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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Multimodality Instrument for Tissue Characterization

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip is discussed. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network, program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration.

Mah, Robert W.↗
NASA NTRS1993

(abstract) Examining Sea Ice SAR Signatures in the Arctic

This research examines the seasonal changes of the sea ice cover in the Arctic Basin as it responds to atmospheric and oceanic conditions. Monitoring this process provides a means of determining the onset and extent of the annual seasonal stages, which is thought to be an indicator for detecting climate change in the polar regions. Much of the response of sea ice to seasonal conditions results in changes in the phase of water (both in the ice and snow cover), surface roughness, and internal properties such as air bubbles. Imagery from SAR has proven to be an important tool for revealing these changes since radar backscatter is affected by both surface roughness and dielectric properties of water and salt. The major ice types and ice features may have unique SAR backscatter signatures because of the inherent variations in surface roughness, salinity, and internal properties in each category.

change surface roughness dielectric properties↗
NASA NTRS2004

Multimodality instrument for tissue characterization

A system with multimodality instrument for tissue identification includes a computer-controlled motor driven heuristic probe with a multisensory tip. For neurosurgical applications, the instrument is mounted on a stereotactic frame for the probe to penetrate the brain in a precisely controlled fashion. The resistance of the brain tissue being penetrated is continually monitored by a miniaturized strain gauge attached to the probe tip. Other modality sensors may be mounted near the probe tip to provide real-time tissue characterizations and the ability to detect the proximity of blood vessels, thus eliminating errors normally associated with registration of pre-operative scans, tissue swelling, elastic tissue deformation, human judgement, etc., and rendering surgical procedures safer, more accurate, and efficient. A neural network program adaptively learns the information on resistance and other characteristic features of normal brain tissue during the surgery and provides near real-time modeling. A fuzzy logic interface to the neural network program incorporates expert medical knowledge in the learning process. Identification of abnormal brain tissue is determined by the detection of change and comparison with previously learned models of abnormal brain tissues. The operation of the instrument is controlled through a user friendly graphical interface. Patient data is presented in a 3D stereographics display. Acoustic feedback of selected information may optionally be provided. Upon detection of the close proximity to blood vessels or abnormal brain tissue, the computer-controlled motor immediately stops probe penetration. The use of this system will make surgical procedures safer, more accurate, and more efficient. Other applications of this system include the detection, prognosis and treatment of breast cancer, prostate cancer, spinal diseases, and use in general exploratory surgery.

Mah, Robert W.↗
NASA NTRS2018

Front Delineation and Tracking with Multiple Underwater Vehicles

This work describes a method for detecting and tracking ocean fronts using multiple autonomous underwater vehicles. Multiple vehicles — equally-spaced along the expected frontal boundary — complete near parallel transects orthogonal to the front. Lateral gradients are used to determine the location of the front crossing from each individual vehicle transect by detecting a change in the observed water property. Adaptive control of the vehicles ensure they remain perpendicular to the estimated front boundary as it evolves over time. This method was demonstrated in and around Monterey Bay, California in May of 2017. We compare the front detection method to previously used methods. We introduce a metric in order to evaluate the adaptive control techniques presented. We show the capability of this method for repeated sampling across a dynamic two-dimensional ocean front using short-range Iver AUVs. This method extends to tracking gradients of different properties using a variety of vehicles.

Chavez, Francisco P.↗
NASA NTRS1997

Vibrational force alters mRNA expression in osteoblasts

Serum-deprived mouse osteoblastic (MC3T3E1) cells were subjected to a vibrational force modeled by NASA to simulate a space shuttle launch (7.83 G rms). The mRNA levels for eight genes were investigated to determine the effect of vibrational force on mRNA expression. The mRNA levels of two growth-related protooncogenes, c-fos and c-myc, were up-regulated significantly within 30 min after vibration, whereas those of osteocalcin as well as transforming growth factor-beta1 were decreased significantly within 3 h after vibration. No changes were detected in the levels of beta-actin, histone H4, or cytoplasmic phospholipase A2 after vibration. No basal levels of cyclooxygenase-2 expression were detected. In addition, the extracellular concentrations of prostaglandin E2 (PGE2), a potent autocrine/paracrine growth factor in bone, were not significantly altered after vibration most likely due to the serum deprivation state of the osteoblasts. In comparison with the gravitational launch profile, vibrational-induced changes in gene expression were greater both in magnitude and number of genes activated. Taken together, these data suggest that the changes in mRNA expression are due to a direct mechanical effect of the vibrational force on the osteoblast cells and not to changes in the local PGE2 concentrations. The finding that launch forces induce gene expression is of utmost importance since many of the biological experiments do not dampen vibrational loads on experimental samples. This lack of dampening of vibrational forces may partially explain why 1-G onboard controls sometimes do not reflect 1-G ground controls. These data may also suggest that scientists use extra ground controls that are exposed to launch forces, have these forces dampened on launched samples, or use facilities such as Biorack that provide an onboard 1-G centrufuge in order to control for space shuttle launch forces.

NASA Discipline Cell Biology↗
NASA NTRS1994

An Algorithm to Generate Deep-Layer Temperatures from Microwave Satellite Observations for the Purpose of Monitoring Climate Change

An algorithm for generating deep-layer mean temperatures from satellite-observed microwave observations is presented. Unlike traditional temperature retrieval methods, this algorithm does not require a first guess temperature of the ambient atmosphere. By eliminating the first guess a potentially systematic source of error has been removed. The algorithm is expected to yield long-term records that are suitable for detecting small changes in climate. The atmospheric contribution to the deep-layer mean temperature is given by the averaging kernel. The algorithm computes the coefficients that will best approximate a desired averaging kernel from a linear combination of the satellite radiometer's weighting functions. The coefficients are then applied to the measurements to yield the deep-layer mean temperature. Three constraints were used in deriving the algorithm: (1) the sum of the coefficients must be one, (2) the noise of the product is minimized, and (3) the shape of the approximated averaging kernel is well-behaved. Note that a trade-off between constraints 2 and 3 is unavoidable. The algorithm can also be used to combine measurements from a future sensor (i.e., the 20-channel Advanced Microwave Sounding Unit (AMSU)) to yield the same averaging kernel as that based on an earlier sensor (i.e., the 4-channel Microwave Sounding Unit (MSU)). This will allow a time series of deep-layer mean temperatures based on MSU measurements to be continued with AMSU measurements. The AMSU is expected to replace the MSU in 1996.

Goldberg, Mitchell D.↗
DOE OSTI2022

Drastically different restructuring of airborne and surface-anchored soot aggregates

Combustion soot particles are fractal aggregates of hydrophobic spherules. Mixing of soot particles with other chemicals during atmospheric processing may partially offset their hydrophobicity, promoting water uptake and structural compaction. Here, we investigated morphological changes in fractal soot particles coated by sulfuric acid and then humidified, both in airborne and surface-bound states. Airborne soot was probed by tandem differential mobility analysis. Surface-bound soot was studied in a controlled microenvironment of a closed cell, using environmental transmission electron microscopy. After humidification, the airborne particles became fully compact, but the deposited particles showed only minor morphological changes despite significant water uptake. Although minor, those changes were detected during both water condensation and evaporation, indicating that condensation-evaporation cycles play an important role in atmospheric soot compaction. Lesser restructuring of deposited aggregates was caused by surface anchoring and coating loss, making anchoring an indispensable tool for preserving morphology of aggregates against changing experimental environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Ultrasonic Characterization of Lithium Ion Thermal Runaway Conditions for Real-time Ultrasonic Enabled BMS Integration

The demand for energy storage is growing, and lithium-ion batteries are a promising technology to meet this need due to their high power/energy density, high round-trip efficiency, rapid response time, and portability. However, recent catastrophic events caused by thermal runaway have slowed their adoption, highlighting the need for an early warning system for battery failure. In this work, ultrasound is used to detect physical changes in 950 mAh batteries by identifying material property changes independent of voltage and current. [Ultrasound signal features (e.g., time of flight, maximum frequency component) were extracted as the batteries were cycled and subjected to both constant current and constant voltage overcharge and were used to develop two metrics identifying failure: a warning to detect the start of overcharge and an emergency stop (E-stop) to immediately take the battery out of service. The identification method involved locating magnitude differences of several ultrasound features compared to baseline operation considering different currents and temperatures, and the warning/stopping metrics were consistent across all experiments. For an average overcharge time of 140 minutes, the average warning was issued 124 minutes before the failure and the average E-stop was triggered 94 minutes before failure. As a test of using ultrasound for early warning detection, a battery was forced into overcharge and returned to normal cycling conditions based on the previously determined warning metric. Both the voltage profile and the ultrasound measurements returned to their baseline behavior, indicating that ultrasonic detection can not only identify battery failure before a catastrophic event, but can also provide early enough warnings such that overcharges can be detected and corrected quickly enough so the battery does not need to be decommissioned.]

25 ENERGY STORAGE↗
NASA NTRS1997

Evaluation of heart rate changes: electrocardiographic versus photoplethysmographic methods

The heart rate (HR) variation to forced deep breathing (HRDB) and to the Valsalva maneuver (Valsalva ratio; VR) are the two most widely used tests of cardiovagal function in human subjects. The HR is derived from a continuously running electrocardiographic (ECG) recording. Recently, HR derived from the arterial waveform became available on the Finapres device (FinapHR), but its ability to detect rapid changes in HR remains uncertain. We therefore evaluated HRDB and VR derived from FinapHR using ECG-derived HR (ECGHR) recordings as the standard. We also compared the averaged HR on Finapres (Finapav) with beat-to-beat Finapres (FinapBB) values. Studies were undertaken in 12 subjects with large HR variations: age, 34.5 +/- 9.3 (SD) years; six males and six females. FinapBB values were superimposable upon ECGHR for both HRDB and VR. In contrast, Finapav failed to follow ECGHR for HRDB and followed HRECG with a lag for the VR. To evaluate statistically how closely FinapHR approximated ECGHR, we undertook regression analysis, using mean values for each subject. To compare the two methods, we evaluated the significance of the difference between test and standard values. For HRDB, FinapBB reproducibly recorded HR (R2 = 0.998), and was significantly (p = 0.001) better than Finapav (R2 = 0.616; p < 0.001). For VR, HRBB generated a VR that was not significantly different from the correct values, while HRav generated a value that was slightly but consistently lower than the correct values (p < 0.001). We conclude that FinapHR reliably records HR variations in the beat-to-beat mode for cardiovascular HR tests.

Non-NASA Center↗
NASA NTRS1976

Applications of space technology to developing nations

The use of imagery from the Landsat spacecraft for the monitoring and management of natural resources in developing countries is discussed. The Landsat imagery can be used to make cartographic maps at scales of 1:250,000 which meet the US National Map Accuracy Standards, providing a means of map updating to correct for river meanders or changing shorelines. The Landsat data can also be used in defining and measuring agricultural areas, identifying pest breeding areas, and monitoring irrigation practices and crop performance. Total volume estimates can be obtained in many cases for surface bodies of water, and subsurface water supplies can be detected from changes in vegetation in some instances.

Freden, S. C.↗
NASA NTRS2009

Autonomously Calibrating a Quadrupole Mass Spectrometer

A computer program autonomously manages the calibration of a quadrupole ion mass spectrometer intended for use in monitoring concentrations and changes in concentrations of organic chemicals in the cabin air of the International Space Station. The instrument parameters calibrated include the voltage on a channel electron multiplier, a discriminator threshold, and an ionizer current. Calibration is achieved by analyzing the mass spectrum obtained while sweeping the parameter ranges in a heuristic procedure, developed by mass spectrometer experts, that involves detection of changes in signal trends that humans can easily recognize but cannot necessarily be straightforwardly codified in an algorithm. The procedure includes calculation of signal-to-noise ratios, signal-increase rates, and background-noise-increase rates; finding signal peaks; and identifying peak patterns. The software provides for several recovery-from-error scenarios and error-handling schemes. The software detects trace amounts of contaminant gases in the mass spectrometer and notifies associated command- and-data-handling software to schedule a cleaning. Furthermore, the software autonomously analyzes the mass spectrum to determine whether the parameters of a radio-frequency ramp waveform are set properly so that the peaks of the mass spectrum are at expected locations.

Lee, Seungwon↗
NASA NTRS1995

To Boldly Go. America's Next Era in Space: New Frontiers in Climate Research

Dr. France Cordova, NASA's Chief Scientist, chaired this, the fourth seminar in the NASA Administrator's Seminar Series. She introduced NASA Administrator, Daniel S. Goldin, who greeted the attendees, and in his opening remarks said that human beings have a need to understand the what and why of the forces of nature and of people, and the stresses on the planet Earth. The first speaker, Dr. Ellen Mosley-Thompson of Ohio State University discussed the many things that scientists have learned from ice cores obtained in Peru and the Antarctic. The next speaker, Dr. Michael McElroy of Harvard University, is active in environmental research. He noted that insurance companies need to know more about the physics and chemistry of weather in order to avoid bankruptcy; that the greenhouse effect, which is good because it reflects heat, is being changed, and we don't know the rules. In the discussion that followed, Goldin asked if the present technology for measuring circulation of air and water and contents of the atmosphere is worth the cost. Drs. McElroy and Mosley-Thompson noted that the historic record in an ice core is endangered by ice melts; that in the last 10 years we've learned that tropics change; that the water vapor in the tropics is critical right now; that clouds absorb short-wave radiation; and that there is a need to improve measurements of atmospheric contents, the development of models, and the understanding of basic physics. We also need to understand parameters for detecting climate change, water, water temperature, and be able to provide fundamental information. Additional information is included in the original extended abstract.

Source record↗
NASA NTRS1991

Global change and relevant space observations; Proceedings of Symposium 1 of the COSPAR 28th Plenary Meeting, The Hague, Netherlands, June 25-July 6, 1990

Topics discussed include the middle-atmosphere change, the detection of an enhanced greenhouse effect, large-scale biological/physical processes in the ocean and at the ocean/atmosphere interface, global to regional energy and water-balance parameters, physical/biological processes at the soil/atmosphere interface, and space systems' capabilities. Papers presented are on complications in determining trends in the stratosphere, changes in characteristics of planetary waves at 80-100 km over central and southern Europe since 1980, the 30-yr trend of observed greenhouse clouds over the tropical oceans, possible causes of enhanced greeenhouse effect as due to natural and anthropogenic phenomena, and advances in modeling ocean primary production and its role in the global carbon cycle. Attention is also given to a climatological analysis of rainfall for the wet pampa and northwest of the Buenos Aires province; the use of thermal IR remote sensing for water budget studies; hydrometeorological, oceanographic, and earth-resources satellite systems operated by USSR, and the NASA ocean data system at the JPL.

Fellous, J. L.↗
NASA NTRS1986

An optimal repartitioning decision policy

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem.

Nicol, D. M.↗
DOE OSTI2022

Automated detection of photovoltaic cleaning events: A performance comparison of techniques as applied to a broad set of labeled photovoltaic data sets

Extracting accurate soiling loss information from photovoltaic (PV) production data first requires segmenting the time series data per natural or manually occurring cleaning events. Maintenance logs are often incomplete, rain data are often unavailable, and the debate on rain thresholds for cleaning and dew or wind cleanings is still ongoing. The present work aims to overtake these issues by improving automated methods to detect these cleaning events and therefore improve extraction of soiling loss information. Time series power production data from 22 PV inverters were labeled for natural or manually occurring cleaning events. The data sets were carefully selected to include varying degrees of soiling, cleaning events, and noise. Several algorithms, including filtering logic and change point detection, were examined for efficacy at detecting the labeled cleanings. All the methods introduced except for changepoint detection showed significant improvement at detecting the labeled cleaning events per the mean F 1 score. Furthermore, the highest performing cleaning detection algorithm achieved an absolute increase in the mean F 1 score of 43% over the default version of the RdTools stochastic rate and recovery (SRR) algorithm. The highest performing algorithm included irradiance filtering and a cleaning detection threshold, adjusted based on the 40-day centered rolling median of the absolute day-to-day deviations in the daily performance index (PI). Furthermore, these improvements are promising as cleaning detection is an essential step in the automated analysis of PV soiling.

14 SOLAR ENERGY↗
NASA NTRS2021

Linear and Nonlinear Trend Analyzes in Global Satellite‐Based Precipitation, 1998–2017

Precipitation varies spatio‐temporally in amount, intensity, and frequency. Although, much research has been conducted on analyzing precipitation patterns and variation at the global scale, trend types have still not received much attention. This study developed a new polynomial‐based model for detecting nonlinear and linear trends in a satellite precipitation product (TRMM 3B43) for the 1998–2017 period at a near‐global scale. We used an automated trend classification method that detects significant trends and classifies them into linear and nonlinear (cubic, quadratic, and concealed) trend types in satellite‐based precipitation at near‐global, continental, and climate zone scales. We found that 12.3% of pixel‐based precipitation time series across the globe have significant trend at 0.05 significance level (50% positive and 50% negative trends). In all continents except Asia, decreasing trends were found to cover larger areas than corresponding increasing trends. Regarding climate zone and precipitation trend change, our results indicate that a linear trend is dominant in the warm temperate (77.7%) and equatorial climates (80.4%) while the least linear change was detected in the polar climate (68.9%). The combined results of continental and climate zone scales indicate significant increasing trends in Asia and arid climate over the last 20 yr. Furthermore, positive trends were found to be more significant at the continental scale, particularly, in Asia relative to the climate zone scale. Linear change in precipitation (80%) was the most dominant trend observed as opposed to nonlinear (quadratic [11%] and cubic [9%]) trend types at the global scale.

Majid Kazemzadeh↗
DOE OSTI2021

The Relationship between Precipitation and Precipitable Water in CMIP6 Simulations and Implications for Tropical Climatology and Change

It is well documented that over the tropical oceans, column-integrated precipitable water (pw) and precipitation (P) have a nonlinear relationship. In this study moisture budget analysis is used to examine this P–pw relationship in a normalized precipitable water framework. It is shown that the parameters of the nonlinear relationship depend on the vertical structure of moisture convergence. Specifically, the precipitable water values at which precipitation is balanced independently by evaporation versus by moisture convergence define a critical normalized precipitable water, pw nc . This is a measure of convective inhibition that separates tropical precipitation into two regimes: a local evaporation-controlled regime with widespread drizzle and a precipitable water–controlled regime. Most of the 17 CMIP6 historical simulations examined here have higher pw nc compared to ERA5, and more frequently they operate in the drizzle regime. When compared to observations, they overestimate precipitation over the high-evaporation oceanic regions off the equator, thereby producing a ‘‘double ITCZ’’ feature, while underestimating precipitation over the large tropical landmasses and over the climatologically moist oceanic regions near the equator. The responses to warming under the SSP585 scenario are also examined using the normalized precipitable water framework. It is shown that the critical normalized precipitable water value at which evaporation versus moisture convergence balance precipitation decreases as a result of the competing dynamic and thermodynamic responses to warming, resulting in an increase in drizzle and total precipitation. Statistically significant historical trends corresponding to the thermodynamic and dynamic changes are detected in ERA5 and in lowintensity drizzle precipitation in the PERSIANN precipitation dataset.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Overview of the potential instrument payload for the EOS system

The Earth Observing System (EOS) is a key element of the U.S. Program in Global Change. It is NASA's initiative to provide the scientific means to observe the earth as a system. The EOS satellite system and accompanying Data and Information System (DIS) provide spacebased platforms and groundbased elements for scientific research and information extraction. The program recognizes the need for global coverage, long term observations, and multidisciplinary analyses in order to detect subtle changes in the environment's state. A multidisciplinary payload of active and passive sensors is proposed to accomplish the objectives of the program. International partners are an important element of the program. This paper focuses on the instrument complement for the EOS-A spacecraft since those decisions will occur this year. Significant programmatic constraints and program science decisions will impact the selection of the EOS-A payload.

Thompson, Leslie L.↗