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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Grid-Connected Modular Soft-Switching Solid State Transformers (M-S4T)

The objective of this project is to develop and verify the concept of a flexible and modular soft-switching solid-state transformer (M-S4T) for direct grid-connected applications. The ability to directly connect power electronics converters to the medium voltage grid (4 kV – 13 kV), and to potentially replace the passive and bulky, but ubiquitous 60 hertz service transformer in the 25 kVA to 100 kVA range, with a more flexible and controllable device, has been regarded as the ‘holy grail’ in grid control. However, this has proven to be extremely difficult. This project has developed the solutions to several key challenges of the direct grid-connected power electronics and realized a 7.2 kV M-S4T prototype. First, a protection method to protect the M-S4T from the high voltages (110 kV for the 13 kV system) that occur on the grid due to transients and lightning strikes have been developed and experimentally verified. Second, the realization and the operation of the M-S4T based on high-voltage SiC devices (>3.3 kV) and a medium-frequency medium-voltage low-leakage transformer in a single-stage solid-state transformer with zero-voltage switching, low dv/dt, and low electromagnetic interference has been successfully demonstrated up to 7.5 kV peak. Third, an oil-cooling system and stable communication and distributed control system for converter module voltage sharing have been developed and experimentally verified. The developed M-S4T has realized a modular universal high-performance power conversion system. This conversion system is scalable to different voltage and power levels and adaptable to four-quadrant bidirectional operation. Moreover, the use of passive cooling techniques meets the equipment life requirements, and the lightning protection scheme fulfills the basic insulation level specifications for direct grid connection. Such power conversion system opens up near-term opportunities, including energy storage, solar PV, or electric vehicle charging with significant cost and footprint savings. In the longer term, the possibility of replacing the utility distribution transformer with an M-S4T will be transformative for future distribution grids with a compact footprint and full controllability to enable high renewable energy and storage penetration. In addition to the main project, this report expands on the Plus-Up projected including as part of the main award. This project developed and demonstrated the technology for autonomous collaborative inverters that can be connected in an ad hoc manner to the grid. The aim of the project was to: (1) evaluate the existing techniques for grid-connected inverters and find their limitations; (2) develop detailed requirements for grid-connected inverters in the modern grid with millions of active nodes; (3) design a unified control strategy that brings more autonomy and intelligence to grid-connected inverters, and addresses parts of the issues with the existing techniques. The proposed technique, called UniCon, enables inverters to 1) connect/disconnect to/from the grid in an ad hoc manner; (2) work based on local sensing. Slow communication could be used for a more optimized behavior; (3) work automatically in both grid-forming/grid-following mode; (4) handle large disturbances, e.g., big load step and fault, in an oscillation-free manner; (5) work collaboratively with other inverters in steady-state and during transients. UniCon can be implemented in the middle-level control; hence it is agnostic to the vendor and to the implementation of the inner voltage/current and protection loops. Furthermore, a new synchronization scheme, based on deep learning, was developed that can extract the grid voltage phase and amplitude in a stable manner. The method is cheap to implement can improve the dynamic performance of the grid-connected inverters during fast transients, e.g., fault. The proposed control scheme was validated by (1) MATLAB/Simulink; (2) hardware-in-the-loop results, and; (3) experimental results using three inverters that form a microgrid in a down-scaled feeder. Lastly, both the M-S4T and UniCon have achieved promising tangible paths to markets. In the case of the M-S4T, the underlying technology — the Soft Switching Solid State Transformer (S4T) developed at the Georgia Tech Center for Distributed Energy (GT-CDE) has been licensed by GridBlock from the Georgia Tech Research Corporation, and GridBlock has been working with manufacturing partner Jabil (one of the largest US-based contract manufacturers) and system integrator Power Secure (largest deployer of microgrids in the US with 4.7 GW under management), to meet the strong initial demand. Similarly, GridBlock has an exclusive license to the UniCon technology, developed under this award by GT-CDE. The UniCon provides an intermediate control layer that enables the implementation of the higher-level ‘transactive’ control commands for the system. The architecture of the system - slow communications with the cloud for system optimization and setpoints, and the use of locally measured quantities for real-time control, provide a very robust and secure way of implementing a real-time must-run grid that is also secure and stable. This is a brand-new functionality that is critical for the future grid and key to GridBlock’s business model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

User Needs and Advances in Space Wireless Sensing and Communications

Decades of space exploration and technology trends for future missions show the need for new approaches in space/planetary sensor networks, observatories, internetworking, and communications/data delivery to Earth. The User Needs to be discussed in this talk includes interviews with several scientists and reviews of mission concepts for the next generation of sensors, observatories, and planetary surface missions. These observatories, sensors are envisioned to operate in extreme environments, with advanced autonomy, whereby sometimes communication to Earth is intermittent and delayed. These sensor nodes require software defined networking capabilities in order to learn and adapt to the environment, collect science data, internetwork, and communicate. Also, some user cases require the level of intelligence to manage network functions (either as a host), mobility, security, and interface data to the physical radio/optical layer. For instance, on a planetary surface, autonomous sensor nodes would create their own ad-hoc network, with some nodes handling communication capabilities between the wireless sensor networks and orbiting relay satellites. A section of this talk will cover the advances in space communication and internetworking to support future space missions. NASA's Space Communications and Navigation (SCaN) program continues to evolve with the development of optical communication, a new vision of the integrated network architecture with more capabilities, and the adoption of CCSDS space internetworking protocols. Advances in wireless communications hardware and electronics have enabled software defined networking (DVB-S2, VCM, ACM, DTN, Ad hoc, etc.) protocols for improved wireless communication and network management. Developing technologies to fulfil these user needs for wireless communications and adoption of standardized communication/internetworking protocols will be a huge benefit to future planetary missions, space observatories, and manned missions to other planets.

Kegege, Obadiah↗
DOE OSTI2021

Towards robust autonomous impedance spectroscopy analysis: A calibrated hierarchical Bayesian approach for electrochemical impedance spectroscopy (EIS) inversion

Distribution-based analyses, such as the distribution of relaxation times (DRT) and the distribution of diffusion times (DDT), present model-free alternatives to equivalent circuit modeling for analysis of electrochemical impedance spectroscopy (EIS) data. However, reconstructing such distributions from noisy impedance data is an ill-posed problem that must be solved with specialized inversion algorithms, requiring careful control and tuning. Furthermore, most inversion algorithms developed to date can only solve problems of limited complexity. Herein, we present a new hierarchical Bayesian method for EIS inversion, leveraging efficient algorithms for optimization and Hamiltonian Monte Carlo (HMC) sampling to solve models of arbitrary complexity. We overcome the challenge of ad-hoc parameter tuning by encoding intrinsic characteristics of the DRT and DDT into flexible prior distributions and “pre-calibrating” the model to simulated data. This approach is versatile, highly robust to noise, and provides quantitative estimates of both the error structure of the data and the uncertainty in the recovered distributions. The model is validated with simulated data to demonstrate accurate recovery of the DRT and the DDT. The method also shows promise for simultaneous recovery of multiple distributions, raising the intriguing possibility of semi-autonomous EIS analysis and ad-hoc model construction. Finally, the practical utility of the method is illustrated with experimental data. Throughout, we draw comparisons to several recently published EIS inversion methodologies.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Ecology Based Decentralized Agent Management System

The problem of maintaining a desired number of mobile agents on a network is not trivial, especially if we want a completely decentralized solution. Decentralized control makes a system more r e bust and less susceptible to partial failures. The problem is exacerbated on wireless ad hoc networks where host mobility can result in significant changes in the network size and topology. In this paper we propose an ecology-inspired approach to the management of the number of agents. The approach associates agents with living organisms and tasks with food. Agents procreate or die based on the abundance of uncompleted tasks (food). We performed a series of experiments investigating properties of such systems and analyzed their stability under various conditions. We concluded that the ecology based metaphor can be successfully applied to the management of agent populations on wireless ad hoc networks.

Peysakhov, Maxim D.↗
NASA NTRS2006

Software Architecture of Sensor Data Distribution In Planetary Exploration

Data from mobile and stationary sensors will be vital in planetary surface exploration. The distribution and collection of sensor data in an ad-hoc wireless network presents a challenge. Irregular terrain, mobile nodes, new associations with access points and repeaters with stronger signals as the network reconfigures to adapt to new conditions, signal fade and hardware failures can cause: a) Data errors; b) Out of sequence packets; c) Duplicate packets; and d) Drop out periods (when node is not connected). To mitigate the effects of these impairments, a robust and reliable software architecture must be implemented. This architecture must also be tolerant of communications outages. This paper describes such a robust and reliable software infrastructure that meets the challenges of a distributed ad hoc network in a difficult environment and presents the results of actual field experiments testing the principles and actual code developed.

Lee, Charles↗
DOE OSTI2024

Learning continuous scattering length density profiles from neutron reflectivities using convolutional neural networks

Interpreting neutron reflectivity (NR) data using ad hoc multi-layer models and physics-based models provides information about spatially resolved neutron scattering length density (NSLD) profiles. Recent improvements in data acquisition systems have allowed acquiring thousands of NR curves in a couple of hours, which has led to a need for automated data analysis tools to interpret NR measurements in real-time. Here, we present a machine learning analysis workflow that uses a series of models, based on a convolutional neural network (CNN), to learn the relation between the NSLDs and the NRs, and subsequently produce continuous NSLD profiles directly from NRs. The usefulness of our CNN-based models is demonstrated by constructing NSLDs from NRs of several films containing homopolymer polyzwitterions and diblock copolymers mixed with different types of salts. Comparisons of the NSLDs with those constructed using ad hoc multi-layer models reveal a very good agreement, suggesting the potential of CNN-based models for real-time automated data analysis of NRs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Automated and efficient local adaptive regression for principal component-based reduced-order modeling of turbulent reacting flows

Principal Component Analysis can be used to reduce the cost of Computational Fluid Dynamics simulations of turbulent reacting flows by reducing the dimensionality of the transported variables through projection of the thermochemical state onto a lower-dimensional manifold. However, because of the nonlinearity of the principal component source terms, nonlinear regression techniques must be utilized for the source terms in terms of the principal components. Unfortunately, widely available and utilized nonlinear regression techniques can have prohibitive computational requirements and/or accuracy that is highly dependent on user experience in ad hoc tuning of model architecture and hyperparameters. Here, in this work, a new nonlinear regression approach is proposed that is both computationally efficient and automated so does not require any user input. The approach is evaluated through a priori prediction of principal component source terms using data from a Direct Numerical Simulation of a turbulent nonpremixed n-heptane/air jet flame. In particular, the proposed framework consists of local regressions whose complexity is adapted according to the local nonlinearity of the data: local linear regression when accurate enough and local Artificial Neural Networks when nonlinear regression is required. The number of local clusters for local regression is determined automatically using the Davies-Bouldin index. In addition, Bayesian optimization is utilized for model training (i.e., to select the best architectures and hyperparameters of the nonlinear regressions in an unsupervised fashion), eliminating ad hoc hand-tuning and/or expensive grid searches. Overall, compared to a single, global neural network, the new local adaptive regression approach is shown to have comparable accuracy but 69% less training time due to the utilization of local linear regression and faster training of local neural networks.

42 ENGINEERING↗
NASA NTRSDate not supplied

Autonomous Lunar PNT Simulator (ALPS)

In this paper we present a simulation tool that has been used to develop an architecture for a low-cost Position, Navigation and Time (PNT) system to provide PNT services on and around the Moon using non-dedicated low-cost orbital and ground assets. The simulation tool has been developed to be flexible and is capable of modeling and analyzing the many different capabilities and configurations that the non-dedicated assets could support. The tool models the creation of an ad hoc swarm, the localization of this swarm and the subsequent provision of PNT services from this swarm. We present results from several studies of select configurations chosen to reflect existing and future real-world needs and capabilities. Over the next few decades there is expected to be a substantial increase in Lunar missions supporting and inspired by NASA’s Artemis Program. It is expected that a large fraction of these missions will be low cost, utilizing rideshares and CubeSats, just as has seen in Earth orbit over the past decade. Many of these missions will need navigation capabilities but may be unable to support the large power, mass and weight that a weak GNSS or DSN based navigation solution would entail. As Lunar PNT service demand is not likely to be needed over the entire lunar surface 24/7, the creation of a dedicated Lunar GNSS constellation cannot be justified. Hence, our proposed architecture envisions utilizing existing Lunar science and exploration assets to create ad hoc and on demand Lunar PNT swarms capable of providing PNT services to low cost missions. The simulation reflects the two distinct parts of the architecture: the creation of a Lunar PNT swarm using non-dedicated existing assets, and the quantitative modeling of the quality of the PNT services that this swarm provides. To support the former, the simulation supports various swarm localization techniques, including centralized and distributed EKFs both of which support pluggable dynamics models. In modeling the PNT service performance the simulation adopts standard techniques from the GNSS community, including providing degree of precision (DOP) estimates for theoretical end users. Crucially, all asset capabilities, including clock accuracy, independent location self-knowledge and timing measurement precision can be set independently for each asset, reflecting the key concept of utilizing non-dedicated assets. The simulation is predominantly implemented in MATLAB, with GMAT being used for the propagation of orbital assets. The paper will present results from the simulation reflecting the tool’s flexibility and focusing on scenarios that match real-world proposed missions, including scenarios designed to provide PNT support to lunar surface missions similar to NASA Ames' forthcoming VIPER mission. The performance of centralized and decentralized swarm configuration and localization techniques will be compared. Finally, performance of the PNT service provided by an autonomous Lunar PNT swarm will be compared to existing radiometric and weak GNSS methods.

Kelley Elizabeth Hashemi↗
DOE OSTI2021

Evaluation of a Surface Spill Operation to Return Adult Steelhead Overshoots Downstream of McNary Dam

This study, funded by the U.S. Army Corps of Engineers (USACE), was conducted by the Pacific Northwest National Laboratory to evaluate the efficacy of operating one Top Spill Weir (TSW) at McNary Dam outside the normal TSW operation dates for juvenile salmon passage. Of interest is whether the TSW is an effective downstream passage route for adult steelhead overshoots. Overshoots are fish which, having passed upstream at McNary Dam, must pass downstream to return to their natal stream to spawn. This report covers Fall (2019) and Spring (2020) study periods. The study design arranged the available 24 hours of TSW spill per week into weekly blocks with sub-blocks differentiated into day and night operations with TSW discharge periods of 4- and 8-hours duration. Hydroacoustic techniques were used to sample adult fish passage at the TSW and at turbine units 1 and 10. The experimental design contrasted TSW spill periods of differing duration and at different times of the day. The small number of fish detected passing the TSW, and the smaller number of fish detected passing the turbine units, were best suited to an ad hoc, exploratory approach to evaluating the effect of TSW spill. It is worthwhile to note that the operations data obtained for the fall study period had a greater than expected number of gaps and apparent anomalies that we believe were a result of how the data were aggregated. These problems are not particularly problematic for the present study, because the available data still provide a good indication of whether the TSW was operating at each point in time. TSW flows in both fall and spring data sets were able to be cleaned up using the established relationship between forebay elevation and TSW discharge rate. Additional cleanup of operations data would be needed, however, if more quantitative evaluation of dam-wide flow and passage relationships were needed. This study contrasted TSW spill periods of differing duration and at different times of the day. The small number of fish detected passing the TSW, and the smaller number of fish detected passing the turbine units were best suited to an ad hoc, exploratory approach to evaluating the effect of TSW spill. Spring adult steelhead passage numbers estimated using hydroacoustics were notably lower than during the fall study period, and that was consistent with our analysis of PIT tagged fish likely to be in the vicinity during each study period. Detections of fish in BlueView sampling areas upstream of the TSW and powerhouse were not correlated with detections of fish passing hydroacoustic sampling areas, which suggests that fish approaching the face of the dam can move around the forebay before passing. Other fish detected in the forebay in large numbers, such as shad, were able to be filtered out of steelhead passage counts and did not appear to be influencing hydroacoustic passage rate estimates. A pulse of passage at the initial TSW opening was weakly evident, but trends across 4- and 8-hour operational periods did not show a distinct decline in passage over time as TSW operation continued. Our findings do not indicate a reason to choose one 8-hour period over two 4-hour periods, or vice versa. This suggests that the duration of spill periods can be chosen based on operational or other considerations. Passage rates were consistently higher during the daytime TSW discharge periods, relative to nighttime TSW discharge periods. The experimental design of the current study used start times near dawn for day periods and near dusk for night periods.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2022

A Dynamo Simulation Generating Saturn-Like Small Magnetic Dipole Tilts

Abstract Among planetary dynamos, the magnetic field of Saturn stands out in its exceptional level of axisymmetry. One of its peculiar features is that the magnetic dipole mode is tilted with respect to the planetary rotation axis by only ≈0.007° or less. Numerical dynamo simulations performed in this context have had great difficulty in producing such small dipole tilt angles without introducing ad hoc ingredients such as a latitudinally varying heat flux pattern in the outer layers or stably stratified layers (SSLs). Here we present a numerical dynamo simulation that generates a highly axisymmetric dynamo with a dipole tilt of about ≈0.0008° on average. The model consists of a deep dynamo layer and an overlying low-conductivity layer but without any SSLs. We highlight a novel mechanism where strong differential rotation generated in the atmospheric layer penetrates into the dynamo region, helping to maintain a very small magnetic dipole tilt. Plain Language Summary Saturn's dipole-dominant magnetic field exhibits a very peculiar feature: the dipole component of the planetary magnetic field is tilted by less than ≈0.007° with respect to the planetary spin axis. Numerical simulations performed in this context suggest that if a spatial heat-flux variation is imposed, along with a stably stratified region, on top of an active dynamo layer, then small dipole tilt values can be realized. Here we present a model where extremely small dipole tilt values can be achieved without these ad hoc ingredients. Our simulations demonstrate that dynamo theory allows extremely small dipole tilt values in a relatively simple model configuration.

Rakesh Kumar Yadav↗
DOE OSTI2023

Automated Symbolic Upscaling: 1. Model Generation for Extended Applicability Regimes

Abstract In porous media theory, upscaling techniques are fundamental to deriving rigorous Darcy‐scale models for flow and reactive transport in subsurface systems. Due to limitations in classical techniques, a number of ad hoc approaches have been proposed to address physical regimes in which reactive time scales are similar to, or faster than, diffusive time scales. In Part 1 of this two part series, we present a strategy for expanding the applicability of classical homogenization theory by generalizing the assumed closure form. We detail the implementation of this strategy on two reactive mass transport problems with moderately reactive physics. The strategy produces nontrivial homogenized models with emergent terms and effective parameters that couple reactive, diffusive, and advective transport. The differences in equation forms between the macroscopic and pore‐scale descriptions advise caution to further studies where the forms of macroscopic equations are assumed, as opposed to rigorously derived. Numerical validation is provided for each problem to show that the error estimates of homogenization theory are satisfied, and to justify the implemented strategy. In Part 2, the presented strategy is automated using symbolic computing to expedite its implementation.

Pietrzyk, Kyle↗
NASA NTRSDate not supplied

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗
NASA NTRS2010

Practical Loop-Shaping Design of Feedback Control Systems

An improved methodology for designing feedback control systems has been developed based on systematically shaping the loop gain of the system to meet performance requirements such as stability margins, disturbance attenuation, and transient response, while taking into account the actuation system limitations such as actuation rates and range. Loop-shaping for controls design is not new, but past techniques do not directly address how to systematically design the controller to maximize its performance. As a result, classical feedback control systems are designed predominantly using ad hoc control design approaches such as proportional integral derivative (PID), normally satisfied when a workable solution is achieved, without a good understanding of how to maximize the effectiveness of the control design in terms of competing performance requirements, in relation to the limitations of the plant design. The conception of this improved methodology was motivated by challenges in designing control systems of the types needed for supersonic propulsion. But the methodology is generally applicable to any classical control-system design where the transfer function of the plant is known or can be evaluated. In the case of a supersonic aerospace vehicle, a major challenge is to design the system to attenuate anticipated external and internal disturbances, using such actuators as fuel injectors and valves, bypass doors, and ramps, all of which are subject to limitations in actuator response, rates, and ranges. Also, for supersonic vehicles, with long slim type of structures, coupling between the engine and the structural dynamics can produce undesirable effects that could adversely affect vehicle stability and ride quality. In order to design distributed controls that can suppress these potential adverse effects, within the full capabilities of the actuation system, it is important to employ a systematic control design methodology such as this that can maximize the effectiveness of the control design in a methodical and quantifiable way. The emphasis is in generating simple but rather powerful design techniques that will allow even designers with a layman s knowledge in controls to develop effective feedback control designs. Unlike conventional ad hoc methodologies of feedback control design, in this approach actuator rates are incorporated into the design right from the start: The relation between actuator speeds and the desired control bandwidth of the system is established explicitly. The technique developed is demonstrated via design examples in a step-by-step tutorial way. Given the actuation system rates and range limits together with design specifications in terms of stability margins, disturbance rejection, and transient response, the procedure involves designing the feedback loop gain to meet the requirements and maximizing the control system effectiveness, without exceeding the actuation system limits and saturating the controller. Then knowing the plant transfer function, the procedure involves designing the controller so that the controller transfer function together with the plant transfer function equate to the designed loop gain. The technique also shows what the limitations of the controller design are and how to trade competing design requirements such as stability margins and disturbance rejection. Finally, the technique is contrasted against other more familiar control design techniques, like PID control, to show its advantages.

Kopasakis, George↗
NASA NTRS2008

Algorithm Optimally Orders Forward-Chaining Inference Rules

People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.

James, Mark↗
NASA NTRS2023

Ad-Hawk Aerial Connectivity Network: An Integrated and Empirical System Evaluation

Wildfires in the United States have been increasing significantly in both frequency and size in recent decades, requiring unprecedented resource and communication efficiency on the part of wildfire management organizations. However, while the methodology and technology to combat wildfires have improved, the connectivity infrastructure in rural regions of the country is either incompatible with newer technology or altogether non-existent. Due to this, many modern communication methods are rendered useless in areas where a connection is needed most, complicating the overall fire management procedure. To improve communication and logistics between responders on the front lines and headquarters, a team of NASA research associates has developed the schematic for a rapidly deployable mobile ad-hoc internet-enabled Wi-Fi network that can bring stable internet access to any desired area. This paper contains the testing and analysis of the Ad-Hawk project conceived in the summer of 2022 and developed in the summer of 2023.

Wildfire↗
DOE OSTI2022

Radiation Detection System Integration Using Multiple-Input Multiple-Output Radios

This study describes the application development of multiple-input multiple-output radios to provide persistent mobile ad hoc network (MANET) for the Department of Homeland Security. By using Man Portable Unit (MPU5) fifth generation radios (manufactured by Persistent Systems) with the Android Team Awareness Kit (ATAK), an Android smartphone geospatial infrastructure and military situational awareness application, the Remote Sensing Laboratory has developed a MANET connectivity to monitor deployed nuclear/radiological search operation assets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Interference Moral Hazard in Large Multihop Networks

Cooperation between network nodes is critical for supporting services in ad hoc networks. Cooperation, however, is an idealized assumption that may not always be present. This assumption can fail because of moral hazard, a scenario in part caused by misaligned incentives between the requesting node and supporting node. In this paper, we characterize a moral hazard that perversely incentivizes nodes to increase their routing payments by transmitting interference into the multi-hop network. We refer to this as the interference moral hazard (IMH) problem which is inherent to strategyproof mechanisms with low overpayments. We investigate IMH as a non-cooperative game played by network nodes on a random graph. For large networks, we show that IMH can be solved in the network design space. Finally, we provide sufficient conditions on the network distribution that guarantee an equilibrium path with interference-free play. This is achieved by 1) lower-bounding the number of nodes and 2) bounding the network density slightly above the 2-connectedness threshold and below a proposed upper-bound. Simulations suggest that density plays a fundamental role in IMH.

42 ENGINEERING↗