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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

remote sensing↗
NASA NTRSDate not supplied

On the Hunt for Detectable Biosignatures in Jezero Crater: What to Look for and Where

Introduction: The Perseverance rover, which is currently exploring Jezero crater on Mars, is equipped with seven instruments that allow for observation of textures, minerals, color, structure, and chemistry of rocks and sediments in order to search for signs of ancient life, understand the geologic history of the crater, and identify candidates for sample return (Farley et al. 2020). The first of these aims includes the direct detection of potential biosignatures, including textures, organic molecules, minerals, and elemental chemistries that are of biogenic origin (Mustard et al. 2013). The presence of these biosignatures will be constrained by the habitability of the local region, the preservation potential of the host rocks, and the sensitivity of the instrument suite, and their biogenicity will be investigated after return to Earth as part of the Mars Sample Return campaign. Here, we examine key targets on the three planned campaigns, potential biosignatures that may be present, and the capabilities of key rover instruments. High Potential Biosignature Sites in Jezero: To date, measurements have been made on multiple sites that both contain minerals known in terrestrial settings to preserve biosignatures and likely were habitable settings (Williford et al. 2021). Two examples include the fine-grained rocks at the base of the delta fan and the NW inner margin of the crater. Fine-grained Rocks at Base of Delta Fan. Fine-grained, clay-bearing rocks may have been deposited as muddy lake sediments that could have hosted life and preserved biosignatures settling out of the water column. The report of organic molecules by the Curiosity rover in the Sheepbed mudstone and Murray formation has highlighted this site in particular. Potential biosignatures in mudstones, especially those rich in silica (McMahon et al. 2018), microbialites and complex organics. NW Inner Margin of Crater. This unit, located along the inner margin of the crater, contains strong carbonate signatures and may have been the littoral zone of a lake (Horgan et al. 2020). The potential biosignatures here include microfossils, microbialites, biominerals, and complex organics. Detectability of Biosignatures by the Mars 2020 Instrument Suite: The Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) instrument comprises a Deep UV spectrometer, context imager, and color camera to generate spatially resolved chemical maps (Bhartia et al. 2020). It is sensitive to trace organics as well as a range of minerals and can detect native fluorescence from aromatic organics; the WATSON and ACI cameras can be used to observe morphologies such as stromatolitic laminations or filaments ranging from the tens of micron to millimeter scale. SHERLOC can detect organics that may be present in either of the high potential biosignature targets, as well as detect carbonates in the latter. However, the presence of high amounts of iron, such as in iron-rich clays, would cause attenuation of spectral response through UV absorption. The Planetary Instrument for X-ray Lithochemistry (PIXL) comprises an X-ray fluorescence spectrometer and camera that can scan rock surfaces to generate elemental maps (Allwood et al. 2020). PIXL can detect chemical biosignatures such as spatial variations of elemental abundances that may have resulted from biological activity. PIXL would be particularly useful in detecting fine textures and elemental chemistries in either high potential biosignature target, but cannot directly detect minerals such as carbonate. The SuperCam instrument performs three types of spectroscopy, color imaging, and acoustic recording to remotely examine elemental composition, minerals, organics, and textures (Maurice et al. 2021). Using laser induced breakdown spectroscopy and time resolved luminescence spectroscopy, SuperCam can detect major elemental building blocks of organics (i.e., C, H, N, O, P, S) and conjugated organic structures, respectively, which may be found in either site. While in other contexts, luminescence is a useful tool for biosignature identification, luminescence generated by the 532 nm laser may obscure the Raman signal. Conclusion: The three instruments discussed can be used collaboratively to establish the presence of potential biosignatures in samples. These high-priority samples may then be returned to Earth for detailed laboratory analysis.

S. Sharma↗
DOE OSTI2025

Evaluating Acoustic vs. AI-Based Satellite Leak Detection in Aging US Water Infrastructure: A Cost and Energy Savings Analysis

The aging water distribution system in the United States, constructed mainly during the 1970s with some pipes dating back 125 years, is experiencing significant deterioration leading to substantial water losses. Along with the potential for water loss savings, improvements in the distribution system by using leak detection technologies can create net energy and cost savings. In this work, a new framework has been presented to calculate the economic level of leakage within water supply and distribution systems for two primary leak detection technologies (acoustic vs. satellite). In this work, a new framework is presented to calculate the economic level of leakage (ELL) within water supply and distribution systems to support smart infrastructure in smart cities. A case study focused using water audit data from Atlanta, Georgia, compared the costs of two leak mitigation technologies: conventional acoustic leak detection and artificial intelligence–assisted satellite leak detection technology, which employs machine learning algorithms to identify potential leak signatures from satellite imagery. The ELL results revealed that conducting one survey would be optimum for an acoustic survey, whereas the method suggested that it would be expensive to utilize satellite-based leak detection technology. However, results for cumulative financial analysis over a 3-year period for both technologies revealed both to be economically favorable with conventional acoustic leak detection technology generating higher net economic benefits of USD 2.4 million, surpassing satellite detection by 50%. A broader national analysis was conducted to explore the potential benefits of US water infrastructure mirroring the exemplary conditions of Germany and The Netherlands. Achieving similar infrastructure leakage index (ILI) values could result in annual cost savings of $\$4$–$\$4.8$ billion and primary energy savings of 1.6–1.9 TWh. These results demonstrate the value of combining economic modeling with advanced leak detection technologies to support sustainable, cost-efficient water infrastructure strategies in urban environments, contributing to more sustainable smart living outcomes.

acoustic leak detection↗
DOE OSTI2024

SPIDARman: System-Level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors

In nuclear power plants (NPPs), anomalies arising from sensors or human errors (HEs) can undermine the performance and reliability of plant operations. Anomaly detection models can be employed to detect sensor errors and HEs. Additionally, physics-informed machine learning models can utilize the known physics of the system, as described by mathematical equations, to ensure that sensor values are consistent with physical laws. Hence, we propose SPIDARman: System-level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors, a holistic physics-informed anomaly detection approach based on generative adversarial networks (GANs) to detect anomalies in both automatically collected sensor data and manually collected surveillance data. Here we test our approach on data collected from a flow loop testbed, showcasing its potential to detect anomalies. Results demonstrate that the proposed model performs better than the baseline GAN-based models in detecting sensor and surveillance anomalies, suggesting the potential of physics-informed anomaly detection GAN models in NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2015

Inflight Microbial Monitoring- An Alternative Method to Culture Based Detection Currently Used on the International Space Station

Previous research has shown that potentially destructive microorganisms and human pathogens have been detected on the International Space Station (ISS). The likelihood of introducing new microorganisms occurs with every exchange of crew or addition of equipment or supplies. Microorganisms introduced to the ISS are readily transferred between crew and subsystems (i.e. ECLSS, environmental control and life support systems). Current microbial characterization methods require enrichment of microorganisms and at least a 48-hour incubation time. This increases the microbial load while detecting only a limited number of the total microorganisms. The culture based method detects approximately 1-10% of the total organisms present and provides no identification. To identify and enumerate ISS microbes requires that samples be returned to Earth for complete analysis. Therefore, a more expedient, low-cost, in-flight method of microbial detection, identification, and enumeration is warranted. The RAZOR EX, a ruggedized, commercial off the shelf, real-time PCR field instrument was tested for its ability to detect microorganisms at low concentrations within one hour. Escherichia coli, Salmonella enterica Typhimurium, and Pseudomonas aeruginosa were detected at low levels using real-time DNA amplification. Total heterotrophic counts could also be detected using a 16S gene marker that can identify up to 98% of all bacteria. To reflect viable cells found in the samples, RNA was also detectable using a modified, single-step reverse transcription reaction.

Inflight Microbial↗
NASA NTRS2024

Crowd-Sourced Technology Challenge for Improving Visual Color Detection of Hydrazine and Monomethylhydrazine Vapors in Spacecraft Environments

NASA currently uses a visual colorimetric detection method for potential hydrazine, monomethylhydrazine (MMH), or unsymmetrical dimethylhydrazine (UDMH) contamination in the International Space Station. Astronauts exposed to propellants or their residues during extravehicular activities may transfer contaminants into the airlock. The colorimetric detection method employs the Contamination Detection Kit (CDK), which uses a potassium tetrachloroaurate redox reaction with the propellant hydrazine vapors and a color comparison card to determine airborne concentrations. Seeking ideas for improvement, the NASA Tournament Lab (NTL) crowdsourced a way to tackle the challenge of detecting hydrazine and MMH vapors using colorimetric detection methods. This Rid the Rocket competition drew over 200 participants and 20 submissions from around the world proposing innovative ways to develop a new chemical colorimetric detection method for hydrazine and MMH vapors on spacecraft. Using a phased approach to evaluate contestants, NASA eventually narrowed the field to five finalists from the United States, Romania, Taiwan, and India. Concept papers and hardware submissions were judged on feasibility, creativity, and ability to detect hydrazine and MMH vapors before being sent to the NASA White Sands Test Facility for laboratory evaluation. Finalists employed variations of sampling methods and color-detection chemistry using a variety of sampling pumps and indicator pads or solutions—including those employing potassium or hydrogen tetrachloroaurate, para -dimethylaminobenzaldehyde (PDAB), and modifiers including sodium metasilicate and cetyltrimethylammonium bromide—to enhance gold nanoparticle formation and surface plasmon resonance (SPR) resulting in visual blue to purple color development. This paper presents a summary of the crowdsourced submissions and results of laboratory testing.

Crowd-Sourced↗
NASA NTRS2006

Passive imaging based multi-cue hazard detection spacecraft safe landing

Accurate assessment of potentially damaging ground hazards during the spacecraft EDL (Entry, Descent and Landing) phase is crucial to insure a high probability of safe landing. A lander that encounters a large rock, falls off a cliff, or tips over on a steep slope can sustain mission ending damage. Guided entry is expected to shrink landing ellipses from 100-300 km to -10 km radius for the second generation landers as early as 2009. Regardless of size and location, however, landing ellipses will almost always contain hazards such as craters, discontinuities, steep slopes, and large rocks. It is estimated that an MSL (Mars Science Laboratory)-sized lander should detect and avoid 16- 150m diameter craters, vertical drops similar to the edges of 16m or 3.75m diameter crater, for high and low altitude HAD (Hazard Detection and Avoidance) respectively. It should also be able to detect slopes 20' or steeper, and rocks 0.75m or taller. In this paper we will present a passive imaging based, multi-cue hazard detection and avoidance (HDA) system suitable for Martian and other lander missions. This is the first passively imaged HDA system that seamlessly integrates multiple algorithm-crater detection, slope estimation, rock detection and texture analysis, and multicues- crater morphology, rock distribution, to detect these hazards in real time.

hazard detection↗
DOE OSTI2026

The role of source geometry and atmospheric propagation in global bolide infrasound detectability

Global infrasound monitoring provides a persistent means of detecting energetic bolide atmospheric entries, complementing optical observations and extending coverage over remote regions. We present a global assessment of the physical factors governing bolide infrasound detectability by correlating 623 bolide events reported by the Center for Near-Earth Object Studies between 2007 and 2025 with waveform data from the International Monitoring System. We identify 311 events with confirmed infrasound detections, corresponding to a detection rate of approximately 50%, substantially higher than inferred from earlier surveys, reflecting both the maturation of the global infrasound network and advances in automated, multi-frequency array processing. Analysis of flight parameters shows that infrasound detectability is selective rather than uniform across the bolide population. Detected events are preferentially associated with steeper entry angles and lower-altitude energy deposition, while shallow, high-altitude trajectories are less consistently observed. Very high-energy events remain detectable regardless of geometry, but for the more common lower-energy regime, observability depends on specific combinations of entry parameters and propagation conditions. This geometric dependence persists across comparable energy ranges and atmospheric conditions, indicating that entry angle exerts a primary control on detectability, with energy and propagation acting as secondary modulating factors. Furthermore, these results provide new physical constraints on bolide-atmosphere interactions and improve interpretation of global infrasound observations for planetary defense and atmospheric-entry studies.

Bolides↗
DOE OSTI2026

Performance evaluation of neutron noise analysis in detecting special nuclear materials

Reliable and rapid inspection techniques play a vital role in preventing illicit trafficking of special nuclear materials. Active interrogation systems using neutrons produced by portable, high-flux deuterium-deuterium or deuterium-tritium neutron generators are being actively developed as a secondary scanning tool for this purpose. In this study, a neutron noise analysis-based approach for detecting unshielded and shielded special nuclear materials by using a pulsed deuterium-tritium neutron generator was evaluated. Here, this approach analyzes the fluctuation of neutron counts. Its performance was quantified with regard to time-to-detection to achieve a minimum probability of detection of 99% and a probability of false alarm of less than 1% considering various amounts of special nuclear materials and different shielding configurations. It was demonstrated that this approach could detect 17 uranium slugs in 5 s given a neutron generator yield of 8.1 × 10 7 n/s. These slugs could be detected within a reasonable time frame (200 s) when they were shielded by 10.16 cm of high-density polyethylene. The results obtained using the neutron noise analysis approach were compared with those obtained using the commonly used differential die-away analysis technique, a sensitive technique for detecting the presence of fissile materials by utilizing the prompt fission neutrons produced when the source neutrons from a neutron generator are completely diminished. For example, the time to detect 2 unshielded uranium slugs was 2.1 s when using the differential die-away analysis technique; it increased to 93 s for the neutron noise analysis approach. Although the noise analysis-based approach exhibits an overall performance which is not as good as that of differential die-away, neutron noise provides an alternative method for effective detection of special nuclear materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Enhanced Stability and Sensitivity for CA-125 Detection Under Microfluidic Shear Flow Using Polyethylene Glycol-Coated Biosensor

The microfluidic-based point-of-care (POC) diagnostic tool has garnered significant interest in recent years, offering rapid and cost-effective disease detection. There is a growing trend toward integrating microfluidic platforms with biosensors, aligning lab-on-a-chip technologies with POC diagnostic devices. Despite numerous efforts to incorporate biosensors into microfluidic systems, researchers have performed very limited investigations on the stability of biomarker detection when biosensors operate under microfluidic shear flow conditions. Gold nanoparticles (AuNPs) are a widely employed material in capacitive biosensors for antibody immobilization and sensitivity enhancement. However, AuNPs have limitations in providing stable detection of biomarkers within microfluidic shear flow due to their agglomeration nature. This study addresses these limitations by employing 2 kDa polyethylene glycol (PEG) as an intermediate biofunctional layer to immobilize CA-125 antibodies on gold-interdigitated electrodes for the stable and accurate detection of CA-125 antigens. The stabilities and sensitivities of AuNPs and PEG-coated biosensors are evaluated under both static drop and microfluidic shear flow conditions for CA-125 antigen detection. The experimental results demonstrate a capacitive signal response (5660 pF at 10 kHz) 2.2 times higher using the PEG-coated biosensor than the signal (2551 pF at 10 kHz) measured by the AuNP-coated biosensor in the detection of CA-125 antigen–antibody conjugation under static drop conditions, indicating the higher sensitivity of the PEG-coated biosensor. Additionally, the PEG-coated biosensor exhibits better consistency for the CA-125 antigen detection between static drop and microfluidic shear flow conditions (Cp decrease in percentage (ΔCp%↓) = 2.9% at 10 kHz) compared to the electrical signals measured using the AuNP-coated biosensor (ΔCp%↓ = 32.4% at 10 kHz), which suggests that the PEG-coated biosensor demonstrates higher stability for CA-125 antigen detection under microfluidic shear flow conditions. With these significant improvements brought by the PEG-coated biosensor, especially under microfluidic conditions, a substantial hurdle in developing electrical biosensors for POC diagnostic applications has been overcome, expediting further advancements in the field.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Grid Edge Waveform Analytics Framework for Event Detection and Classification

This paper provides a grid edge waveform analytics framework for power system event detection and classification in the local as well as in the wide area. This framework overviews data excellence for event detection and classification. The data excellence describes the data acquisition process and requirements, data processing, data quality, and data integrity. Power system event detection in the local area based on different features such as energy-based, cyclostationary approach, template matching, and wavelet transform are also discussed. Furthermore, local area event detection and classification using approaches such as statistical, signal processing, artificial intelligence, and hybrid are also discussed. Moreover, an overview of wide-area event detection and classification along with several other aspects such as wide-area events, wide-area event detection approaches, event location and system performance, event pattern recognition, inter-area oscillation, and wide-area frequency response under variable deployment of inverter-based resources are also provided. The proposed framework is the first step toward the goal of developing appropriate tools and methodologies to detect and classify local as well as wide-area events using waveform analytics. The appropriate event detection and classification framework development is especially important now as more and more grid edge devices with communication capabilities are being deployed in the modern power grid than ever before.

Bhusal, Narayan↗
DOE OSTI2024

Elastic Changepoint Detection for Globally-indexed Functional Time Series Data with Climate Applications

Changepoint detection is a vital tool in the application of climate data analysis. Numerous types of climate observation data are most properly represented by functional time series, implying a need for accurate changepoint detection methods applicable to functional time series data. Such data taken at a global scale often contain both spatial heterogeneity and dependence as well as phase (time) misalignment. In this report, we present methods which can detect spatially-dependent changepoints while allowing different estimates of change time and change strength depending on location. Additionally, we provide extensions to this spatially-predicted model which controls for phase variability among observations. Our methods provide the ability to detect a single change, or control for epidemic changes (where a “return-to-normal” change is more likely to be detected than the initial change). We showcase results analyzing the June 1991 eruption of Mt. Pinatubo, where our methods demonstrate the ability to accurately detect both single and epidemic changepoints even in the presence of strong seasonal variability. We find that our spatially-predicted model improves the detection of relevant changepoints versus methods which do not take spatial information into account, and we find that controlling for phase variability helps to control the false discovery rate during the detection process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Development Fiber Optic Distributed System for Direct Detection of Subsurface Gases Leakages

Carbon, natural gas, and hydrogen gas storage is an emerging solution to safeguard us against pollution, support goals of negative carbon emission, and protect sources of renewable energy. Properly constructed storage wells provide a virtually impervious barrier to any unintended subsurface transmission. The ability to ensure the long-term integrity of such wells is vital to the success of any storage operation and be successful in the public eyes. Therefore, robust monitoring of any gas migration into the subsurface is highly sought. A fiber-optic distributed chemical sensor (DCS) enables monitoring of long-term well integrity along its depth, ensuring the success of any storage operation and bolsters public acceptance of the safety of the reservoir via leak early detection. The same technique can be applied to gas monitoring in pipeline networks and nuclear stockpile monitoring applications. Fiber based Raman spectroscopy enables DCS, as optical fibers can be deployed in virtually any environment and relay spectroscopic information over long distances back to the user. Hollow core fibers (HCF) make excellent DCSs as the air core of the fiber allows gas from the environment to diffuse into the core, which interacts with the laser signal that is carried in the air core. This work builds upon the previous LDRD project, Fiber Optic System for Direct Detection of Carbon Dioxide Leakage in Carbon Storage Wells (21-FS-003), in which the feasibility of Raman spectroscopy detection of Carbon Dioxide (CO2) in HCF detection was demonstrated. We mitigated the risk of this DCS technology by establishing and completing five objectives. The first objective was to model and optically characterize HCF uptake of CO2, establishing the relationship between HCF length, gas diffusion time, detectable gas concentration, and measured Raman intensity. In objective two, we developed a fiber core drilling recipe to enable additional diffusion ports in the fiber core and established a method for maintaining fiber strength and integrity post drilling. Objective three characterized the drilled fibers against the undrilled fibers, establishing the differences in the gas mechanics and optical properties and provided parameters to iterate the drilling process. In objective four, a fusion splicing technique was developed to join the HCF to conventional single-mode fibers, localizing the gas detection point at the drilled HCF hole, emulating a DCS. Lastly, objective five was the testing of the sensor in Edgar Mines at Colorado School of Mines on a CO2 pipeline with a simulated leak, to showcase the ability to detect CO2 leaks. This capstone result showed CO2 leak detection in < 10 minutes, raising the technology readiness level of HCF segments as deployable DCS.

organic↗
DOE OSTI2024

Passive Islanding Detection of Inverter-Based Resources in a Noisy Environment

Islanding occurs when a load is energized solely by local generators and can result in frequency and voltage instability, changes in current, and poor power quality. Poor power quality can interrupt industrial operations, damage sensitive electrical equipment, and induce outages upon the resynchronization of the island with the grid. This study proposes an islanding detection method employing a Duffing oscillator to analyze voltage fluctuations at the point of common coupling (PCC) under a high-noise environment. Unlike existing methods, which overlook the noise effect, this paper mitigates noise impact on islanding detection. Power system noise in PCC measurements arises from switching transients, harmonics, grounding issues, voltage sags and swells, electromagnetic interference, and power quality issues that affect islanding detection. Transient events like lightning-induced traveling waves to the PCC can also introduce noise levels exceeding the voltage amplitude by more than seven times, thus disturbing conventional detection techniques. The noise interferes with measurements and increases the nondetection zone (NDZ), causing failed or delayed islanding detection. The Duffing oscillator nonlinear dynamics enable detection capabilities at a high noise level. The proposed method is designed to detect the PCC voltage fluctuations based on the IEEE standard 1547 through the Duffing oscillator. For the voltages beyond the threshold, the Duffing oscillator phase trajectory changes from periodic to chaotic mode and sends an islanded operation command to the inverter. The proposed islanding detection method distinguishes switching transients and faults from an islanded operation. Experimental validation of the method is conducted using a 3.6 kW PV setup.

Energy & Fuels↗
NASA NTRS1995

A Game Theoretic Fault Detection Filter

The fault detection process is modelled as a disturbance attenuation problem. The solution to this problem is found via differential game theory, leading to an H(sub infinity) filter which bounds the transmission of all exogenous signals save the fault to be detected. For a general class of linear systems which includes some time-varying systems, it is shown that this transmission bound can be taken to zero by simultaneously bringing the sensor noise weighting to zero. Thus, in the limit, a complete transmission block can he achieved, making the game filter into a fault detection filter. When we specialize this result to time-invariant system, it is found that the detection filter attained in the limit is identical to the well known Beard-Jones Fault Detection Filter. That is, all fault inputs other than the one to be detected (the "nuisance faults") are restricted to an invariant subspace which is unobservable to a projection on the output. For time-invariant systems, it is also shown that in the limit, the order of the state-space and the game filter can be reduced by factoring out the invariant subspace. The result is a lower dimensional filter which can observe only the fault to be detected. A reduced-order filter can also he generated for time-varying systems, though the computational overhead may be intensive. An example given at the end of the paper demonstrates the effectiveness of the filter as a tool for fault detection and identification.

Chung, Walter H.↗
NASA NTRS1998

Optical Detection of Lightning from Space

Optical sensors have been developed to detect lightning from space during both day and night. These sensors have been fielded in two existing satellite missions and may be included on a third mission in 2002. Satellite-hosted, optically-based lightning detection offers three unique capabilities: (1) the ability to reliably detect lightning over large, often remote, spatial regions, (2) the ability to sample all (IC and CG) lightning, and (3) the ability to detect lightning with uniform (i.e., not range-dependent) sensitivity or detection efficiency. These represent significant departures from conventional RF-based detection techniques, which typically have strong range dependencies (biases) or range limitations in their detection capabilities. The atmospheric electricity team of the NASA Marshall Space Flight Center's Global Hydrology and Climate Center has implemented a three-step satellite lightning research program which includes three phases: proof-of-concept/climatology, science algorithm development, and operational application. The first instrument in the program, the Optical Transient Detector (OTD), is deployed on a low-earth orbit (LEO) satellite with near-polar inclination, yielding global coverage. The sensor has a 1300 x 1300 sq km field of view (FOV), moderate detection efficiency, moderate localization accuracy, and little data bias. The OTD is a proof-of-concept instrument and its mission is primarily a global lightning climatology. The limited spatial accuracy of this instrument makes it suboptimal for use in case studies, although significant science knowledge has been gained from the instrument as deployed.

Boccippio, Dennis J.↗
NASA NTRS1999

Propellant Feed System Leak Detection: Lessons Learned From the Linear Aerospike SR-71 Experiment (LASRE)

This paper presents pertinent results and assessment of propellant feed system leak detection as applied to the Linear Aerospike SR-71 Experiment (LASRE) program flown at the NASA Dryden Flight Research Center, Edwards, California. The LASRE was a flight test of an aerospike rocket engine using liquid oxygen and high-pressure gaseous hydrogen as propellants. The flight safety of the crew and the experiment demanded proven technologies and techniques that could detect leaks and assess the integrity of hazardous propellant feed systems. Point source detection and systematic detection were used. Point source detection was adequate for catching gross leakage from components of the propellant feed systems, but insufficient for clearing LASRE to levels of acceptability. Systematic detection, which used high-resolution instrumentation to evaluate the health of the system within a closed volume, provided a better means for assessing leak hazards. Oxygen sensors detected a leak rate of approximately 0.04 cubic inches per second of liquid oxygen. Pressure sensor data revealed speculated cryogenic boiloff through the fittings of the oxygen system, but location of the source(s) was indeterminable. Ultimately, LASRE was cancelled because leak detection techniques were unable to verify that oxygen levels could be maintained below flammability limits.

Hass, Neal↗
NASA NTRS2003

Kepler Mission to Detect Earth-like Planets

Kepler Mission to detect Earth-like planets in our Milky Way galaxy was approved by NASA in December 2001 for a 4-5 year mission. The launch is planned in about 5 years. The Kepler observatory will be placed in an Earth-trailing orbit. The unique feature of the Kepler Mission is its ability to detect Earth-like planets orbiting around solar-type stars at a distance similar to that of Earth (from our Sun); such an orbit could provide an environment suitable for supporting life as we know it. The Kepler observatory accomplishes this feat by looking for the transits of planetary object in front of their suns; Kepler has a photometric precision of 10E-5 (0.00001) to achieve such detections. Other ongoing planetary detection programs (based mostly on a technique that looks for the shifting of spectral lines of the primary star due to its planetary companions' motions around it) have detected massive planets (with masses in the range of Jupiter); such massive planets are not considered suitable for supporting life. If our current theories for the formation of planetary systems are valid, we expect to detect about 50 Earth-like planets during Kepler's 4-year mission (assuming a random distribution of the planetary orbital inclinations with respect to the line of sight from Kepler). The number of detection will increase about 640 planets if the planets to be detected are Jupiter-sized.

Kondo, Yoji↗