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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Future Vision for Autonomous Ocean Observations

Autonomous platforms already make observations over a wide range of temporal and spatial scales, measuring salinity, temperature, nitrate, pressure, oxygen, biomass; and many other parameters. However, the observations are not comprehensive. Future autonomous systems need to be more affordable, more modular, more capable and easier to operate. Creative new types of platforms and new compact, low power, calibrated and stable sensors are under development to expand autonomous observations. Communications and recharging need bandwidth and power which can be supplied by standardized docking stations. In situ power generation will also extend endurance for many types of autonomous platforms, particularly autonomous surface vehicles. Standardized communications will improve ease of use, interoperability, and enable coordinated behaviors. Improved autonomy and communications will enable adaptive networks of autonomous platforms. Improvements in autonomy will have three aspects: hardware, control, and operations. As sensors and platforms have more onboard processing capability and energy capacity, more measurements become possible. Control systems and software will have the capability to address more complex states and sophisticated reactions to sensor inputs, which allows the platform to handle a wider variety of circumstances without direct operator control. Operational autonomy is increased by reducing operating costs. To maximize the potential of autonomous observations new standards and best practices are needed. In some applications, focus on common platforms and volume purchases could lead to significant cost reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as EGO for the emerging glider operations should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

47 OTHER INSTRUMENTATION↗
NASA NTRS1989

Low frequency electric and magnetic fields

Following preliminary investigations of the low frequency electric and magnetic fields that may exists in the Earth-ionospheric cavity, measurements were taken with state-of-the art spectrum analyzers. As a follow up to this activity, an investigation was initiated to determine sources and values for possible low frequency signal that would appear in the cavity. The lowest cavity resonance is estimated at about 8 Hz, but lower frequencies may be an important component of our electromagnetic environment. The potential field frequencies produced by the electron were investigated by a classical model that included possible cross coupling of the electric and gravitation fields. During this work, an interesting relationship was found that related the high frequency charge field with the extremely low frequency of the gravitation field. The results of numerical calculations were surprisingly accurate and this area of investigation is continuing. The work toward continued development of a standardized monitoring facility is continuing with the potential of installing the prototype at West Virginia State College early in 1990. This installation would be capable of real time monitoring of ELF signals in the Earth-ionoshpere cavity and would provide some directional information. A high gain, low noise, 1/f frequency corrected preamplifier was designed and tested for the ferrite core magnetic sensor. The potential application of a super conducting sensor for the ELF magnetic field detection is under investigation. It is hoped that a fully operational monitoring network could pinpoint the location of ELF signal sources and provide new information on where these signals originate and what causes them, assuming that they are natural in origin.

Spaniol, Craig↗
NASA NTRS2016

Enabling Wireless Avionics Intra-Communications

The Electromagnetics and Sensors Branch of NASA Langley Research Center (LaRC) is investigating the potential of an all-wireless aircraft as part of the ECON (Efficient Reconfigurable Cockpit Design and Fleet Operations using Software Intensive, Networked and Wireless Enabled Architecture) seedling proposal, which is funded by the Convergent Aeronautics Solutions (CAS) project, Transformative Aeronautics Concepts (TAC) program, and NASA Aeronautics Research Institute (NARI). The project consists of a brief effort carried out by a small team in the Electromagnetic Environment Effects (E3) laboratory with the intention of exposing some of the challenges faced by a wireless communication system inside the reflective cavity of an aircraft and to explore potential solutions that take advantage of that environment for constructive gain. The research effort was named EWAIC for "Enabling Wireless Aircraft Intra-communications." The E3 laboratory is a research facility that includes three electromagnetic reverberation chambers and equipment that allow testing and generation of test data for the investigation of wireless systems in reflective environments. Using these chambers, the EWAIC team developed a set of tests and setups that allow the intentional variation of intensity of a multipath field to reproduce the environment of the various bays and cabins of large transport aircraft. This setup, in essence, simulates an aircraft environment that allows the investigation and testing of wireless communication protocols that can effectively be used as a tool to mitigate some of the risks inherent to an aircraft wireless system for critical functions. In addition, the EWAIC team initiated the development of a computational modeling tool to illustrate the propagation of EM waves inside the reflective cabins and bays of aircraft and to obtain quantifiable information regarding the degradation of signals in aircraft subassemblies. The nose landing gear of a UAV CAD model was used to model the propagation of a system in a "deployed" configuration versus a "stowed" configuration. The differences in relative field strength provide valuable information about the distribution of the field that can be used to engineer RF links with optimal radiated power and antenna configuration that accomplish the intended system reliability. Such modeling will be necessary in subsequent studies for managing multipath propagation characteristics inside a main cabin and to understand more complex environments, such as the inside wings, landing gear bays, cargo bays, avionics bays, etc. The results of the short research effort are described in the present document. The team puts forth a set of recommendations with the intention of informing the project and program leadership of the future work that, in the opinion of the EWAIC team, would assist the ECON team reach the intended goal of developing an all-wireless aircraft.

Torres, Omar↗
NASA NTRS1993

AVIRIS and TIMS data processing and distribution at the land processes distributed active archive center

The U.S. Government has initiated the Global Change Research program, a systematic study of the Earth as a complete system. NASA's contribution of the Global Change Research Program is the Earth Observing System (EOS), a series of orbital sensor platforms and an associated data processing and distribution system. The EOS Data and Information System (EOSDIS) is the archiving, production, and distribution system for data collected by the EOS space segment and uses a multilayer architecture for processing, archiving, and distributing EOS data. The first layer consists of the spacecraft ground stations and processing facilities that receive the raw data from the orbiting platforms and then separate the data by individual sensors. The second layer consists of Distributed Active Archive Centers (DAAC) that process, distribute, and archive the sensor data. The third layer consists of a user science processing network. The EOSDIS is being developed in a phased implementation. The initial phase, Version 0, is a prototype of the operational system. Version 0 activities are based upon existing systems and are designed to provide an EOSDIS-like capability for information management and distribution. An important science support task is the creation of simulated data sets for EOS instruments from precursor aircraft or satellite data. The Land Processes DAAC, at the EROS Data Center (EDC), is responsible for archiving and processing EOS precursor data from airborne instruments such as the Thermal Infrared Multispectral Scanner (TIMS), the Thematic Mapper Simulator (TMS), and Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). AVIRIS, TIMS, and TMS are flown by the NASA-Ames Research Center ARC) on an ER-2. The ER-2 flies at 65000 feet and can carry up to three sensors simultaneously. Most jointly collected data sets are somewhat boresighted and roughly registered. The instrument data are being used to construct data sets that simulate the spectral and spatial characteristics of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument scheduled to be flown on the first EOS-AM spacecraft. The ASTER is designed to acquire 14 channels of land science data in the visible and near-IR (VNIR), shortwave-IR (SWIR), and thermal-IR (TIR) regions from 0.52 micron to 11.65 micron at high spatial resolutions of 15 m to 90 m. Stereo data will also be acquired in the VNIR region in a single band. The AVIRIS and TMS cover the ASTER VNIR and SWIR bands, and the TIMS covers the TIR bands. Simulated ASTER data sets have been generated over Death Valley, California, Cuprite, Nevada, and the Drum Mountains, Utah using a combination of AVIRIS, TIMS, amd TMS data, and existing digital elevation models (DEM) for the topographic information.

Mah, G. R.↗
NASA NTRS1991

A cost-effective intelligent robotic system with dual-arm dexterous coordination and real-time vision

Dexterous coordination of manipulators based on the use of redundant degrees of freedom, multiple sensors, and built-in robot intelligence represents a critical breakthrough in development of advanced manufacturing technology. A cost-effective approach for achieving this new generation of robotics has been made possible by the unprecedented growth of the latest microcomputer and network systems. The resulting flexible automation offers the opportunity to improve the product quality, increase the reliability of the manufacturing process, and augment the production procedures for optimizing the utilization of the robotic system. Moreover, the Advanced Robotic System (ARS) is modular in design and can be upgraded by closely following technological advancements as they occur in various fields. This approach to manufacturing automation enhances the financial justification and ensures the long-term profitability and most efficient implementation of robotic technology. The new system also addresses a broad spectrum of manufacturing demand and has the potential to address both complex jobs as well as highly labor-intensive tasks. The ARS prototype employs the decomposed optimization technique in spatial planning. This technique is implemented to the framework of the sensor-actuator network to establish the general-purpose geometric reasoning system. The development computer system is a multiple microcomputer network system, which provides the architecture for executing the modular network computing algorithms. The knowledge-based approach used in both the robot vision subsystem and the manipulation control subsystems results in the real-time image processing vision-based capability. The vision-based task environment analysis capability and the responsive motion capability are under the command of the local intelligence centers. An array of ultrasonic, proximity, and optoelectronic sensors is used for path planning. The ARS currently has 18 degrees of freedom made up by two articulated arms, one movable robot head, and two charged coupled device (CCD) cameras for producing the stereoscopic views, and articulated cylindrical-type lower body, and an optional mobile base. A functional prototype is demonstrated.

Marzwell, Neville I.↗
NASA NTRS2006

Ikhana: A NASA UAS Supporting Long Duration Earth Science Missions

NASA's Ikhana unmanned aerial vehicle (UAV) is a General Atomics MQ-9 Predator-B modified to support the conduct of Earth science missions for the NASA Science Mission Directorate through partnerships, other government agencies and universities. Ikhana, a Native American word meaning 'intelligence', can carry over 2000 lbs of atmospheric and remote sensing instruments in the payload bay and external pods. The aircraft is capable of mission durations in excess of 24 hours at altitudes above 40,000 ft. Redundant flight control, avionics, power, and network systems increase the system reliability and allow easier access to public airspace. The aircraft is remotely piloted from a mobile ground control station (GCS) using both C-band line-of-sight and Ku-band over-the-horizon satellite datalinks. NASA's GCS has been modified to support on-site science monitoring, or the downlink data can be networked to remote sites. All ground support systems are designed to be deployable to support global Eart science investigations. On-board support capabilities include an instrumentation system and an Airborne Research Test System (ARTS). The ARTS can host research algorithms that will autonomously command and control on-board sensors, perform sensor health monitoring, conduct data analysis, and request changes to the flight plan to maximize data collection. The ARTS also has the ability to host algorithms that will autonomously control the aircraft trajectory based on sensor needs, (e.g. precision trajectory for repeat pass interferometry) or to optimize mission objectives (e.g. search for specific atmospheric conditions). Standard on-board networks will collect science data for recording and for inclusion in the aircraft's high bandwidth downlink. The Ikhana project will complete GCS development, science support systems integration, external pod integration and flight clearance, and operations crew training in early 2007. A large-area remote sensing mission is currently scheduled for the Summer 2007.

Cobleigh, Brent R.↗
NASA NTRS2011

Low-Cost Miniaturized Laser Heterodyne Radiometer for Highly Sensitive Detection of CO2 and CH4 in the Atmospheric Column

We present a new passive ground-network instrument capable of measuring carbon dioxide (CO2) at 1.57 microns and methane (CH4) at 1.62 microns -- key for validation of OCO-2, ASCENDS, OCO-3, and GOSAT. Designed to piggy-back on an AERONET sun tracker (AERONET is a global network of more than 450 aerosol sensing instruments), this instrument could be rapidly deployed into the established AERONET network of ground sensors. Because aerosols induce a radiative effect that influences terrestrial carbon exchange, this simultaneous measure of aerosols and carbon cycle gases offers a uniquely comprehensive approach. This instrument is a variation of a laser heterodyne radiometer (LHR) that leverages recent advances in telecommunications lasers to miniaturize the instrument (the current version fits in a carry-on suitcase). In this technique, sunlight that has undergone absorption by the trace gas is mixed with laser light at a frequency matched to a trace gas absorption feature in the infrared (IR). Mixing results in a beat signal in the RF (radio frequency) region that can be related to the atmospheric concentration. By dividing this RF signal into a filter bank, concentrations at different altitudes can be resolved. For a one second integration, we estimate column sensitivities of 0.1 ppmv for CO2, and <1 ppbv for CH4.

Wilson, Emily L.↗
DOE OSTI2022

Cyber-Resilient Frequency Control of Power Grids with Energy Storage Systems

The integration of synchronous generators and energy storage systems operated through communication networks introduces new challenges and vulnerabilities to the electric grid, where cyber attacks can corrupt sensor measurements or control inputs and interrupt functions such as frequency regulation. This paper proposes a defense methodology for the design of resilient operating constraints imposed on each generation and storage unit in order to prevent any attack sequence from driving the system's frequency to unsafe conditions. The resilient operating constraints are found by using ellipsoidal approximations of the reachable set of the power system, leading to a convex optimization problem with linear matrix inequalities. Numerical results in a single-area power system with synchronous generation and energy storage demonstrate how the resilient constraints provide security guarantees against any type of attack affecting frequency measurements or controller setpoints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Automation and Robotics for Space-Based Systems, 1991

A NASA Langley workshop on Automation and Robotics for Space-Based Systems was held on December 10, 1991. This conference proceedings document presents the overhead slides from each speaker at this event. The purpose of this in-house workshop was to assess the state-of-the-art of automation and robotics for space operations from a LaRC perspective and to identify areas of opportunity for future research. The workshop was sponsored by the Guidance, Navigation, and Control Technical Committee, chaired by Mr. Raymond C. Montgomery. Nineteen talks were given, reflecting a high level of interest in the field of automation at NASA Langley. Over half of the presentations came from the Automation Technology Branch, covering telerobotic control, EVA and IVA robotics, hand controllers for teleoperation, sensors, neural networks, and automated structural assembly, all applied to space missions. Other talks covered RMS active damping augmentation, space crane work, modeling, simulation, and control of large, flexible space manipulators, and virtual passive controller designs for space robots.

Automation↗
DOE OSTI2021

Novel Data Driven Noise Emulation Framework using Deep Neural Network for Generating Synthetic PMU Measurements

Sensors play a critical role in supporting day-to-day grid operations and they are essential to operator’s decision-making process. Furthermore, sensors and sensor behaviors need to be emulated with grid simulations to perform modeling studies and to design cutting edge power systems applications. Ensuring the accurate behavior of these applications requires accurate emulation of sensors and pertinent signals. However, most grid simulators and modeling tools assume either zero error scenarios or simplistic noise models that may not always correlate to real-world sensors. To address the above issue, this work presents an initial study on the noise characteristics of phasor measurement units (PMUs), along with models for recreating their unique noise signatures. The proposed methods (both analytical and machine-learning-based) provide a substantial increase in a sensor’s model fidelity, a feature that can be leveraged by an end-user application to yield more accurate system representations. The proposed methods were then applied to micro PMU data from the EPFL microgrid campus to extract sensor noise profiles. This data was used to train a deep learning model, which was tested to emulate the noise characteristics present in actual signals. Based on the observed results and the employed data-driven methodology, the proposed methods may be adapted to replicate the behavior of other grid sensors and power new applications capable of detecting sensor degradation and eventual device failures in near real-time.

PMU, noise emulation, synthetic measurements, deep↗
DOE OSTI2021

Modulation and Modeling of Three-Dimensional Nanowire Assemblies Targeting Gas Sensors with High Response and Reliability

Despite improved sensitivity, simple downsizing of gas-sensing components to randomly arranged nanostructures often faces challenges associated with unpredictable electrical conduction pathways. In the present study, controlled fabrication of three-dimensional (3D) metal oxide nanowire networks is demonstrated that can greatly improve both signal stability and sensor response compared to random nanowire arrays. For example, the highest ever reported H 2 S gas response value, and a 5 times lower relative standard deviation of baseline resistance than that of random nanowires assemblies, are achieved with the ordered 3D nanowire network. Systematic engineering of 3D geometries and their modeling, utilizing equivalent circuit components, provide additional insights into the electrical conduction and gas-sensing response of 3D assemblies, revealing the critical importance of wire-to-wire junction points and their arrangement. Here these findings suggest new design rules for both enhanced performance and reliability of chemical sensors, which may also be extended to other devices based on nanoscale building blocks.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Precision pointing compensation for DSN antennas with optical distance measuring sensors

The pointing control loops of Deep Space Network (DSN) antennas do not account for unmodeled deflections of the primary and secondary reflectors. As a result, structural distortions due to unpredictable environmental loads can result in uncompensated boresight shifts which degrade pointing accuracy. The design proposed here can provide real-time bias commands to the pointing control system to compensate for environmental effects on pointing performance. The bias commands can be computed in real time from optically measured deflections at a number of points on the primary and secondary reflectors. Computer simulations with a reduced-order finite-element model of a DSN antenna validate the concept and lead to a proposed design by which a ten-to-one reduction in pointing uncertainty can be achieved under nominal uncertainty conditions.

Scheid, R. E.↗
DOE OSTI2024

Mid-IR UAV-based sensing platform with deep learning to Identify and Quantify Gaseous Emission in Gas Flares

This report details the development and evaluation of a Mid-Infrared (Mid-IR) Unmanned Aerial Vehicle (UAV)-based sensing platform integrated with deep learning algorithms for the identification and quantification of gaseous emissions in gas flares. The project, spearheaded by Omega Optics, Inc., aimed to address environmental monitoring challenges by leveraging advanced photonic technologies and autonomous UAV operations. The research focused on designing, optimizing, and fabricating photonic crystal waveguides and grating couplers to enhance the sensitivity and accuracy of gas detection. A comprehensive drone-based system was developed, featuring a miniaturized sensor, GPS module, and microcontroller communication network for real-time gas concentration monitoring. The system's adaptive sampling algorithm, implemented using the Robot Operating System (ROS), enables autonomous detection and localization of gas emission sources. Preliminary results demonstrate the platform's capability to detect and monitor gas emissions with high precision, cost-effectiveness, and scalability. Future work will expand upon this foundation by introducing 3D wind model-based learning for dynamic environmental conditions and further enhancing the user interface and data processing algorithms to support broader environmental monitoring applications. Overall, this project represents a significant step forward in UAV-based environmental sensing technologies, offering robust solutions for detecting and mitigating the impacts of gaseous emissions on public health and safety.

47 OTHER INSTRUMENTATION↗
NASA NTRS2001

Offering an Array of Improvements

Sensors Unlimited, Inc., with SBIR funding from NASA's Langley Research Center, Goddard Space Flight Center, Marshall Space Flight Center, and the Jet Propulsion Laboratory, developed a monolithic focal plane array for near-infrared imaging. The company developed one- (1- D) and two-dimensional (2-D) imaging arrays consisting of a highly reliable InGaAs p-I-n diode as a photodetector for monitoring a variety of applications, including single element device applications in receivers. The InGaAs 1-D and 2-D arrays have many applications. For example, they monitor the performance of dense wavelength division multiplexing (DWDM) systems- the process of packaging many channels into a single fiber-optic cable. Sensors Unlimited commercially offers its LXTM and LYTM Series InGaAs linear arrays for reliable DWDM performance monitoring. The LX and LY arrays enable instrument module designs with no moving parts, which provides for superior uniformity, and fast, linear outputs that remain stable over a wide temperature range. Innovative technologies derived from the monolithic focal plane array have enabled telecommunication companies to optimize existing bandwidth in their fiber-optic networks in order to support a high volume of network traffic. At the same time, the technologies obtained from the array have the potential for reducing costs, while increasing performance from Sensors Unlimited's current product lines.

Source record↗
NASA NTRS2011

The Habitat Demonstration Unit Project: A Modular Instrumentation System for a Deep Space Habitat

NASA is focused on developing human exploration capabilities in low Earth orbit (LEO), expanding to near Earth asteroids (NEA), and finally to Mars. Habitation is a crucial aspect of human exploration, and a current focus of NASA activities. The Habitation Demonstration Unit (HDU) is a project focused on developing an autonomous habitation system that enables human exploration of space by providing engineers and scientists with a test bed to develop, integrate, test, and evaluate habitation systems. A critical feature of the HDU is the instrumentation system, which monitors key subsystems within the habitat. The following paper will discuss the HDU instrumentation system performance and lessons learned during the 2010 Desert Research and Technology Studies (D-RaTS). In addition, this paper will discuss the evolution of the instrumentation system to support the 2011 Deep Space Habitat configuration, the challenges, and the lessons learned of implementing this configuration. In 2010, the HDU was implemented as a pressurized excursion module (PEM) and was tested at NASA s D-RaTS in Arizona [1]. For this initial configuration, the instrumentation system design used features that were successful in previous habitat instrumentation projects, while also considering challenges, and implementing lessons learned [2]. The main feature of the PEM instrumentation system was the use of a standards-based wireless sensor node (WSN), implementing an IEEE 802.15.4 protocol. Many of the instruments were connected to several WSNs, which wirelessly transmitted data to the command and data handling system via a mesh network. The PEM instrumentation system monitored the HDU during field tests at D-RaTS, and the WSN data was later analyzed to understand the performance of this system. In addition, several lessons learned were gained from the field test experience, which fed into the instrumentation design of the next generation of the HDU.

Rojdev, Kristina↗
DOE OSTI2023

Bayesian sequential optimal experimental design for nonlinear models using policy gradient reinforcement learning

We present a mathematical framework and computational methods for optimally designing a finite sequence of experiments. This sequential optimal experimental design (sOED) problem is formulated as a finite-horizon partially observable Markov decision process (POMDP) under a Bayesian setting and with information-theoretic utilities. The formulation is general and may accommodate continuous random variables, non-Gaussian posteriors, and nonlinear forward models. The sOED design policy incorporates elements of feedback and lookahead simultaneously, and we show it to generalize the commonly-used batch and greedy design strategies. We solve for the sOED policy using the policy gradient (PG) method from reinforcement learning, and provide a derivation for the PG expression in the sOED context. Adopting an actor-critic approach, the policy and value functions are parameterized using deep neural networks and improved via PG estimates produced from simulated episodes of designs and observations. The new PG-sOED algorithm is first validated on a linear-Gaussian benchmark, and then compared against other design baselines on a sensor movement problem for contaminant source inversion in a convection-diffusion field. As a result, we provide explanation for the policy behaviors using knowledge of the underlying physical process.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Temperature Field Reconstruction of Surfaces Heated Through Radiative Heat Transfer Using Convolutional Neural Networks

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.

Aldeia Machado, Luiz Carlos↗
NASA NTRS1993

Materials flight experiment carrier capability and future flight experiments on Hitchhiker-M carrier program

The CMSS has designed, fabricated, and qualified a unique Materials FLight EXperiment (MFLEX) carrier. The MFLEX is a reusable materials experiment carrier designed to support a wide array of sensors that measure synergistic effects on candidate space materials in Low Earth Orbit (LEO). The MFLEX can be integrated on a variety of launch vehicles/carriers and multiple units can be networked to optimize the surface area of carriers such as the Hitchhiker-M currently being built by the Goddard Space Flight Center (GSFC).

Davis, D.↗