laminar-flow leading-edge test articles in cloud encounters

An extensive data bank of concurrent measurements of laminar flow (LF), particle concentration, and aircraft charging state was gathered for the first time. From this data bank, 13 flights in the simulated airline service (SAS) portion were analyzed to date. A total of 6.86 hours of data at one-second resolution were analyzed. An extensive statistical analysis, for both leading-edge test articles, shows that there is a significant effect of cloud and haze particles on the extent of laminar flow obtained. Approximately 93 percent of data points simulating LFC flight were obtained in clear air conditions; approximately 7 percent were obtained in cloud and haze. These percentages are consistent with earlier USAF and NASA estimates and results. The Hall laminar flow loss criteria was verified qualitatively. Larger particles and higher particle concentrations have a more marked effect on LF than do small particles. A particle spectrometer of a charging patch are both acceptable as diagnostic indicators of the presence of particles detrimental to laminar flow.

Davis, Richard E.↗

Towards a multiscale approach for understanding irradiation induced swelling and creep in 316 stainless steels - A coupled cluster dynamics and crystal plasticity approach

Structural materials undergo mechanical degradation, in part due to irradiation-induced swelling and creep, under nuclear reactor conditions. While swelling results from the migration and clustering of irradiation-induced atomic-scale mobile defects, the interaction of mesoscale dislocations with these defects causes creep deformation. A coupled crystal plasticity (CP) and mean-field cluster dynamics (CD) approach is presented to investigate the effect of irradiation on the long-term mechanical behavior of 316 stainless steel, which are under consideration for use in nuclear reactors. The temporal evolution of Frenkel pairs and extended defect population, under a chosen irradiation flux and temperature, is predicted using the CD model. The impact of the irradiation defects on the stress state, and the resulting dislocation-mediated inelastic deformation, is modeled concurrently with the CP model. The inelastic deformation is irradiation flux dependent, and early-stage defect evolution determines the later-stage mechanical behavior in 316 stainless steel.

36 - MATERIALS SCIENCE↗

Conditioning the Surface and Bulk of High-Nickel Cathodes with a Nb Coating: An In Situ X-ray Study

Surface coating is commonly employed by industries to improve the cycling and thermal stability of high-nickel (Ni) transition metal (TM) layered cathodes for their practical use in lithium-ion batteries. Niobium (Nb) coating or substitution has been shown to be effective in stabilizing LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes; in addition, the electrochemical performance of the final products varies depending on the postprocessing. In this follow-up study, we use in situ synchrotron X-ray diffraction to investigate the kinetic processes and the involved structural evolution in Nb-coated NMC811 upon heat treatment. Furthermore, quantitative structure analysis reveals thermally driven concurrent changes in the bulk and surface, in particular, the phase evolution of the coating layer and Nb/TM interdiffusion that facilitates penetration of Nb into the bulk and particle growth at the increased temperatures. Findings from this study highlight the new opportunities for the intended control of the structure and surface properties of high-Ni cathodes through surface coating in conjunction with postprocessing.

36 MATERIALS SCIENCE↗

Using Life-Cycle Human Factors Engineering to Avoid $2.4 Million in Costs: Lessons Learned from NASA's Requirements Verification Process for Space Payloads

The Human Factors Implementation Team (HFIT) process has been used to verify human factors requirements for NASA International Space Station (ISS) payloads since 2003, resulting in $2.4 million in avoided costs. This cost benefit has been realized by greatly reducing the need to process time-consuming formal waivers (exceptions) for individual requirements violations. The HFIT team, which includes astronauts and their technical staff, acts as the single source for human factors requirements integration of payloads. HFIT has the authority to provide inputs during early design phases, thus eliminating many potential requirements violations in a cost-effective manner. In those instances where it is not economically or technically feasible to meet the precise metric of a given requirement, HFIT can work with the payload engineers to develop common sense solutions and formally document that the resulting payload design does not materially affect the astronaut s ability to operate and interact with the payload. The HFIT process is fully ISO 9000 compliant and works concurrently with NASA s formal systems engineering work flow. Due to its success with payloads, the HFIT process is being adapted and extended to ISS systems hardware. Key aspects of this process are also being considered for NASA's Space Shuttle replacement, the Crew Exploration Vehicle.

Carr, Daniel↗

Fair Concurrent Training of Multiple Models in Federated Learning

Federated learning (FL) enables collaborative learning across multiple clients. In most FL work, all clients train a single learning task. However, the recent proliferation of FL applications may increasingly require multiple FL tasks to be trained simultaneously, sharing clients’ computing resources, which we call Multiple-Model Federated Learning (MMFL). Current MMFL algorithms use naïve average-based client-task allocation schemes that often lead to unfair performance when FL tasks have heterogeneous difficulty levels, as the more difficult tasks may need more client participation to train effectively. Furthermore, in the MMFL setting, we face a further challenge that some clients may prefer training specific tasks to others, and may not even be willing to train other tasks, e.g., due to high computational costs, which may exacerbate unfairness in training outcomes across tasks. We address both challenges by firstly designing FedFairMMFL, a difficulty-aware algorithm that dynamically allocates clients to tasks in each training round, based on the tasks’ current performance levels. We provide guarantees on the resulting task fairness and FedFairMMFL’s convergence rate. We then propose novel auction designs that incentivizes clients to train multiple tasks, so as to fairly distribute clients’ training efforts across the tasks, and extend our convergence guarantees to this setting. Here, we finally evaluate our algorithm with multiple sets of learning tasks on real world datasets, showing that our algorithm improves fairness by improving the final model accuracy and convergence speed of the worst performing tasks, while maintaining the average accuracy across tasks.

Federated learning↗

Shifts in belowground processes along a temperate forest edge

Abstract Context Forests are increasingly fragmented, and as a result most forests in the United States are within one km of an edge. Edges change environmental conditions of the forest—especially radiation, roughness, temperature, and moisture—that can have consequences for plant productivity and ecosystem functions. However, edge effects on aboveground characteristics of plants and the environment are better understood relative to plant roots and soil in the belowground environment. Objectives Our main objectives were to determine if soil C pools and fluxes are higher at the edge relative to other landscape positions, and to understand how specific belowground processes contribute to bulk differences in pools and fluxes. Methods We measured environmental conditions, live and dead fine root traits, soil chemistry, and soil respiration along a 75 m transect from interior forest to meadow in Gaithersburg, MD. Results We observed differences in the soil chemical, biological and hydrological environment between the forest interior, edge and adjacent meadow. In some cases, the forest edge represented a mid-point in environmental or belowground characteristics between the forest interior and meadow ( e.g. , pH, C-to-N ratio [C:N], live fine root biomass, heterotrophic respiration), likely reflecting the change in litter type and quality associated with the transition from grass to woody species. In other cases, neighboring landscape positions were different from the forest edge, which was drier and had higher dead fine root biomass. Although soil C contents were not significantly different across landscape positions, there was a tendency towards higher average soil C content at the edge relative to other landscape positions, suggesting that increased C loss related to root decay and greater soil respiration at the edge relative to the forest interior may have been offset by increased C gain from high plant productivity and subsequent inputs to soil. Conclusions This research provides insight into how forest edge environments may differ from the interior and how concurrent processes above- and belowground may contribute to those differences.

54 ENVIRONMENTAL SCIENCES↗

FitCache: A Transparent Drop-In Framework for Multi-Tier Caching to Accelerate Distributed Deep Learning Workloads

Training in Deep learning (DL) remains highly compute- and data-intensive, with I/O becoming a critical bottleneck as models and datasets scale. Recent studies report that data loading can dominate training time, especially on large-scale HPC systems with shared parallel file systems (PFS). Existing caching approaches either rely on single-tier designs or require intrusive modifications to training pipelines, limiting their portability and effectiveness. In this work, we present FitCache, a transparent drop-in framework for multi-tier caching to accelerate distributed DL training by coordinating fast local memory (e.g., DRAM, Persistent Memory (PMem)) and NVMe as hierarchical caches atop PFS. Our design adapts to hardware diversity, i.e., if NVMe is missing, memory transparently acts as a caching tier, ensuring stable performance. FitCache transparently intercepts I/O requests and issues concurrent fetches across all tiers, returning data from the fastest responder without centralized metadata or static redirection paths. FitCache adapts to dynamic workloads and heterogeneous clusters while maintaining POSIX compatibility. Experiments on Frontier (2048 GPUs) and smaller research clusters show that FitCache reduces training time by up to 40% and per-batch I/O latency by up to 71.6% compared to Lustre Orion PFS, offering a drop-in solution for scalable DL training.

Hu, Guangxing [ORNL] (ORCID:0009000283203614)↗

Magnetic heat pumping

A ferromagnetic or ferrimagnetic element is used to control the temperature and applied magnetic field of the element to cause the state of the element as represented on a temperature-magnetic entropy diagram to repeatedly traverse a loop. The loop may have a first portion of concurrent substantially isothermal or constant temperature and increasing applied magnetic field, a second portion of lowering temperature and constant applied magnetic field, a third portion of isothermal and decreasing applied magnetic field, and a fourth portion of increasing temperature and constant applied magnetic field. Other loops may be four-sided, with two isotherms and two adiabats. Preferably, a regenerator is used to enhance desired cooling or heating effects, with varied magnetic fields, or varying temperatures including three-sided figures traversed by the representative point.

Brown, G. V.↗

Radiation Shielding for Nuclear Thermal Propulsion

Design and analysis of radiation shielding for nuclear thermal propulsion has continued at Marshall Space Flight Center. A set of optimization tools are in development, and strategies for shielding optimization will be discussed. Considerations for the concurrent design of internal and external shielding are likely required for a mass optimal shield design. The task of reducing radiation dose to crew from a nuclear engine is considered to be less challenging than the task of thermal mitigation for cryogenic propellant, especially considering the likely implementation of additional crew shielding for protection from solar particles and cosmic rays. Further consideration is thus made for the thermal effects of radiation absorption in cryogenic propellant. Materials challenges and possible methods of manufacturing are also discussed.

Caffrey, Jarvis A.↗

Remote Concurrent Engineering: A-Team Studies in the Virtual World

NASA Jet Propulsion Laboratory’s (JPL’s)Architecture Team (A-Team) has nearly a decade of experiencein maturing early formulation mission and technology conceptsby combining innovative collaborative engineering methodswith cutting-edge subject matter expertise and advancedanalysis tools in an in-person environment. When COVID-19forced JPL’s workforce to work remotely in March 2020, ATeamhad to quickly pivot from an in-person collaborativeenvironment to a remote working environment.Through introspection, careful planning, and considerablepractice, A-Team was able to develop new operating proceduresto effectively continue early formulation studies in a virtualenvironment. A-Team has held over 57 remote studies in the 10months since the start of mandatory telework at JPL in March2020. In the remote setting, A-Team conducts studies in half-daysessions with clients and subject matter experts (SMEs) viavideoconferencing, shared computer screens, and digitalcollaborative tools.The key lesson is that increased staffing and planning is neededto prepare and successfully run remote A-Team studies. RemoteA-Team studies require careful selection of the appropriatetools for security, accessibility, and usability within theNASA/JPL environment. Knowledge capture methods andtemplates need to be thought out and agreed upon in advance asthere is less room for improvising in a remote format. Variouscommunication channels have to be monitored to allow for teamcoordination while maintaining fruitful participant engagementduring a session. In addition, technical backup for all roleswithin the A-Team have to be identified to allow the study tocontinue even if a team member’s connectivity is temporarilyinterrupted. Finally, careful thought has to be put into methodsand processes to create a collaborative environment in a virtualspace such that a group of experts who are only connected viathe internet can experience the creative spark and flow of a greatcollaborative and innovative study.

Zusack, Steven↗

Resampling and data augmentation for short-term PV output prediction based on an imbalanced sky images dataset using convolutional neural networks

Integrating photovoltaics (PV) into electricity grids is challenged by potentially large fluctuations in power generation. In recent years, sky image-based PV output prediction using convolutional neural networks (CNNs) has emerged as a promising approach to forecasting fluctuations. A key challenge is imbalanced sky image datasets: because of the geography of solar PV system installations, sky image datasets are often rich in sunny condition data but deficient in cloudy condition data. This imbalance contrasts with the fact that model errors are dominated by cloudy condition performance. In this study, we attempt to remedy this by exploring the enrichment and augmentation of an imbalanced sky images dataset for two PV output prediction tasks: nowcasting (predicting concurrent PV output) and forecasting (predicting 15-minute-ahead future PV output). We empirically examine the efficacy of using different resampling and data augmentation approaches to create a rebalanced dataset for model development. A three-stage greedy search is used to determine the optimal resampling approach, data augmentation techniques and over-sampling rate. The results show that for the nowcast problem, resampling and data augmentation can effectively enhance the model performance, reducing overall root mean squared error (RMSE) by an average of 4%, or a 15 std. (standard deviation) of improvement compared to the variability of the baseline model. In contrast, the treatment RMSE for the forecast problem nearly always overlaps the baseline performance at the ± 2 std. level. The optimal resampling approach expands on the original dataset by over-sampling the minority cloudy data, with the best results from large over-sampling rate (e.g., 4 ~ 6 times over-sampling of cloudy images).

14 SOLAR ENERGY↗

Persistent Elevated Soot Emissions Induced by Clustered Stochastic Preignition Events

Stochastic Preignition (SPI) is an abnormal combustion phenomenon that can occur in spark-ignition engines particularly under high-load operation. SPI is characterized by uncontrolled initiation of combustion prior to spark discharge, an abnormal combustion process that can lead to severe knock events and significant engine damage. SPI has been associated with fuel properties, lubricant composition, and engine design and operation. Here, in this work, a single-cylinder test engine with a dry-sump oil system was utilized to study the SPI response of E10 and E25 fuels with a range of Reid Vapor Pressure (RVP). An automated test procedure was employed, consisting of ten square-waved load profile segments, with each segment composed of 5 min of low-load operation followed by 25 min of sustained high-load operation. These tests were replicated across multiple days of testing including a lubricant triple flush between tests, and an online Fuel in Oil diagnostic measurement. Exhaust particulate emissions were continuously measured by an AVL microsoot sensor (MSS). Elevated particulate matter emissions were observed to occur concurrently with SPI events as blooms of soot. Particularly after clustered events (i.e., multiple SPI cycles occurring within 10 consecutive engine cycles), high soot emissions were observed to persist over several days of sequential operation despite daily lubricant changes, a complete warm-up procedure, and sustained low-load operation between test segments. This result implies that the particulate emissions trends may be dominated by deposit-based effects, where higher load operation is needed to alter deposition and formation processes. The observed soot blooms were also found to correspond to a reduction in the engine fueling and the fuel engine oil dilution rate despite the engine exhaust remaining at stoichiometric exhaust operation. These observations suggest that post-SPI events, pathways for lubricant migration and consumption into the combustion chamber may occur until these pathways are closed from deposit formation or ring dynamics during extended operation. These observed sooting propensity persisted with all fuels tests, but a linear correlation was observed between the summation of soot and particulate matter index (PMI) value for each fuel as well as SPI events, proving that PMI is a crucial fuel property for reducing SPI.

Splitter, Derek [Oak Ridge National Laboratory (OR↗

Eleventh Annual Conference on Manual Control

This volume contains a compilation of written versions of papers presented at the Eleventh Annual Conference on Manual Control in a meeting held at NASA-Ames Research Center, May 21-23, 1975. Five main topics were discussed during this three-day conference. These were covered in sessions on Concurrent Tasks, Physiological Systems, Controls and Displays, Performance/Workload Evaluation, and System Identification. Forty-nine papers are included with presentations on results of analytical studies to develop and evaluate human operator models for a range of control task, vehicle dynamics and display situations; results of tests of physiological control systems and applications to medical problems; and on results of simulator and flight tests to determine display, control and dynamics effects on operator performance and workload for aircraft, automobile and remote control systems.

Source record↗

Effects of non-thermal termolecular chemistry on detonation development in hydrogen (H2) / methane (CH4) - air mixtures

In combustion simulations, it is usually assumed that highly-energized collision complexes (either radical or stable species) formed in exothermic reactions are always under thermal equilibrium as they evolve through competing networks of reactions. However, in practical flames, non-trivial amounts of reactive radicals such as H, O and OH are present apart from O2. As a result, collisions of these reactive species with the energized collision complexes have been shown in recent studies to induce non-thermal reactivity. These studies have also demonstrated that such non-thermal reactions can be suitably represented in macroscopic kinetics models as chemically termolecular reactions. The present work was focused on identifying and quantifying the effects of including such reactions on the evolution of an initial deflagration front to a developing detonation in H2/CH4-air mixtures under boosted internal combustion (IC) engine conditions. Specifically, fully resolved simulations, with and without non-thermal reactivity, were performed for a constant volume reactor containing stoichiometric H2/CH4-air mixture. It was found that inclusion of termolecular chemistry resulted in a delayed onset of end-gas auto-ignition. Concurrently, the developing detonation intensity was observed to be significantly higher. Chemical explosive mode analysis (CEMA) was performed to identify the dominant species/reactions responsible for the observed variation in the results.

Detonation↗