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At least 379 records · Page 21

Casing Annulus Monitoring of CO 2 Injection Using Wireless Autonomous Distributed Sensor Networks

Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.

47 OTHER INSTRUMENTATION↗

Fuel Cell Airframe Integration Study for Short-Range Aircraft: Aircraft Propulsion and Subsystems Integration Evaluation - Volume 1

The objective of this study is to define the functionality and evaluate the propulsion and power system benefits derived from a Solid Oxide Fuel Cell (SOFC) based Auxiliary Power Unit (APU) for a future short range commercial aircraft, and to define the technology gaps to enable such a system. United Technologies Corporation (UTC) Integrated Total Aircraft Power System (ITAPS) methodologies were used to evaluate a baseline aircraft and several SOFC architectures. The technology benefits were captured as reductions of the mission fuel burn, life cycle cost, noise and emissions. As a result of the study, it was recognized that system integration is critical to maximize benefits from the SOFC APU for aircraft application. The mission fuel burn savings for the two SOFC architectures ranged from 4.7 percent for a system with high integration to 6.7 percent for a highly integrated system with certain technological risks. The SOFC APU itself produced zero emissions. The reduction in engine fuel burn achieved with the SOFC systems also resulted in reduced emissions from the engines for both ground operations and in flight. The noise level of the baseline APU with a silencer is 78 dBA, while the SOFC APU produced a lower noise level. It is concluded that a high specific power SOFC system is needed to achieve the benefits identified in this study. Additional areas requiring further development are the processing of the fuel to remove sulfur, either on board or on the ground, and extending the heat sink capability of the fuel to allow greater waste heat recovery, resolve the transient electrical system integration issues, and identification of the impact of the location of the SOFC and its size on the aircraft.

Gummalla, Mallika↗

Incorporation of SemiSpan SuperSonic Transport (S4T) Aeroservoelastic Models into SAREC-ASV Simulation

The Simulink-based Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV) was modified to incorporate linear models representing aeroservoelastic characteristics of the SemiSpan SuperSonic Transport (S4T) wind-tunnel model. The S4T planform is for a Technology Concept Aircraft (TCA) design from the 1990s. The model has three control surfaces and is instrumented with accelerometers and strain gauges. Control laws developed for wind-tunnel testing for Ride Quality Enhancement, Gust Load Alleviation, and Flutter Suppression System functions were implemented in the simulation. The simulation models open- and closed-loop response to turbulence and to control excitation. It provides time histories for closed-loop stable conditions above the open-loop flutter boundary. The simulation is useful for assessing the potential impact of closed-loop control rate and position saturation. It also provides a means to assess fidelity of system identification procedures by providing time histories for a known plant model, with and without unmeasured turbulence as a disturbance. Sets of linear models representing different Mach number and dynamic pressure conditions were implemented as MATLAB Linear Time Invariant (LTI) objects. Configuration changes were implemented by selecting which LTI object to use in a Simulink template block. A limited comparison of simulation versus wind-tunnel results is shown.

Christhilf, David M.↗

Towards Persistent Space Observations through Autonomous Multi-Agent Formations

Sensing platforms must advance in scale and sophistication in order to support increasingly ambitious missions across Earth and space science; intelligence, surveillance, and reconnaissance (ISR); and planetary exploration. Distributed, persistent observation platforms have the potential to play a pivotal role in next generation missions through improved area coverage, enhanced situational awareness, and faster identification of trends and changes. The Multi-Agent Clusters for Persistent Observations from Space (MACPOS) project at NASA Langley Research Center is developing key technologies for the autonomous, heterogeneous formations that will comprise such platforms. Research thrusts include dynamic formation negotiation for self-assembling clusters of agents, distributed motion planning, and coordinated trajectory execution. Adaptive leader-follower formation negotiation allows agents to cluster and break off as necessary to adapt to both nominal and new mission objectives. Coordinated motion planning and execution maintain the formation while ensuring safe separation distances among agents and obstacles in the environment. These capabilities align MACPOS with NASA’s initiative for space and surface in-situ assembly through fundamental technology development for autonomous multi-agent systems. This paper presents an overview and early progress for the MACPOS project. We describe the system architecture for both individual agents and the overall fleet. Design considerations are given for the planning, control, and metrology subsystems. Finally, we discuss planned project milestones and the expected course of development.

Matthew P Vaughan↗

Genetic ablation of root cap cells in Arabidopsis

The root cap is increasingly appreciated as a complex and dynamic plant organ. Root caps sense and transmit environmental signals, synthesize and secrete small molecules and macromolecules, and in some species shed metabolically active cells. However, it is not known whether root caps are essential for normal shoot and root development. We report the identification of a root cap-specific promoter and describe its use to genetically ablate root caps by directing root cap-specific expression of a diphtheria toxin A-chain gene. Transgenic toxin-expressing plants are viable and have normal aerial parts but agravitropic roots, implying loss of root cap function. Several cell layers are missing from the transgenic root caps, and the remaining cells are abnormal. Although the radial organization of the roots is normal in toxin-expressing plants, the root tips have fewer cytoplasmically dense cells than do wild-type root tips, suggesting that root meristematic activity is lower in transgenic than in wild-type plants. The roots of transgenic plants have more lateral roots and these are, in turn, more highly branched than those of wild-type plants. Thus, root cap ablation alters root architecture both by inhibiting root meristematic activity and by stimulating lateral root initiation. These observations imply that the root caps contain essential components of the signaling system that determines root architecture.

Non-NASA Center↗

NASA Space Exploration Logistics Workshop Proceedings

As NASA has embarked on a new Vision for Space Exploration, there is new energy and focus around the area of manned space exploration. These activities encompass the design of new vehicles such as the Crew Exploration Vehicle (CEV) and Crew Launch Vehicle (CLV) and the identification of commercial opportunities for space transportation services, as well as continued operations of the Space Shuttle and the International Space Station. Reaching the Moon and eventually Mars with a mix of both robotic and human explorers for short term missions is a formidable challenge in itself. How to achieve this in a safe, efficient and long-term sustainable way is yet another question. The challenge is not only one of vehicle design, launch, and operations but also one of space logistics. Oftentimes, logistical issues are not given enough consideration upfront, in relation to the large share of operating budgets they consume. In this context, a group of 54 experts in space logistics met for a two-day workshop to discuss the following key questions: 1. What is the current state-of the art in space logistics, in terms of architectures, concepts, technologies as well as enabling processes? 2. What are the main challenges for space logistics for future human exploration of the Moon and Mars, at the intersection of engineering and space operations? 3. What lessons can be drawn from past successes and failures in human space flight logistics? 4. What lessons and connections do we see from terrestrial analogies as well as activities in other areas, such as U.S. military logistics? 5. What key advances are required to enable long-term success in the context of a future interplanetary supply chain? These proceedings summarize the outcomes of the workshop, reference particular presentations, panels and breakout sessions, and record specific observations that should help guide future efforts.

deWeek, Oliver↗

Plasma confinement state classification via FPP relevant microwave diagnostics

We present a parsimonious and robust machine learning approach for identifying plasma confinement states in fusion power plants (FPPs) where reliable identification of the low-confinement and high-confinement regimes is critical for safe and efficient operation. Unlike research-oriented devices, FPPs must operate with a severely constrained set of diagnostics. To address this challenge, we demonstrate that a minimalist model, using only electron cyclotron emission (ECE) signals, can achieve accurate and reliable state classification. ECE provides electron temperature profiles without the engineering or survivability issues of in-vessel probes, making it a primary candidate for FPP-relevant diagnostics. Our framework employs ECE as input, extracts features using radial basis functions, and applies a gradient boosting classifier, achieving a test accuracy of 96% (correct predictions). Robustness analysis and feature importance analyzes confirm the approach’s reliability. These results demonstrate that state-of-the-art performance is attainable from a restricted diagnostic set, paving the way for minimalist yet resilient plasma control architectures for FPPs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Surface structure studies in 2D and 3D Nb resonators using GI-XRD

Superconductor radio frequency (SRF) Nb-resonators are a key element in the development of new generations of particle accelerators as well as in the fabrication of 3D circuit QED architecture for quantum computing. Nevertheless, Niobium is extremally reactive to light elements such as C, N, O and H, and therefore to the impurities ordering under special conditions, e.g., cryogenic temperatures. Since these resonators are put through a series of metallurgical and chemical processes, the number of impurities in the solid increases in tens of ppm. Upon operational conditions ~1.6 K, Nb become vulnerable to H atoms ordering, which leads to the nucleation of secondary phases such as Nb-hydrides. Thereupon to the energy dissipation and eventually to the superconductivity breakdown known as Q-disease and potentially High-Field Q-slope. In this contribution, we present a detailed structural analysis by high-energy grazing-incidence X-ray diffraction of specimens extracted from 3D Nb resonators to shed light on the kinetic formation of the resulting secondary phases and their crystal phase identification upon cooling and heating cycles. To our knowledge, this is the first study carried out in resonators samples using a light source, shallow angles and temperatures near ~4 K. Consequently, this work opens new routes to understand the chemical and phase composition, crystal and electronic structure of the Nb surface at temperatures near the operating conditions as a strategy to improve the physical and functional properties of Nb superconducting resonators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Variable Vector Countermeasure Suit (V2Suit) for Space Habitation and Exploration

The "Variable Vector Countermeasure Suit (V2Suit) for Space Habitation and Exploration" is a visionary system concept that will revolutionize space missions by providing a platform for integrating sensors and actuators with daily astronaut intravehicular activities to improve human health and performance. The V2Suit uses control moment gyroscopes (CMGs) within a miniaturized module placed on body segments to provide a "viscous resistance" during movements and a countermeasure to the sensorimotor and musculoskeletal adaptation performance decrements that manifest themselves while living and working in microgravity and during gravitational transitions during long-duration spaceflight, including post-flight recovery and rehabilitation. Through an integrated design, system initialization, and control systems approach the V2Suit is capable of generating this "viscous resistance" along an arbitrarily specified direction of "down." When movements are made, for example, parallel to that "down" direction a resistance is applied, and when the movement is perpendicular to that direction no resistance is applied. The V2Suit proposes to be a countermeasure to this spaceflight-related adaptation and de-conditioning and the unique sensorimotor characteristics associated with living and working in 0-G, which are critical for future long-duration space missions.This NIAC Phase I project focused on detailing several aspects of the V2Suit concept, including human-system integration, system architecture, computer aided design (CAD) modeling, and closed-loop simulation and analysis. In addition, early-stage breadboard prototyping of several aspects of the V2Suit system modules enabled characterization of expected performance and identified areas for further research and development to enable operational implementation of the V2Suit. In particular, potential challenges with integration of commercial-off-the-shelf components were identified. The key enabler for operational use and adoption of the V2Suit is a low-profile body worn form factor that does not interfere with normal, everyday movements and interfaces adequately with the body as to provide the generated gyroscopic torque for the perceptions of movement with a "viscous resistance." These aspects were investigated through mockups using a life-size mannequin, and through body attachment mechanisms on the breadboard prototype. Through the evaluation and investigation of commercially-available components, as well as an identification of desirable form factors, CAD models of the V2Suit modules were developed. These models included all of the required elements and spin motors, flywheel masses, gimbal motors, slip rings, inertial measurement units, motor controllers, and the required mounting brackets/hardware and cabling. The configuration and orientation of the control moment gyroscopes (CMGs) was specified according to results from the modeling, simulation and analysis. Two revisions of the CAD model were investigated through closed-loop simulation of the CMGs, and their ability to generate a resultant reaction force during movement and null undesirable torques due to changes in the direction of the angular momentum vector as a result of the normal body movements.

space missions↗

Architects, Engineers, and Contractors - Key to Moving Towards a Zero Carbon Future: Preprint

Many building owners have set energy or carbon goals often citing targets of carbon neutrality in the next 10 to 30 years. Ultimately, these goals need to be translated into actions related to new and existing construction. Designers and contractors are key to designing solutions that meet the energy and carbon goals. As a voluntary program, the Design and Construction Allies (Allies program) was formed to identify barriers for the adoption of zero energy and zero carbon buildings (ZEZC). The goal was to understand why "all" buildings are not designed with ZEZC in mind. Currently the Allies program consists of 25 leading architecture, engineering, and construction firms that are seeking to take actionable steps to deliver buildings with the ZEZC goal. In the first year, the Allies have found numerous barriers and have implemented working groups to address key challenges that can be solved readily Allies. The paper will document program formulation and engagement strategies as well as the identified barriers and related recommendations for the design and construction community to shift towards ZEZC as a normal design and construction outcome. Two major topics rose to the top that the working groups were created to address: (1) providing guidance and knowledge to clients such that they will be active in creating ZEZC, and (2) bringing together knowledge around embodied carbon such that action can be taken to reduce this carbon emission area. Each working group has refined the barriers and created solutions that have been tested by Ally members. This rapid identification of barriers and subsequent creation of deployable solutions shows rapid change can happen.

design allies↗

A Learn-to-Fly Approach for Adaptively Tuning Flight Control Systems

A method is presented for adaptively tuning feedback control gains in a flight control system to achieve desired closed-loop performance. The method combines efficient aircraft parameter estimation, for identifying closed-loop dynamics models, with online nonlinear optimization, for sequentially perturbing and updating control gains to improve performance. Access to flight measurements and the control gains is required, but no prior information about the aircraft dynamics or the flight control architecture is needed. After the procedure, the optimized control gains (with uncertainties), the open-loop dynamics model, and the closed-loop dynamics model are available. The method is demonstrated for tuning a longitudinal stability augmentation system using a realistic nonlinear flight dynamics simulation of a subscale airplane. Convergence was attained using five maneuvers that spanned approximately one minute of flight test time. Although shown for a relatively simple case, the method is general and can be applied to other aircraft, axes of motion, performance metrics, and control system designs.

Adaptive tuning↗

Deep learning for morphological identification of extended radio galaxies using weak labels

Abstract The present work discusses the use of a weakly-supervised deep learning algorithm that reduces the cost of labelling pixel-level masks for complex radio galaxies with multiple components. The algorithm is trained on weak class-level labels of radio galaxies to get class activation maps (CAMs). The CAMs are further refined using an inter-pixel relations network (IRNet) to get instance segmentation masks over radio galaxies and the positions of their infrared hosts. We use data from the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, specifically the Evolutionary Map of the Universe (EMU) Pilot Survey, which covered a sky area of 270 square degrees with an RMS sensitivity of 25–35 $\mu$ Jy beam $^{-1}$ . We demonstrate that weakly-supervised deep learning algorithms can achieve high accuracy in predicting pixel-level information, including masks for the extended radio emission encapsulating all galaxy components and the positions of the infrared host galaxies. We evaluate the performance of our method using mean Average Precision (mAP) across multiple classes at a standard intersection over union (IoU) threshold of 0.5. We show that the model achieves a mAP $_{50}$ of 67.5% and 76.8% for radio masks and infrared host positions, respectively. The network architecture can be found at the following link: https://github.com/Nikhel1/Gal-CAM

Astronomy & Astrophysics↗

A Vision of Quantitative Imaging Technology for Validation of Advanced Flight Technologies

Flight-testing is traditionally an expensive but critical element in the development and ultimate validation and certification of technologies destined for future operational capabilities. Measurements obtained in relevant flight environments also provide unique opportunities to observe flow phenomenon that are often beyond the capabilities of ground testing facilities and computational tools to simulate or duplicate. However, the challenges of minimizing vehicle weight and internal complexity as well as instrumentation bandwidth limitations often restrict the ability to make high-density, in-situ measurements with discrete sensors. Remote imaging offers a potential opportunity to noninvasively obtain such flight data in a complementary fashion. The NASA Hypersonic Thermodynamic Infrared Measurements Project has demonstrated such a capability to obtain calibrated thermal imagery on a hypersonic vehicle in flight. Through the application of existing and accessible technologies, the acreage surface temperature of the Shuttle lower surface was measured during reentry. Future hypersonic cruise vehicles, launcher configurations and reentry vehicles will, however, challenge current remote imaging capability. As NASA embarks on the design and deployment of a new Space Launch System architecture for access beyond earth orbit (and the commercial sector focused on low earth orbit), an opportunity exists to implement an imagery system and its supporting infrastructure that provides sufficient flexibility to incorporate changing technology to address the future needs of the flight test community. A long term vision is offered that supports the application of advanced multi-waveband sensing technology to aid in the development of future aerospace systems and critical technologies to enable highly responsive vehicle operations across the aerospace continuum, spanning launch, reusable space access and global reach. Motivations for development of an Agency level imagery-based measurement capability to support cross cutting applications that span the Agency mission directorates as well as meeting potential needs of the commercial sector and national interests of the Intelligence, Surveillance and Reconnaissance community are explored. A recommendation is made for an assessment study to baseline current imaging technology including the identification of future mission requirements. Development of requirements fostered by the applications suggested in this paper would be used to identify technology gaps and direct roadmapping for implementation of an affordable and sustainable next generation sensor/platform system.

Horvath, Thomas J.↗

Dictionary Learning with Accumulator Neurons

The Locally Competitive Algorithm (LCA) uses local competition between non-spiking leaky integrator neurons to infer sparse representations, allowing for potentially real-time execution on massively parallel neuromorphic architectures such as Intel's Loihi processor. Here, we focus on the problem of inferring sparse representations from streaming video using dictionaries of spatiotemporal features optimized in an unsupervised manner for sparse reconstruction. Non-spiking LCA has previously been used to achieve unsupervised learning of spatiotemporal dictionaries composed of convolutional kernels from raw, unlabeled video. We demonstrate how unsupervised dictionary learning with spiking LCA (\hbox{S-LCA}) can be efficiently implemented using accumulator neurons, which combine a conventional leaky-integrate-and-fire (\hbox{LIF}) spike generator with an additional state variable that is used to minimize the difference between the integrated input and the spiking output. We demonstrate dictionary learning across a wide range of dynamical regimes, from graded to intermittent spiking, for inferring sparse representations of both static images drawn from the CIFAR database as well as video frames captured from a DVS camera. On a classification task that requires identification of the suite from a deck of cards being rapidly flipped through as viewed by a DVS camera, we find essentially no degradation in performance as the LCA model used to infer sparse spatiotemporal representations migrates from graded to spiking. We conclude that accumulator neurons are likely to provide a powerful enabling component of future neuromorphic hardware for implementing online unsupervised learning of spatiotemporal dictionaries optimized for sparse reconstruction of streaming video from event based DVS cameras.

artificial intelligence↗

Report series: finding of effect and mitigation documentation for the mercury solar photovoltaic array and battery energy storage system, area 23, nevada national security site, nye county, nevada

The U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) proposes to install solar photovoltaic (PV) power generation arrays and an associated battery energy storage system (BESS) for the town of Mercury at the Nevada National Security Site (NNSS) in Nye County, Nevada (Figure 1). The purposes of the development of this facility are to support long-term efforts to modernize Mercury and to provide energy-resilient infrastructure and address climate adaptation needs. Because it is within the boundary of the Mercury Historic District (MHD), it is subject to the terms of the Programmatic Agreement Between the National Nuclear Security Administration Nevada Field Office and the Nevada State Historic Preservation Officer Regarding Modernization and Operational Maintenance of the Nevada National Security Site, at Mercury in Nye County, Nevada (hereafter referred to as the Mercury PA). An identification and evaluation report prepared for this undertaking determined that a contributing element to the MHD, the Mercury airstrip (26NY15777), is within the APE (Haynes 2024). The Mercury airstrip was developed following the closure of Camp Desert Rock in 1957 and used until late 1963 or 1964 when the Camp Desert Rock Airport was renovated, and the Mercury Bypass road constructed. The town of Mercury and the immediate surrounding area have been determined eligible for listing in the National Register of Historic Places (NRHP) as the MHD (SHPO Resource No. D230) under Criteria A and C for its importance in supporting nuclear testing and scientific research from 1951 through 1992 (Reed 2019). Originally recorded in 2016, 26NY15777 was determined individually not eligible for listing in the NRHP because it lacked sufficient integrity to convey its significance (Palmer 2016). It was subsequently determined in 2018 to be a contributing element of the MHD in an architectural survey of the district (Palmer 2018) and identified in Appendix C of the Mercury PA as a Category I contributing element. However, as per Stipulation IV.B.2, because the airstrip had already been formally evaluated and determined not to be individually eligible for the NRHP in consultation with the SHPO, this categorization was an error. NNSA/NFO reported this to the SHPO in Haynes 2024 and the SHPO concurred on June 11, 2024 (Reed). Accordingly, the airstrip is a Category II Property for the purposes of complying with the Mercury PA. The Mercury airstrip is a historic property for the purposes of compliance with Section 106 of the National Historic Preservation Act (NHPA) and subject to the stipulations of the Mercury PA.

25 ENERGY STORAGE↗

Intelligent systems technology infrastructure for integrated systems

A system infrastructure must be properly designed and integrated from the conceptual development phase to accommodate evolutionary intelligent technologies. Several technology development activities were identified that may have application to rendezvous and capture systems. Optical correlators in conjunction with fuzzy logic control might be used for the identification, tracking, and capture of either cooperative or non-cooperative targets without the intensive computational requirements associated with vision processing. A hybrid digital/analog system was developed and tested with a robotic arm. An aircraft refueling application demonstration is planned within two years. Initially this demonstration will be ground based with a follow-on air based demonstration. System dependability measurement and modeling techniques are being developed for fault management applications. This involves usage of incremental solution/evaluation techniques and modularized systems to facilitate reuse and to take advantage of natural partitions in system models. Though not yet commercially available and currently subject to accuracy limitations, technology is being developed to perform optical matrix operations to enhance computational speed. Optical terrain recognition using camera image sequencing processed with optical correlators is being developed to determine position and velocity in support of lander guidance. The system is planned for testing in conjunction with Dryden Flight Research Facility. Advanced architecture technology is defining open architecture design constraints, test bed concepts (processors, multiple hardware/software and multi-dimensional user support, knowledge/tool sharing infrastructure), and software engineering interface issues.

Lum, Henry↗

Neural MUSE Analysis

Researchers at Oak Ridge National Laboratory (ORNL) created data as part of the MUSE (Multi-Agency Urban Search Experiment Detector and Algorithm Test Bed) project simulating illicit nuclear materials located in various buildings along a road. In the simulation, a truck containing a radiation detector drives down the road gathering listmode data (counting the and energy of incident gamma radiation). Building materials, source shielding, driving speed, truck direction, truck location on the road, source type, and source placement are all varied between runs of the data set. This data was created using deterministic neutron transport and Monte Carlo methods through a combination of SCALE, MAVRIC, MCNP, and GADRAS. As part of a follow-on NA-22 project, two Kaggle competitions were created to determine the best algorithms for finding and identifying gamma sources in this simulated urban environment. The winning algorithm was neural network-based and had a test accuracy of 76.4% accuracy for source identification. This work seeks to build upon this work and improve the results through the application of novel machine learning techniques. As a first step, the data was classified by a simple Convolutional Neural Network (CNN) To accomplish this, the data was first preprocessed into “waterfall plots.” These plots are composed of energy vs count plots that are stacked vertically to show progression in time. The horizontal axis indicating the particle energy incorporated user defined bin spacing with options for in linear-, logarithmic-, square root-, and user-spaced bins. The z or color dimension showed the number of counts corresponding the energy-time combination. This data was then used to generate more data, by generating a local estimate of the mean of the distribution for a bin and then randomly re-sampling that bin from a Poisson distribution. Once all of this data was generated, it was fed into a well-known CNN architecture, ResNet50. The output layer of this model was removed and replaced with layers corresponding to the shape desired isotope outputs. The provided training data was used to train the classifier and the remaining testing data was used to evaluate the model. Results are soon to be forthcoming.

61 RADIATION PROTECTION AND DOSIMETRY↗

Evolvable Mars Campaign Long Duration Habitation Strategies: Architectural Approaches to Enable Human Exploration Missions

The Evolvable Mars Campaign (EMC) is the current NASA Mars mission planning effort which seeks to establish sustainable, realistic strategies to enable crewed Mars missions in the mid-2030s timeframe. The primary outcome of the Evolvable Mars Campaign is not to produce "The Plan" for sending humans to Mars, but instead its intent is to inform the Human Exploration and Operations Mission Directorate near-term key decisions and investment priorities to prepare for those types of missions. The FY'15 EMC effort focused upon analysis of integrated mission architectures to identify technically appealing transportation strategies, logistics build-up strategies, and vehicle designs for reaching and exploring Mars moons and Mars surface. As part of the development of this campaign, long duration habitats are required which are capable of supporting crew with limited resupply and crew abort during the Mars transit, Mars moons, and Mars surface segments of EMC missions. In particular, the EMC design team sought to design a single, affordable habitation system whose manufactured units could be outfitted uniquely for each of these missions and reused for multiple crewed missions. This habitat system must provide all of the functionality to safely support 4 crew for long durations while meeting mass and volume constraints for each of the mission segments set by the chosen transportation architecture and propulsion technologies. This paper describes several proposed long-duration habitation strategies to enable the Evolvable Mars Campaign through improvements in mass, cost, and reusability, and presents results of analysis to compare the options and identify promising solutions. The concepts investigated include several monolithic concepts: monolithic clean sheet designs, and concepts which leverage the co-manifested payload capability of NASA's Space Launch System (SLS) to deliver habitable elements within the Universal Payload Adaptor between the SLS upper stage and the Orion/Service module on the top of the vehicle. Multiple modular habitat options for Mars surface and in-space missions are also considered with various functionality and volume splits between modules to find the best balance of reducing the single largest mass which must be delivered to a destination and reducing the number of separate elements which must be launched. Analysis results presented for each of these concepts in this paper include mass/volume/power sizing using parametric sizing tools, identification of unique operational constraints, and limited comments on the additional impacts of reusability/dormancy on system design. Finally, recommendations will be made for promising solutions which will be carried forward for consideration in the Evolvable Mars Campaign work.

Simon, Matthew A.↗