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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Near Real Time Tools for ISS Plasma Science and Engineering Applications

The International Space Station (ISS) program utilizes a plasma environment forecast for estimating electrical charging hazards for crews during extravehicular activity (EVA). The process uses ionospheric electron density and temperature measurements from the ISS Floating Potential Measurement Unit (FPMU) instrument suite with the assumption that the plasma conditions will remain constant for one to fourteen days with a low probability for a space weather event which would significantly change the environment before an EVA. FPMU data is typically not available during EVA's, therefore, the most recent FPMU data available for characterizing the state of the ionosphere during EVA is typically a day or two before the start of an EVA or after the EVA has been completed. In addition to EVA support, information on ionospheric plasma densities is often needed for support of ISS science payloads and anomaly investigations during periods when the FPMU is not operating. This presentation describes the application of space weather tools developed by MSFC using data from near real time satellite radio occultation and ground based ionosonde measurements of ionospheric electron density and a first principle ionosphere model providing electron density and temperature run in a real time mode by GSFC. These applications are used to characterize the space environment during EVA periods when FPMU data is not available, monitor for large charges in ionosphere density that could render the ionosphere forecast and plasma hazard assessment invalid, and validate the assumption of "persistence of conditions" used in deriving the hazard forecast. In addition, the tools are used to provide space environment input to science payloads on ISS and anomaly investigations during periods the FPMU is not operating.

Minow, Joseph I.↗
NASA NTRSDate not supplied

Unlocking the Microbiome of the International Space Station

With the start of human occupation more than 22 years ago, the microbiome of International Space Station (ISS) has been monitored to assess risk to both crew and craft. Historically, this monitoring has been achieved through onboard culture and ground-based analyses. Data spanning this timeframe are descriptive of a semi-closed, human occupied environment with associations to crew changes and process escapes within the environmental control and life support systems. While this approach has served to provide alerts to anomalies and overall confidence in the controls in place, the data are limited to the media type and growth conditions used. The bias toward the detection of culturable organisms has depicted an overall lack in biodiversity. As NASA leaves the ISS to focus on exploration, it is critical to fully understand its microbiome and its possible association to the noted positive influence on crew and vehicle health. The implementation of culture-independent, nanopore sequencing-based studies, both onboard the ISS and with returned ground samples, is revealing a more thorough depiction of the microbiome. As noted with pervious culture-based data, there is a common core microbiome across time and location, but key distinct areas of greater diversity exist. Through further investigation, these areas are emerging as unique ecological niches, potentially resulting in environmentally driven microbial selection. Moreover, the presence of some noted taxa within these unique locations has implications for crew health, planetary protection, and controls used in future spacecraft systems. The ability to perform in situ profiling of the ISS microbiome is transforming how NASA assesses risk and is a critical tool towards monitoring the establishment of the environmental microbiome in exploration spacecraft.

Sarah Stahl-Rommel↗
DOE OSTI2023

An Integrated Approach to Predicting Ash Deposition and Heat Transfer in Coal-Fired Boilers

The overall goal of this project is to develop via measurements and simulations an advanced online technology to predict, monitor and manage fireside ash deposition in a coal-fired boiler allowing for more efficient operations under a range of load conditions and fuel property variability. With this in place fuel sorting and blending can be done upstream and operations can be optimized to compensate for load and fuel properties. In support of this objective, three experimental campaigns were undertaken during the course of the project to measure ash deposition rates within the boiler at different fuel flow rates and its ash composition variability. Simulations of the experimental conditions representing actual geometry, operational scenarios in terms of air flow rates, coal flow rates as well as coal compositions, heating values, and particle size distributions were also carried out. Deposition rates were predicted using a unique particle kinetic energy and viscosity based ash deposition methodology whose validity was ascertained by comparing against deposition rate measurements for widely varying operating conditions and ash compositions in a lab-scale furnace. With a unique end-to-end combustion modeling methodology established and different simulation scenarios carried out, the results from our computational fluid dynamic (CFD) simulations in conjunction with the plant data summarized in this report were used to refine Microbeam Technology Incorporated’s MTI CSPI-CT Tool to predict and monitor fire-side ash deposition under a range of load conditions and fuel property variability in real time.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1991

Atmospheric effects on NOAA AVHRR data over Sahelian regions

Variable atmospheric conditions have a significant impact on satellite monitoring of vegetation in the Sahelian zone of Africa. The effects of atmospheric O3, H2O, and aerosols on spectral, directional reflectances and derived measures, such as the normalized difference vegetation index are discussed using a sensitivity study. An atmospheric correction scheme is presented based on measurements of optical thicknesses from the ground and is applied to NOAA AVHRR data. The use of the reflectance of the ocean surface close to the terrestrial target to estimate atmospheric effects on terrestrial reflectance is also discussed.

Soufflet, V.↗
NASA NTRS2006

Liquid Hydrogen Sensor Considerations for Space Exploration

The on-orbit management of liquid hydrogen planned for the return to the moon will introduce new considerations not encountered in previous missions. This paper identifies critical liquid hydrogen sensing needs from the perspective of reliable on-orbit cryogenic fluid management, and contrasts the fundamental differences in fluid and thermodynamic behavior for ground-based versus on-orbit conditions. Opportunities for advanced sensor development and implementation are explored in the context of critical Exploration Architecture operations such as on-orbit storage, docking, and trans-lunar injection burn. Key sensing needs relative to these operations are also examined, including: liquid/vapor detection, thermodynamic condition monitoring, mass gauging, and leak detection. Finally, operational aspects of an integrated system health management approach are discussed to highlight the potential impact on mission success.

Moran, Matthew E.↗
NASA NTRS2010

System and method of self-properties for an autonomous and automatic computer environment

Systems, methods and apparatus are provided through which in some embodiments self health/urgency data and environment health/urgency data may be transmitted externally from an autonomic element. Other embodiments may include transmitting the self health/urgency data and environment health/urgency data together on a regular basis similar to the lub-dub of a heartbeat. Yet other embodiments may include a method for managing a system based on the functioning state and operating status of the system, wherein the method may include processing received signals from the system indicative of the functioning state and the operating status to obtain an analysis of the condition of the system, generating one or more stay alive signals based on the functioning status and the operating state of the system, transmitting the stay-alive signal, transmitting self health/urgency data, and transmitting environment health/urgency data. Still other embodiments may include an autonomic element that includes a self monitor, a self adjuster, an environment monitor, and an autonomic manager.

Hinchey, Michael G.↗
DOE OSTI2022

Real-time Condition Monitoring of Power Modules in Grid-tied Power Converter

This paper proposes and demonstrates a real-time condition monitoring method using gate driver integrated sensing circuits and sensor fusion algorithms. Power device on-state voltage (VDSon) measurement and junction temperature (Tj) sensing circuits with high noise immunity are built and integrated into an adaptive gate driver circuit for power modules. Considering the inherently noisy measurement environment of power converters, VDSon together with several other measurements are fused together to provide accurate descriptions of the stress and degradation of each power device. Furthermore, the gate driver circuit can actively control the turn-on gate voltage (VGSon) for each device based on the stress and degradation state. The proposed sensing circuits and power device condition assessment algorithms are implemented in a 75 KVA grid-tied power converter. This paper focuses on the sensing circuits hardware designs and testing in grid-tied power converter prototype and device stress index generation. More comprehensive results on the device state of health index generation will be presented in future work.

Fan, Junchong↗
DOE OSTI2025

Modeling High Current Pulsed Discharge in AA Battery Cathodes: The Effect of Localized Charging during Rest

During high current operation, substantial heterogeneity develops within battery cathodes, particularly when their thickness is large. Heterogeneity relaxation during subsequent rest is important for understanding battery performance under pulsed conditions. Localized charge balancing phenomena within batteries at zero net current are not well understood and merit investigation. In this work, the heterogeneity within cathodes of commercial alkaline Zn–MnO 2 batteries is measured during discharge and monitored during rest using energy dispersive X-ray diffraction (EDXRD). Significant gradients in protonation form during discharge and partially relax under rest. It is demonstrated that the proton gradient relaxation is through local redox activity at zero net current, where local (de)protonation works to redistribute charge across the cathode thickness. To support this redox-based relaxation, a fundamental kinetic study on prismatic MnO 2 cathodes is conducted to determine an appropriate model to describe both discharge and charge kinetics of MnO 2 . These kinetics are incorporated into a computational model to simulate the proton gradient formation and partial relaxation under identical discharge conditions as the operando EDXRD experiments. Model and experimental data are found to be in excellent agreement, correctly predicting localized charge balancing at rest.

Batteries↗
DOE OSTI2024

Multi-Parameter Optical Fiber Sensing of Humidity, CH4, CO2, and Corrosion

In this work, the previously demonstrated capability of the optical fiber sensor (OFS) for successful monitoring of humidity has been extended to monitor the humidity, CH4, and CO2 with different gas composition based on the strain produced along the single mode fiber (SMF) sensor. This is enabled by absorption of H2O/gases on to the commercially available polyacrylate coated jacketed portion of the fiber resulting a change in strain. Under equilibrium, a differential microstrain was observed along the jacketed portion of the SMF with N2, CH4, and CO2 at different humidity conditions, while the unjacketed portion of the fiber was used only for sensing pressure/temperature induced strain. In case of N2 at 800 psig pressure, the observed microstrain was approximately 80, 65, 50 and 35 µε at 100, 75.0, 46.8, and 23.4 RH% respectively. Comparatively, a microstrain of approximately 95 µε was observed with 100% RH CH4 which demonstrates that SMF produces a measurable CH4 response alongside water. Similarly, the observed microstrain with CO2 was approximately 105, 90, 85, 80, and 70 µε at 100, 75.0, 46.8, 23.4, and 0 RH% respectively. Linear regression and principal component analysis of these dataset provided deconvolution of the impact of strain from H2O, CH4, and CO2 enabling good cross sensitivity. Additionally, modified OFS comprising of Fe coated fiber section was employed to monitor corrosion, using Fe as corrosion proxy, under harsh corrosive environment.

Mainali, Badri↗
DOE OSTI2021

Data-driven estimation of energy consumption for electric bus under real-world driving conditions

Reliable and accurate estimation of an electric bus’s instantaneous energy consumption is critical in evaluating energy impacts of planning and control of electric bus operations. In this study, we developed machine learning-based long short-term memory (LSTM) and artificial neural network (ANN) models to estimate 1 Hz energy consumption of electric buses based on continuous monitoring data of electric buses in Chattanooga, Tennessee, in 2019 and 2020. We propose a data-partitioning algorithm to separate energy charging and discharging modes before applying data-driven estimation models. Here, a K-fold cross-validation-based model selection process was conducted to identify the optimal model structure and input variables in terms of prediction accuracy. The estimation results show the predicted mean absolute percentage error rates of LSTM and ANN models were 3% and 5%, respectively. We compared the proposed models with existing models in the literature based on the same testing data to demonstrate the predictability of our models.

Artificial neural network↗
DOE OSTI2024

A prediction model of failure threshold for shear deformation in a Zr-based bulk metallic glass

The failure of bulk metallic glasses (BMGs) during plastic deformation at room temperature is abrupt and instantaneous, while the analysis of precursor information based on avalanche events helps predict catastrophic failure. An acoustic emission (AE) signal can provide accurate precursor information for material failure, due to its sensitive and high fast calculation ability. In the current study, AE monitoring tests are carried out during uniaxial compression tests of BMGs at different strain rates. The AE experimental failure threshold, E max , is proposed on the basis of AE cumulative energy, which reflects the intensity of damage evolution at different loading conditions. Compared with the critical shear band velocity (CSBV) associated with stick-slip dynamics of serrated flow, E max is a more sensitive failure parameter since it is connected with the local microscopic changes that occur during the material response process. Here, the E max is obtained prior to reaching the CSBV since the calculation of these two avalanches analysis focuses on the different stages of shear band growth. In particular, AE events are related to the “dry” friction process in the first stage, however, the CSBV is responsible for the “viscous” glide in the second stage. Therefore, Emax is not affected by the complex interactions between the shear bands during the stick-slip process. The maximum avalanche of serrated flow, S max , is proposed as the experimental failure threshold, which depends on the applied strain rate as S max ~ $\dot{ε}$ –λ . According to the relationship of E max and S max , the theoretical failure threshold, E max , follows a criterion E max = 2545$\dot{ε}$ –λ - 4468, where λ is equivalent to 0.15 for this work. Finally, combining the different calculations and AE measurements, this model gives new insights to predict the deformation failure behavior of Zr-based BMGs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗
DOE OSTI2023

Air Conditioning Systems Fault Detection and Diagnosis-Based Sensing and Data-Driven Approaches

The air conditioning (AC) system is the primary building end-use contributor to the peak demand for energy. The energy consumed by this system has grown as fast as it has in the last few decades, not only in the residential section but also in the industry and transport sectors. Therefore, to combat energy crises, urgent actions on energy efficiency should be taken to support energy security. Consequently, the faults in AC system components increase energy consumption due to the degradation of the system’s performance and the losses in the energy conversion procedure. In this work, AC system fault detection and diagnosis (FDD) methods are investigated to propose analytic tools to identify faults and provide solutions to those problems. The analysis of existing work shows that data-driven approaches are more accurate for both soft and hard fault detection and diagnosis in AC systems. Therefore, the proposed methods are not accurate for simultaneous fault detection, while in some works, authors tested the method with several faults separately without investigating scenarios that combine more than one fault. Moreover, this study shows that integrating data-driven approaches requires deploying an optimal sensing and measurement architecture that can detect a maximum number of faults with minimally deployed sensors. The new sensing, information, and communication technologies are discussed for their integration in AC system monitoring in order to optimize system operation and detect faults.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Emergent Trends Complicate the Interpretation of the United States Drought Monitor (USDM)

Abstract Effective drought management must be informed by an understanding of whether and how current drought monitoring and assessment practices represent underlying nonstationary climate conditions, either naturally occurring or forced by climate change. Here we investigate the emerging climatology and associated trends in drought classes defined by the United States Drought Monitor (USDM), a weekly product that, since 2000, has been used to inform drought management in the United States. The USDM classifies drought intensity based in part on threshold percentiles in key hydroclimate quantities. Here we assess how those USDM‐defined drought threshold percentiles have changed over the last 23 years, examining precipitation, runoff, soil moisture (SM), terrestrial water storage (TWS), vapor pressure deficit (VPD), and near‐surface air temperature. We also assess underlying trends in the frequency of drought classifications across the U.S. Our analysis suggests that the frequency of drought class occurrence is exceeding the threshold percentiles defined by the USDM in a number of regions in the United States, particularly in the American West, where the last 23 years have emerged as a prolonged dry period. These trends are also reflected in percentile‐based thresholds in precipitation, runoff, SM, TWS, VPD, and temperature. Our results emphasize that while the USDM appears to be accurately reflecting observed nonstationarity in the physical climate, such trends raise critical questions about whether and how drought diagnosis, classification, and monitoring should address long‐term intervals of wet and dry periods or trends.

Geology↗
DOE OSTI2022

Relationship Between the Marginal Probability of Failure for a CPP Test and the Recommended Corrosion Control Requirements for Hanford Double Shell Waste Tanks

The Hanford Site in Washington State currently stores millions of gallons of radioactive waste in underground, carbon steel, double shell tanks (DSTs) that were constructed between 1968 and 1986. A chemistry control and monitoring program has been established mitigate corrosion in order to extend the service life for the DSTs. The current waste temperatures in the DSTs are at historical lows (i.e., typically less than 50 °C). The previous chemistry control requirements were determined for conditions at temperatures significantly higher. SRNL undertook a statistically based investigation of the role of nitrate and halide ion (i.e., chloride and fluoride) induced pitting corrosion. The objective was to develop a comprehensive waste chemistry envelope for the simultaneous minimization of the pitting and SCC risks caused by halide and nitrate ions at the lower temperature conditions. On the basis of these tests, new chemistry control requirements were proposed and have since been implemented for pitting corrosion control.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Embedded High-Temperature Sensors: Enhancing Thermoelectrical Performance with Refractory Composites Gradient Layers

To monitor the stability of various energy and manufacturing systems, sensors capable of operating at temperatures exceeding 1000 °C in diverse environments for extended durations are essential. However, under harsh conditions, degradation of sensing materials is a concern that can be controlled by embedding the sensors into refractory oxides. Doped-LaCrO3 based composites are excellent candidates for high-temperature sensing applications due to their good thermoelectrical properties. However, chemical reactivity between the conductive phase and the refractory oxides can decrease the performance of the sensors. In this work, it was devised gradient-type protective layers safeguarding conductive phases within embedded thermocouples, which were fabricated and characterized by X-Ray Diffraction for phase development analysis, Scanning Electron Microscopy and Energy-dispersive X-ray spectroscopy for microstructure and cationic interdiffusion kinetics, long-term thermoelectric testing was completed up to 1400 °C. The enhanced performance of these novel sensors addresses a critical limitation, rendering them viable for long-term high-temperature applications.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1987

Independent Orbiter Assessment (IOA): Analysis of the purge, vent and drain subsystem

The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. This report documents the independent analysis results corresponding to the Orbiter PV and D (Purge, Vent and Drain) Subsystem hardware. The PV and D Subsystem controls the environment of unpressurized compartments and window cavities, senses hazardous gases, and purges Orbiter/ET Disconnect. The subsystem is divided into six systems: Purge System (controls the environment of unpressurized structural compartments); Vent System (controls the pressure of unpressurized compartments); Drain System (removes water from unpressurized compartments); Hazardous Gas Detection System (HGDS) (monitors hazardous gas concentrations); Window Cavity Conditioning System (WCCS) (maintains clear windows and provides pressure control of the window cavities); and External Tank/Orbiter Disconnect Purge System (prevents cryo-pumping/icing of disconnect hardware). Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode. Four of the sixty-two failure modes analyzed were determined as single failures which could result in the loss of crew or vehicle. A possible loss of mission could result if any of twelve single failures occurred. Two of the criticality 1/1 failures are in the Window Cavity Conditioning System (WCCS) outer window cavity, where leakage and/or restricted flow will cause failure to depressurize/repressurize the window cavity. Two criticality 1/1 failures represent leakage and/or restricted flow in the Orbiter/ET disconnect purge network which prevent cryopumping/icing of disconnect hardware. Each level of hardware was evaluated and analyzed for possible failure modes and effects. Criticality was assigned based upon the severity of the effect for each failure mode.

Bynum, M. C., III↗
NASA NTRS1996

A Conservation Strategy for the Florida Scrub-Jay on John F. Kennedy Space Center/Merritt Island National Wildlife Refuge: An Initial Scientific Basis for Recovery

The Florida Scrub-Jay (Aphelocoma coerulescens) is an indicator of ecosystem integrity of Florida scrub, an endangered ecosystem that requires frequent fire. One of the largest populations of this federally threatened species occurs on John F. Kennedy Space Center/Merritt Island National Wildlife Refuge. Population trends were predicted using population modeling and field data on reproduction and survival of Florida Scrub-Jays collected from 1988 - 1995. Analyses of historical photography indicated that habitat suitability has been declining for 30 years. Field data and computer simulations suggested that the population declined by at least 40% and will decline by another 40% in 1 0 years, if habitat management is not greatly intensified. Data and computer simulations suggest that habitat suitability cannot deviate greatly from optimal for the jay population to persist. Landscape trajectories of vegetation structure, responsible for declining habitat suitability, are associated with the disruption of natural fire regimes. Prescribed fire alone can not reverse the trajectories. A recovery strategy was developed, based on studies of Florida Scrub-Jays and scrub vegetation. A reserve design was formulated based on conservation science principles for scrub ecosystems. The strategy emphasizes frequent fire to restore habitat, but includes mechanical tree cutting for severely degraded areas. Pine thinning across large areas can produce rapid increases in habitat quality. Site-specific strategies will need to be developed, monitored, and modified to achieve conditions suitable for population persistence.

Breininger, D. R.↗