Search NASA⌕ Search

SEARCH · Search NASA

Results for “Deep potential”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Proving Ground Potential Mission and Flight Test Objectives and Near Term Architectures

NASA is developing a Pioneering Space Strategy to expand human and robotic presence further into the solar system, not just to explore and visit, but to stay. NASA's strategy is designed to meet technical and non-technical challenges, leverage current and near-term activities, and lead to a future where humans can work, learn, operate, and thrive safely in space for an extended, and eventually indefinite, period of time. An important aspect of this strategy is the implementation of proving ground activities needed to ensure confidence in both Mars systems and deep space operations prior to embarking on the journey to the Mars. As part of the proving ground development, NASA is assessing potential mission concepts that could validate the required capabilities needed to expand human presence into the solar system. The first step identified in the proving ground is to establish human presence in the cis-lunar vicinity to enable development and testing of systems and operations required to land humans on Mars and to reach other deep space destinations. These capabilities may also be leveraged to support potential commercial and international objectives for Lunar Surface missions. This paper will discuss a series of potential proving ground mission and flight test objectives that support NASA's journey to Mars and can be leveraged for commercial and international goals. The paper will discuss how early missions will begin to satisfy these objectives, including extensibility and applicability to Mars. The initial capability provided by the launch vehicle will be described as well as planned upgrades required to support longer and more complex missions. Potential architectures and mission concepts will be examined as options to satisfy proving ground objectives. In addition, these architectures will be assessed on commercial and international participation opportunities and on how well they develop capabilities and operations applicable to Mars vicinity missions.

Smith, R. Marshall↗
NASA NTRS2008

Extreme Helicity and Intense Convective Towers in Hurricane Bonnie

Helicity was calculated in Hurricane Bonnie (1998) using tropospheric-deep dropsonde soundings from the NASA Convection and Moisture Experiment. Large helicity existed downshear of the storm center with respect to the ambient vertical wind shear. It was associated with veering, semicircular hodographs created by strong, vortex-scale, radial-vertical flow induced by the shear. The most extreme values of helicity, among the largest ever reported in the literature, occurred in the vicinity of deep convective cells in the downshear-left quadrant. These cells reached as high as 17.5 km and displayed the temporal and spatial scales of supercells. Convective available potential energy (CAPE) averaged 861 J/kg downshear, but only about one-third as large upshear. The soundings nearest the deep cells were evaluated using two empirical supercell parameters that make use of CAPE, helicity, and/or shear. These parameters supported the possible existence of supercells as a consequence of the exceptional helicity combined with moderate but sufficient CAPE. Ambient vertical wind shear exceeded 12 m/s for 30 h, yet the hurricane maintained 50 m/s maximum winds. It is hypothesized that the long-lived convective cells enabled the storm to resist the negative impact of the shear. Supercells in large-helicity, curved-hodograph environments appear to provide a useful conceptual model for intense convection in the hurricane core. Helicity calculations might also give some insight into the behavior of vortical hot towers, which share some characteristics with supercells.

Molinari, John↗
NASA NTRS1979

Control considerations for CCV fighters at high angles of attack

Wind tunnel and piloted simulation studies were conducted to investigate the potential high angle of attack control problems that are introduced by the use of the CCV concept of relaxed static pitch stability (RSS) on fighter aircraft. A conventional wing/aft tail design incorporating modest levels of static instability and a close-coupled canard/wing design exhibiting very high levels of instability was investigated. Two types of high angle of attack control problems can result from the use of RSS: pitch departures caused by coupling and deep stall trim. Avoidance of these problems requires that the airplane have sufficient nose-down pitch control at high angles of attack. The effectiveness of several pitch control configurations were investigated including conventional aft-mounted stabilators, wing-mounted elevators, canard-mounted flaps, and all-moveable canards. Varying the incidence of the canards was the most effective scheme; however, very large deflections may be required on highly unstable configurations to prevent pitch departure without sacrificing roll performance and to avoid deep stall trim. For situations where the high angle of attack pitch control requirement is not met, control laws were developed to inhibit the departure and to allow deep stall recovery. However, these schemes involve limiting airplane roll capability and therefore can potentially compromise maneuverability.

Nguyen, L. T.↗
NASA NTRS2016

Carbon Nanofiber Nanoelectrodes for Neural Stimulation and Chemical Detection: The Era of Smart Deep Brain Stimulation

A sensor platform based on vertically aligned carbon nanofibers (CNFs) has been developed. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report two studies using vertically aligned CNF nanoelectrodes for biomedical applications. CNF arrays are investigated as neural stimulation and neurotransmitter recording electrodes for application in deep brain stimulation (DBS). Polypyrrole coated CNF nanoelectrodes have shown great promise as stimulating electrodes due to their large surface area, low impedance, biocompatibility and capacity for highly localized stimulation. CNFs embedded in SiO2 have been used as sensing electrodes for neurotransmitter detection. Our approach combines a multiplexed CNF electrode chip, developed at NASA Ames Research Center, with the Wireless Instantaneous Neurotransmitter Concentration Sensor (WINCS) system, developed at the Mayo Clinic. Preliminary results indicate that the CNF nanoelectrode arrays are easily integrated with WINCS for neurotransmitter detection in a multiplexed array format. In the future, combining CNF based stimulating and recording electrodes with WINCS may lay the foundation for an implantable "smart" therapeutic system that utilizes neurochemical feedback control while likely resulting in increased DBS application in various neuropsychiatric disorders. In total, our goal is to take advantage of the nanostructure of CNF arrays for biosensing studies requiring ultrahigh sensitivity, high-degree of miniaturization, and selective biofunctionalization.

bioinstrumentation↗
NASA NTRS2016

Carbon Nanofiber Nanoelectrodes for Neural Stimulation and Chemical Detection: The Era of "Smart" Deep Brain Stimulation

A sensor platform based on vertically aligned carbon nanofibers (CNFs) has been developed. Their inherent nanometer scale, high conductivity, wide potential window, good biocompatibility and well-defined surface chemistry make them ideal candidates as biosensor electrodes. Here, we report two studies using vertically aligned CNF nanoelectrodes for biomedical applications. CNF arrays are investigated as neural stimulation and neurotransmitter recording electrodes for application in deep brain stimulation (DBS). Polypyrrole coated CNF nanoelectrodes have shown great promise as stimulating electrodes due to their large surface area, low impedance, biocompatibility and capacity for highly localized stimulation. CNFs embedded in SiO2 have been used as sensing electrodes for neurotransmitter detection. Our approach combines a multiplexed CNF electrode chip, developed at NASA Ames Research Center, with the Wireless Instantaneous Neurotransmitter Concentration Sensor (WINCS) system, developed at the Mayo Clinic. Preliminary results indicate that the CNF nanoelectrode arrays are easily integrated with WINCS for neurotransmitter detection in a multiplexed array format. In the future, combining CNF based stimulating and recording electrodes with WINCS may lay the foundation for an implantable smart therapeutic system that utilizes neurochemical feedback control while likely resulting in increased DBS application in various neuropsychiatric disorders. In total, our goal is to take advantage of the nanostructure of CNF arrays for biosensing studies requiring ultrahigh sensitivity, high-degree of miniaturization, and selective biofunctionalization.

human body↗
NASA NTRS2012

The Potential for a Ka-band (32 GHz) Worldwide VLBI Network

Ka-band (32 GHz, 9mm) Very Long Baseline Interferometric (VLBI) networking has now begun and has tremendous potential for expansion over the next few years. Ka-band VLBI astrometry from NASA's Deep Space Network has already developed a catalog of 470 observable sources with highly accurate positions. Now, several antennas worldwide are planning or are considering adding Ka-band VLBI capability. Thus, there is now an opportunity to create a worldwide Ka-band network with potential for high resolution imaging and astrometry. With baselines approaching a Giga-lambda, a Ka-band network would be able to probe source structure at the nano-radian (200 as) level ( 100X better than Hubble) and thus gain insight into the astrophysics of the most compact regions of emission in active galactic nuclei. We discuss the advantages of Ka-band, show the known sources and candidates, simulate projected baseline (uv) coverage, and discuss potential radio frequency feeds. The combination of these elements demonstrates the feasibility of a worldwide Ka network within the next few years!

quasar↗
NASA NTRSDate not supplied

Supporting Crew Medical Decisions on Deep Space Missions: A Real-Time Performance Monitoring

Crewed missions into deep space will require astronauts to respond autonomously to safety- and time-critical anomalies. These and other potential issues will require the continuous monitoring and recognition of potentially subtle, but complex, anomalous data patterns. NASA continues to investigate real-time metrics for Extravehicular Operations1 and for providing feedback to improve performance2. Since it is unknown how long-term exposure to deep space will affect crew health, continuous monitoring of clinical and subclinical status is warranted. NASA is characterizing crew medical decision-support needs and identifying the recommended requirements of a Clinical Decision Support System (CDSS) within the Exploration Medical Capability Element (ExMC) of the Human Research Program3. Early detection, and continuous monitoring, of performance may provide an effective prognostic capability for assessing crew health state, and the identified requirements could be provided for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. There is evidence to suggest that automatic, unobtrusive collection of keystroke features, such as alphanumeric key latencies, backspaces or typing rhythm, could be a valuable performance screening tool. Keystroke features show significant differences between control subjects and patients with overt clinical illness, such as multiple sclerosis4 and Parkinson’s disease5, as well as behavioral health and performance issues, such as mild cognitive impairment6 and depression7. This work is exploring a capability for the assessment of early task performance decline in crew as they perform daily activities. Timestamped keyboard entries are continuously collected and stored. Nominal keystroke interactions are compared to those obtained after exposure to spaceflight stressors, e.g., fatigue, to determine the methods sensitivity. This work will pave the way toward an objective detection tool that may be deployed in a spaceflight setting.

clinical↗
NASA NTRS2022

TruePAL – An AI Assistant for First Responder Safety

This paper presents the development of an AI assistant, Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL), to provide real-time warning of risks of potential crashes to the first responders. The TruePAL system employs an AI and deep learning technology for saving first responders and roadside crews lives in and around active traffic. A deep neural network (DNN) and a Non-Axiomatic Reasoning System (NARS) are implemented as an AI system. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL team has developed an explainable AI approach by opening up the DNN blackbox to extract the activation filters of various features and parts of the targeted objects. The combination of DNN and NARS makes the TruePAL system explainable to the users. TruePAL ingests on-board cameras, radar, and other sensor signals, analyzes the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. The TruePAL team, in collaboration with the Miami/Dade Police Dept., has designed five use cases and multiple sub-scenarios in a CARLA driving simulator to test the capability of TruePAL in timely warning to the first responder drivers in potential crash scenarios. We have successfully demonstrated its capability of timely warning in over a dozen scenarios based on the use cases. The preliminary test simulation results show that TruePAL could provide the drivers and crew members advanced warning before a crash occurs.

Chow, Edward↗
NASA NTRS1988

Storage and computationally efficient permutations of factorized covariance and square-root information arrays

A unified method to permute vector stored Upper triangular Diagonal factorized covariance and vector stored upper triangular Square Root Information arrays is presented. The method involves cyclic permutation of the rows and columns of the arrays and retriangularization with fast (slow) Givens rotations (reflections). Minimal computation is performed, and a one dimensional scratch array is required. To make the method efficient for large arrays on a virtual memory machine, computations are arranged so as to avoid expensive paging faults. This method is potentially important for processing large volumes of radio metric data in the Deep Space Network.

Muellerschoen, R. J.↗
NASA NTRS2000

Technology Assessment of Doe's 55-we Stirling Technology Demonstrator Convector (TDC)

The Department of Energy (DOE), Germantown, Maryland and the NASA Glenn Research Center (GRC), Cleveland, Ohio are developing a Stirling Convertor for an advanced radioisotope power system as a potential power source for spacecraft on-board electric power for NASA deep space science missions. The Stirling Convertor is being evaluated as an alternative high efficiency power source to replace Radioisotope Thermoelectric Generators (RTGs). Stirling Technology Company (STC), Kennewick, Washington, is developing the highly efficient, long life 55-We free-piston Stirling Convertor known as the Technology Demonstrator Convertor (TDC) under contract to DOE. GRC provides Stirling technology expertise under a Space Act Agreement with the DOE. Lockheed Martin Astronautics (LMA), Valley Forge, Pennsylvania is the current power system integrator for the Advanced Radioisotope Power System (ARPS) Project for the DOE. JPL is responsible for the Outer Planets/Solar Probe Project for NASA.

Furlong, Richard↗
NASA NTRS2002

Impact Testing of a Stirling Converter's Linear Alternator

The U.S. Department of Energy (DOE), in conjunction with the NASA John H. Glenn Research Center and Stirling Technology Company, are currently developing a Stirling convertor for a Stirling Radioisotope Generator (SRG). NASA Headquarters and DOE have identified the SRG for potential use as an advanced spacecraft power system for future NASA deep-space and Mars surface missions. Low-level dynamic impact tests were conducted at NASA Glenn Research Center's Structural Dynamics Laboratory as part of the development of this technology. The purpose of this test was to identify dynamic structural characteristics of the Stirling Technology Demonstration Convertor (TDC). This paper addresses the test setup, procedure, and results of the impact testing conducted on the Stirling TDC in May 2001.

Suarez, Vicente J.↗
NASA NTRS2003

Alloy Interface Interdiffusion Modeled

With renewed interest in developing nuclear-powered deep space probes, attention will return to improving the metallurgical processing of potential nuclear fuels so that they remain dimensionally stable over the years required for a successful mission. Previous work on fuel alloys at the NASA Glenn Research Center was primarily empirical, with virtually no continuing research. Even when empirical studies are exacting, they often fail to provide enough insight to guide future research efforts. In addition, from a fundamental theoretical standpoint, the actinide metals (which include materials used for nuclear fuels) pose a severe challenge to modern electronic-structure theory. Recent advances in quantum approximate atomistic modeling, coupled with first-principles derivation of needed input parameters, can help researchers develop new alloys for nuclear propulsion.

Bozzolo, Guillermo H.↗
NASA NTRS2007

Structural Benchmark Testing for Stirling Convertor Heater Heads

The National Aeronautics and Space Administration (NASA) has identified high efficiency Stirling technology for potential use on long duration Space Science missions such as Mars rovers, deep space missions, and lunar applications. For the long life times required, a structurally significant design limit for the Stirling convertor heater head is creep deformation induced even under relatively low stress levels at high material temperatures. Conventional investigations of creep behavior adequately rely on experimental results from uniaxial creep specimens, and much creep data is available for the proposed Inconel-718 (IN-718) and MarM-247 nickel-based superalloy materials of construction. However, very little experimental creep information is available that directly applies to the atypical thin walls, the specific microstructures, and the low stress levels. In addition, the geometry and loading conditions apply multiaxial stress states on the heater head components, far from the conditions of uniaxial testing. For these reasons, experimental benchmark testing is underway to aid in accurately assessing the durability of Stirling heater heads. The investigation supplements uniaxial creep testing with pneumatic testing of heater head test articles at elevated temperatures and with stress levels ranging from one to seven times design stresses. This paper presents experimental methods, results, post-test microstructural analyses, and conclusions for both accelerated and non-accelerated tests. The Stirling projects use the results to calibrate deterministic and probabilistic analytical creep models of the heater heads to predict their life times.

Krause, David L.↗
NASA NTRS2015

Center Planning and Development: Multi-User Spaceport Initiatives

The Vehicle Assembly building at NASAs Kennedy Space Center has been used since 1966 to vertically assemble every launch vehicle, since the Apollo Program, launched from Launch Complex 39 (LC-39). After the cancellation of the Constellation Program in 2010 and the retirement of the Space Shuttle Program in 2011, the VAB faced an uncertain future. As the Space Launch System (SLS) gained a foothold as the future of American spaceflight to deep space, NASA was only using a portion of the VABs initial potential. With three high bays connected to the Crawler Way transportation system, the potential exists for up to three rockets to be simultaneously processed for launch. The Kennedy Space Center (KSC) Master plan, supported by the Center Planning and Development (CPD) Directorate, is guiding Kennedy toward a 21st century multi-user spaceport. This concept will maintain Kennedy as the United States premier gateway to space and provide multi-user operations through partnerships with the commercial aerospace industry. Commercial aerospace companies, now tasked with transporting cargo and, in the future, astronauts to the International Space Station (ISS) via the Commercial Resupply Service (CRS) and Commercial Crew Program (CCP), are a rapidly growing industry with increasing capabilities to make launch operations more economical for both private companies and the government. Commercial operations to Low Earth Orbit allow the government to focus on travel to farther destinations through the SLS Program. With LC-39B designated as a multi-use launch pad, companies seeking to use it will require an integration facility to assemble, integrate, and test their launch vehicle. An Announcement for Proposals (AFP) was released in June, beginning the process of finding a non-NASA user for High Bay 2 (HB2) and the Mobile Launcher Platforms (MLPs). An Industry Day, a business meeting and tour for interested companies and organizations, was also arranged to identify and answer any additional questions posed by potential proposers. After amending the AFP and posting additional material for potential users to consider, proposals are being accepted until July 31, at which point they will be evaluated to determine the proposer which best meets the objectives of the government. By identifying VAB HB2 as available and seeking proposals from the commercial sector for VAB HB2 and MLP use, Center Planning and Development is ensuring Kennedy Space Centers relevance in the evolving launch industry of the 21st century.

AFP↗
NASA NTRS2018

An Analysis of the Lightning Jump Algorithm Using Geostationary Lightning Mapper Flashes

Lightning's relation to severe weather has been studied since the 1980's. The invention of the Lightning Mapping Array allowed for total lightning measurements in a 125 km operational range. This brought forth an automated lightning Jump Algorithm (LIA) that predicted severe weather based on two-sigma increases in total lightning. The LIA's biggest downfall is being restrained to the limited field of view (FOV) of LMA's. The launch of the Geostationary Lightning Mapper (GLM) aboard the GOES-16 satellite now gives us hemispheric total lightning measurements. The wide FOV makes the GLM a good candidate to apply the LIA to. However the GLM and LMA have some differences. One being the coarser spatial resolution of GLM. Another being that LMA measures very high frequency (VHF) electromagnetic radiation while GLM measures optical radiation. These differences suggest an extensive study must be done on using the LIA with GLM to understand potential differences in the LIA and to maximize its operational skill. Four deep dive cases are conducted showcasing the differences between the GLM and LMA and their jumps.

Curtis, Nathan↗
NASA NTRSDate not supplied

Surface Systems and Interface Standardization

Space exploration on planetary surfaces will require the use of various surface systems which will likely need to interface with one another. These systems must communicate and share data, as well as distribute power and transfer fluids for sustainable surface operations. Such systems can range from landers, surface habitats, mobility systems, cargo, and In-Situ Resource Utilizations (ISRUs). Previous and current programs have developed space interoperability standards that help aid in reducing potential risks of interface integration. One example of this is the International Deep Space Interoperability Standards (IDSIS) which focuses on deep space exploration. A goal of the Artemis program is to develop a sustained human presence on the lunar surface that would be a training ground for future Mars exploration. Therefore, it will be beneficial to identify interface standards between the surface assets which will help mitigate risk and reduce complexity in the harsh environments of space exploration. A key contribution to sustainability is commonality between hardware and software interfaces. Generic interfaces for data, power, and fluids will reduce risk, promote interoperability, and define standard interfaces across surface exploration projects and programs. Standardized interfaces would be advantageous for improving efficiency and reducing overall complexity, which are critical considerations for future space exploration. Furthermore, it will provide cost reductions to the Artemis programs over their life cycle (in Operations & Maintenance (O&M) and Logistics). Unique proprietary interfaces if considered or allowed would not only increase complexity but also add cost to the programs. Of course, understanding what will work and not work effectively in these unique environments such as the lunar surface is important. These unique environments require much needed intelligent design, prototyping, comprehensive testing, and field experience, utilizing consensus on common interface solutions.

Jaime Gomez↗
NASA NTRS2024

Evaluation of Machine Learning and Deep Learning Algorithms for Fire Prediction in Southeast Asia

Vegetation fires are prevalent in South/Southeast Asian countries, making fire prediction crucial due to their potential environmental, economic, and social impacts. Accurate predictions of fires facilitate timely interventions, helping to mitigate uncontrolled fires that can lead to biodiversity loss and air quality issues. In this study, we utilize VIIRS satellite-derived fire data alongside six machine learning and deep learning models—Simple Persistence, Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), CNN-LSTM, and ConvLSTM—to determine the most effective fire prediction model, using Root Mean Square Error (RMSE) as the metric. Our results indicate that the CNN model is the most reliable in regions with spatial dependencies, such as Brunei, Indonesia, Malaysia, the Philippines, Timor-Leste, and Thailand. Conversely, the ConvLSTM model excels in countries with complex spatiotemporal dynamics like Laos, Myanmar, and Vietnam. The CNN-LSTM hybrid model also performed well in Cambodia, suggesting a need for a balanced approach in areas requiring both spatial and temporal feature extraction. Furthermore, simpler models like Persistence and MLP showed limitations in capturing dynamic patterns and temporal dependencies. Our findings highlight the importance of evaluating models before implementing any decision support systems (DSS) in fire management. By tailoring models to specific regional fire data, we can enhance prediction accuracy and responsiveness, ultimately improving fire risk management in Southeast Asia and beyond.

Deep learning↗
NASA NTRSDate not supplied

The BioSensor Instrument Beyond LEIA: a Versatile Platform for Lunar Biology

Introduction: The BioSensor is a deep-space-compatible automated microfluidic culturing instrument. While originally designed to measure the effects of deep space radiation on yeast growth for the BioSentinel mission, it has the potential to host a diverse range of life science experiments with single- and/or multi-celled organisms and can be adapted to interface with a diverse range of platforms in both crewed and uncrewed settings. It is therefore a leading candidate for hosting life sciences experimentation associated with a lunar surface habitat. BioSensor design: The function of the BioSensor is to monitor the growth and metabolic activity of samples in batch fluidic culture, without the need for crew involvement. The current configuration houses organisms in 16 wells within 16 microfluidic cards, accommodating a total of 256 samples, replicates, and controls. Each well has an optical system including three LEDs and a photodiode detector to measure absorbance at three wavelengths, enabling measurement of optical density, color change in dyes such as alamarBlue, and bioproduction of pigmented compounds. Organisms are loaded into fluidic wells and air-dried for storage during integration, launch, and transit, then activated by the introduction of culture medium from storage bags via manifolds that fill one card at a time. Temperature is controlled by individual card heaters, and timing of all activities (fluidics fills, optical measurements, temperatures) is directed by an experiment script. The self-contained BioSensor payload is roughly 4U in volume; with electrical/mechanical/thermal interface, e.g. for operation on ISS or a lunar lander, as well as a linear energy-transfer (LET) charged-particle radiation spectrometer, the entire system is closer to 6U. BioSentinel and LEIA: Flown on the ISS and in a deep-space free flyer for BioSentinel, the BioSensor has been modified for use in the LEIA mission, including improvements to reduce the sensitivity to lengthy launch delays. LEIA will monitor yeast growth in the radiation and reduced-gravity environment of the lunar surface no earlier than 2026, on a CLPS lander [4]. Changes include accommodating additional culture media and an additional LED color for a new biological assay (bioproduction of carotenoids-- dietary antioxidants), as well as modifications to the housing to allow late-load biology changeout and improved isolation between fluidics and electronics. Future prospects: Future work with the BioSensor, beyond LEIA, will include expanding the range and diversity of organisms and assays accommodated. Preliminary work has demonstrated the growth of Arabidopsis seedlings in BioSensor fluidic cards, including optical measurements of growth rate over time. Minor modifications could allow measurement of phenotypes related to photosynthetic capacity in both plants and cyanobacteria. The experimental capabilities of the BioSensor could be dramatically increased by introducing the capability for fluorescence measurements, and/or the design of novel biological assays using luminescence. The BioSensor can also be adapted for new platforms and experiment settings; in addition to free-flyer, ISS, and CLPS lander, a preliminary design concept has been developed for crewed deployment directly to the lunar surface. The instrument could be accommodated inside a lunar habitat, where its automated operation would make it an excellent candidate for experiments from fundamental investigations into the response of organisms to lunar surface conditions to applied-science purposes such as screening engineered strains of various organisms for bioproduction capability.

J A Lee↗