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At least 523 records · Page 29

Collaborative Fault Tolerant Control of Non-Signalized Intersections for Connected and Autonomous Vehicles

With the potential of increased penetration of connected and autonomous vehicles (CAVs), intersectional signal control faces new challenges in terms of its operation and implementation. One possibility is to fully make use of the communication capabilities of CAVs so that intersectional signal control can be realized by CAVs alone – this leads to non-signalized intersectional operation for traffic networks in urban areas. In this paper, the state-of-the-art on collaborative fault tolerant control schemes for complex systems will be briefly described. This is then followed by the formulation of operational fault tolerant control that realizes the collaborative fault tolerance functionality at CAVs operational level in response to possible individual vehicle faults, where detailed modelling using vehicle movement dynamics will be described together with the construction of fast fault diagnosis and a collaborative fault tolerant control algorithm. A simple example will be given as well to demonstrate the proposed algorithm together with the discussions on other issues such as randomness of the system, communication errors and full energy consideration. These leads to several future directions of the research for the traffic flow control of non-signalized intersections with 100% penetration of CAVs.

Wang, Hong↗

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗

Understanding the Charging Flexibility of Shared Automated Electric Vehicle Fleets

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL. In each of these four cities, SAEV simulations are performed using local projected electricity prices from the Regional Energy Deployment System (ReEDS) for a handful of supply side scenarios. A coordinated charging model is introduced that seeks to reduce fleet charging costs in response to time-varying electricity prices and increasing shares of personal trip demand served (between 1% and 25% of all metro trips served by the SAEV fleet). Simulation results are presented across various scenarios assuming fleetwide coordination to minimize charging energy costs while constrained by offering adequate mobility service to fleet customers. The results indicate that the SAEV charging load is highly flexible; energy costs were shown to reduce between 13% and 46% across a wide range of simulated scenarios. In addition, these savings were realized without detrimentally impacting the fleet’s ability to service trips.

autonomous vehicle↗

The research challenges in security and safeguards for nuclear fission batteries

This paper discusses the nuclear security and safeguards research challenges presented by the development and deployment of nuclear fission batteries. These are defined as easily transportable and deployable nuclear systems which are designed to operate either unattended or autonomously. We start by defining the current landscape of domestic and international safeguards and security and discuss how it can be affected by the introduction these new nuclear systems. We then specifically discuss the technology gaps and technologies to be developed to facilitate their practical deployment. We find that, as expected, we can leverage conclusions from existing security and safeguards studies for small modular rectors and develop bespoke target set analyses to inform security postures based on probabilistic risk assessment. We find also that specific fission battery security economic analysis tools are needed and security by design must be applied early. However, the most important finding is that these new systems will require a new comprehensive set of cyber tools covering transportation, installation, operation, maintenance security of the fission battery systems. Altogether, we find that the development of the necessary security and safeguards requirements at the design phase of such a technology will be of great benefit in the smooth deployment of this modern nuclear energy system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Urban Air Mobility (UAM) Market Study

The Booz Allen Team explored market size and potential barriers to Urban Air Mobility (UAM) by focusing on three potential markets – Airport Shuttle, Air Taxi, and Air Ambulance. We found that the Airport Shuttle and Air Taxi markets are viable, with a significant total available market value in the U.S. of $500 billion, for a fully unconstrained scenario. In this unconstrained best-case scenario, passengers would have the ability to access and fly a UAM at any time, from any location to any destination, without being hindered by constraints such as weather, infrastructure, or traffic volume. Significant legal and regulatory, weather, certification, public perception, and infrastructure constraints exist, which reduce the market potential for these applications to only about 0.5% of the total available market, or $2.5 billion, in the near term. However, we determined that these constraints can be addressed through ongoing intra-governmental partnerships, government and industry collaboration, strong industry commitment, and existing legal and regulatory enablers. We found that the Air Ambulance market is not a viable market if served by electric vertical takeoff and landing (eVTOL) vehicles due to technology constraints but may potentially be viable if a hybrid VTOL aircraft are utilized. The barriers and challenges we characterized in this study can be stratified according to their applicability or potential mitigation through technology as well as market maturity (Figure 1). In the near term, high cost of service will be a key economic challenge. We found potential for significant reduction in service cost through increased vehicle and component efficiency, and automation in a more mature market scenario. Weather conditions also pose a challenge to the UAM market, though there is potential for mitigation of some of these impacts through technology such as sensors enabling operations in low visibility. However, even in a mature market with advanced technology, disruptions are still likely to occur due to weather events such as thunderstorms and strong winds. High density operations will likely stress the current Air Traffic Management (ATM) system in the near term, but technology and new initiatives such as the Air Traffic Management -eXploration project (ATM-X) will enable safe and efficient integration of UAM into the National Airspace System (NAS). Current battery technology creates a barrier in the near term, especially for the Air Ambulance market, as battery weight and extensive recharging times would be needed for these operations. Advancements in battery technology, as well as use of hybrid VTOLs, could significantly reduce this barrier in the longer term. As UAM emerges as a viable mode of transportation in the near term, adverse energy and environmental impacts, particularly noise, may impact community acceptance and potentially persist as the market matures into larger-scale operations. For non-technology related challenges, we found that infrastructure constraints will create a significant barrier to UAM in the near term but could be addressed in the longer term through development and expansion of vertiports. Competition from existing modes of transportation such as ride-sharing (e.g., Lyft, Uber) and ground taxi’s pose a key barrier to UAM in the short term, which will likely evolve into competition from other emerging technologies such as autonomous cars and electric trains in the longer term. Weather events will influence other components of the operation such as passenger comfort (e.g., extreme temperatures, turbulence) and infrastructure (e.g., winter weather causing cracks and degradation in vertiports). There is also potential for these impacts to be heightened in the longer term from the increased frequency of adverse weather such as thunderstorms due to changing climatic conditions. We also found that the public has strong concerns about safety as a passenger in a piloted UAM, including “lasing” of pilots, unruly passengers, and sabotage. They would prefer that all passengers pass through a security screening process before boarding a vehicle. They would also prefer to use UAM for longer regional trips, such as flying from Washington, DC to Baltimore, MD or San Diego, CA to Los Angeles, CA. A longer term automated UAM vehicle market will face challenges due to public apprehension about automation and unmanned operations, and a preference to fly with passengers they know in an autonomous (unmanned) operational scenario.

Rohit Goyal↗

A modeling framework for designing and evaluating curbside traffic management policies at Dallas-Fort Worth International Airport

Emerging mobility technologies are changing the transportation system landscape. This is especially evident at airports, such as the Dallas-Fort Worth International Airport (DFW). Without careful analysis, these changes could lead to inefficient and costly airport operations. This paper presents a modeling framework that integrates travel mode encoding, demand projection, and microsimulation to enable airports to develop, simulate, and evaluate curbside traffic managements policies and measure their impact. Here, the framework is utilized to analyze several traffic scenarios and policies for DFW: a baseline scenario which represents DFW traffic pattern as observed in 2018 and projected to 2045, a transit network company (TNC) electrification policy, a TNC queuing policy, a policy that increased transit ridership, a bus-only policy which considers the use of only buses inside DFW, an autonomous vehicle (AV) policy which investigates the impact of autonomous vehicle (AV) adoption on airport operations, and an example COVID-19 scenario which models the impact of the COVID19 pandemic. The simulations’ results demonstrate that: increasing the DFW transit ridership postpones the need for airport curbside expansion the most; encouraging shared-mobility with the bus-only policy produces the most savings in curbside congestion delays; automation and electrification for all passenger vehicle trips to/from DFW generates the most saving in fuel consumption and emissions; and uncontrolled AV adoption incurs the highest increase in fuel consumption, delay, and emissions and could require immediate airport capacity extension. Without policy intervention or investment in additional infrastructure capacity, these results predict the current operations would face significant congestion on high demand days starting as early as 2028. While derived in close partnership with DFW, the methodology presented here can be generalized to any airport.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

5G Enabled Energy Innovation: Advanced Wireless Networks for Science (Workshop Report)

Rapidly expanding, new telecommunications infrastructure based on 5G technologies will disrupt and transform how we design, build, operate, and optimize scientific infrastructure and the experiments and services enabled by that infrastructure, from continental-scale sensor networks to centralized scientific user facilities, from intelligent Internet of Things devices to supercomputers. Concurrently, 5G will introduce, or exacerbate, challenges related to protecting infrastructure and associated scientific data as well as to fully leveraging opportunities related to expanded infrastructure scale and complexity. The U.S. Department of Energy (DOE) Office of Science operates scientific infrastructure, supporting some of the nation’s most advanced intellectual discoveries, spanning the country and including 30 world-class user facilities from supercomputers to accelerators. Along with field experiments and remote observatories, every aspect of DOE’s scientific enterprise will be affected by 5G, which amounts to a complete renovation of the underpinnings of the nation’s information infrastructure. In this report we explore the scientific opportunities and new research challenges associated with 5G, ranging from scalability to heterogeneity to cybersecurity. The rapid commercial deployment of 5G opens the opportunity to rethink and reinvent DOE’s scientific infrastructure and experimentation, from intelligent sensor networks at unprecedented scales to a digital continuum of cyberinfrastructure spanning low-power sensors, high-performance computing embedded within and at the edge of the network, and DOE’s large-scale user instrument and computing facilities. New programming paradigms, workflow and data frameworks, and AI-based system design, operation, and autonomous adaptation and optimization will be necessary in order to exploit these new opportunities. Field deployments and centralized scientific instruments can also be revolutionized, moving (without traditional performance penalties) from wired to wireless connectivity for data and control systems, improving flexibility, and opening new sensing modalities, including the use of the 5G electromagnetic spectrum itself as an environmental probe. For DOE science, in contrast to commercial 5G applications and settings, devices will be deployed in extreme environments such as cryogenically cooled instrument control systems and in remote settings with harsh conditions, requiring the design of new materials for RF communication and edge processing to operate in these regimes. Concurrently, 5G infrastructure comprises both hardware and sophisticated software systems - currently closed and proprietary. The cybersecurity challenges to 5G-empowered reinvention mirror the complexity and variety of new 5G features, from virtualization to private network slices to ubiquitous access. Research is also needed in order to accelerate the development of secure and open 5G software infrastructure, reducing reliance on hardware and software produced outside the United States and providing the transparency and rigorous evaluation and testing afforded through open software. Twelve broad research thrusts are laid out in four chapters, with a companion fifth chapter (and three additional research thrusts) underscoring the needs and opportunities for an aggressive testbed program co-designed by networking experts and scientists involved in the 15 research thrusts. The urgency of undertaking this research is fueled by a global, accelerating deployment of new telecommunications infrastructure that is designed for entertainment and commercial applications - barely scratching the surface of what 5G can do to extend U.S. leadership in scientific discovery.

42 ENGINEERING↗

Multi-Billion Shot, High-Fluence Exposure of Cr(4+): YAG Passive Q-Switch

NASA's Goddard Space Flight Center is developing the Geoscience Laser Altimeter System (GLAS) employing a diode pumped, Q-Switched, ND:YAG laser operating at 40 Hz repetition rate. To meet the five-year mission lifetime goal, a single transmitter would accumulate over 6.3 billion shots. Cr(4+):YAG is a promising candidate material for passively Q-switching the laser. Historically, the performance of saturable absorbers has degraded over long-duration usage. To measure the multi-billion shot performance of Cr(4+):YAG, a passively Q-switched GLAS-like oscillator was tested at an accelerated repetition rate of 500 Hz. The intracavity fluence was calculated to be approximately 2.5 J/cm(exp 2). The laser was monitored autonomously for 165 days. There was no evidence of change in the material optical properties during the 7.2 billion shot test.. All observed changes in laser operation could be attributed to pump laser diode aging. This is the first demonstration of multi-billion shot exposure testing of Cr(4+):YAG in this pulse energy regime

Stephen, Mark A.↗

Methods for Improving Long-Range Wireless Communication Between Extreme Terrain Vehicles

Axel is an extreme terrain, two-wheeled rover designed to traverse rocky surface and sub-surface landscapes in order to conduct remote science experiments in hard-to-reach locations. The rover's design meets many requirements for a mobile research platform capable of reaching water seeps on Martian cliff sides. Axel was developed by the Mobility and Robotic Systems section at the Caltech Jet Propulsion Laboratory. Unique design criteria associated with extreme terrain mobility led to a unique rover solution, consisting of a central module, which provides long-term energy storage and space for large-scale science payloads, and two detachable Axels that can detach and explore extreme terrain locations that are inaccessible to conventional rovers. The envisioned mission could involve a four-wheeled configuration of Axel called 'DuAxel' that is able to traverse the benign, flattened terrain of a landing site and approach the edge of the targeted crater or cave where it would deploy anchoring legs and detach one of the Axel rovers [1]. A tether provides a secure link between the Axel rover and the central module, acting as an anchor to allow Axel to descend along steep crater walls to collect data from the scientifically relevant sites along the water seeps or crater ledges. After completing its scientific mission Axel would hoist itself up to the central module and dock autonomously (using its on-board stereo cameras), allowing the once-again recombined DuAxel to travel to another location to repeat data collection.

wireless communication↗

The Utility of Satellites and Autonomous Remote Sensing Platforms for Monitoring Offshore Aquaculture Farms: A Case Study for Canopy Forming Kelps

The emerging sector of offshore kelp aquaculture represents an opportunity to produce biofuel feedstock to help meet growing energy demand. Giant kelp represents an attractive aquaculture crop due to its rapid growth and production, however precision farming over large scales is required to make this crop economically viable. These demands necessitate high frequency monitoring to ensure outplant success, maximum production, and optimum quality of harvested biomass, while the long distance from shore and large necessary scales of production makes in person monitoring impractical. Remote sensing offers a practical monitoring solution and nascent imaging technologies could be leveraged to provide daily products of the kelp canopy and subsurface structures over unprecedented spatial scales. Here, we evaluate the efficacy of remote sensing from satellites and aerial and underwater autonomous vehicles as potential monitoring platforms for offshore kelp aquaculture farms. Decadal-scale analyses of the Southern California Bight showed that high offshore summertime cloud cover restricts the ability of satellite sensors to provide high frequency direct monitoring of these farms. By contrast, daily monitoring of offshore farms using sensors mounted to aerial and underwater drones seems promising. Small Unoccupied Aircraft Systems (sUAS) carrying lightweight optical sensors can provide estimates of canopy area, density, and tissue nitrogen content on the time and space scales necessary for observing changes in this highly dynamic species. Underwater color imagery can be rapidly classified using deep learning models to identify kelp outplants on a longline farm and high acoustic returns of kelp pneumatocysts from side scan sonar imagery signal an ability to monitor the subsurface development of kelp fronds. Current sensing technologies can be used to develop additional machine learning and spectral algorithms to monitor outplant health and canopy macromolecular content, however future developments in vehicle and infrastructure technologies are necessary to reduce costs and transcend operational limitations for continuous deployment in an offshore setting.

54 ENVIRONMENTAL SCIENCES↗

Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Heterogeneous Catalyst Discovery

Artificial intelligence is reshaping scientific exploration, but most methods automate procedural tasks without engaging in scientific reasoning, limiting autonomy in discovery. We demonstrate that hierarchical agentic large language model reasoning can efficiently drive simulation and scientific exploration. Across two chemical applications, CO adsorption on Cu surface transition metal adatoms and on M–N–C catalysts, reasoning-guided exploration reduces required atomistic simulations by up to 90% relative to heuristic or random selection. Comparisons across single-agent, multi-agent, and stochastic baselines show that hierarchical strategies yield more coherent and information-efficient search trajectories. Reasoning traces reveal chemically grounded decisions that cannot be explained by semantic bias or stochastic sampling. We realize these agentic reasoning strategies in Materials Agents for Simulation and Theory in Electronic-structure Reasoning (MASTER), a multimodal system that translates natural language into density functional theory workflows. Altogether, multi-agent collaboration accelerates heterogeneous catalyst discovery and marks a step toward more autonomous, reasoning-guided scientific exploration.

30 DIRECT ENERGY CONVERSION↗

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗

Observations of optical counterparts of Gamma-Ray bursts

This is a final report for a contract begun in Dec. 1987 and ended in Mar. 1989 to use the existing Lincoln Laboratory Experimental Test Site in Socorro, NM to search for optical counterparts to gamma-ray bursts. The objective was to develop an autonomous staring system to search for stationary, transient optical flashes. The search was to use an existing 31-inch telescope equipped with a sensitive video detector. The approach for the search was to develop real-time processing software to monitor the video signal from the detector and to record any transient, point-like flashes that occurred in the field of view. The system would have been able to detect fainter flashes (B is approximately 15(sup m) in 1/30 s, delta(m(sub v)) = 0.25(sup m)) than other systems but lacked a large field of view (only 1.2 deg diameter) necessary to give a high probability of detecting a random flash on the sky. As such, the plan was to monitor known gamma-ray burst error boxes and wait for a repetition of an earlier event. The high payoff of good sensitivity with high angular resolution (1 pixel = 10sec) and good time resolution (30 s) to allow post-burst searches warranted funding if the cost was not prohibitive. The contract began in the middle of the three-year cycle for High Energy Astrophysics Gamma-Ray Astronomy Research and Analysis Program. This final report briefly describes the portion of the plan completed under the original contract.

Knight, Frederick K.↗

A Network for Standardized Ocean Color Validation Measurements

The Aerosol Robotic Network (AERONET) was developed to support atmospheric studies at various scales with measurements from worldwide distributed autonomous sunphotometers [Holben et al. 1998]. AERONET has now extended its support to marine applications through the additional capability of measuring the radiance emerging from the sea with modified sun-photometers installed on offshore platforms like lighthouses, navigation aids, oceanographic and oil towers. The functionality of this added network component called AERONET - Ocean Color (AERONET-OC), has been verified at different sites and deployment structures over a four year testing phase. Continuous or occasional deployment platforms (see Fig. 1) included: the Acqua Alta Oceanographic Tower (AAOT) of the Italian National Research Council in the northern Adriatic Sea since spring 2002; the Martha s Vineyard Coastal Observatory (MVCO) tower of the Woods Hole Oceanographic Institution in the Atlantic off the Massachusetts coast for different periods since spring 2004; the TOTAL Abu-Al-Bukhoosh oil Platform (AABP, shown through an artistic rendition in Fig. 1) in the Persian (Arabian) Gulf in fall 2004; the Gustaf Dal n Lighthouse Tower (GDLT) of the Swedish Maritime Administration in the Baltic Sea in summer 2005; and the platform at the Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE) site located in the Atlantic Ocean off the Virginia coast since fall 2005. Data collected during the network testing phase, confirm the capability of AERONET-OC to support the validation of marine optical remote sensing products through standardized measurements of normalized water-leaving radiance, LWN, and aerosol optical thickness, a, at multiple coastal sites.

Zibordi, Giuseppe↗

EMI Mitigation of a Ćuk-Based Power-Electronic System Using Switching-Sequence-Based Control

Switching-sequence-based control (SBC) laws when designed based on topological switching behavior can have positive effects on slow- and fast-scale dynamics of a power-electronic system (PES). The slow-scale control can encompass fast PES state regulation and tracking, based on predefined objective, while fastscale control can address differential-mode (DM) and commonmode (CM) spectral-peak energy associated with PES switching operation. Such control laws may offer enhanced programmability to conventional PES design where bulky electromagnetic interference (EMI) filters have been traditionally used to reduce EMI of switching power converters to meet EMI regulatory standards. An EMI filter is always a less programmable solution since it is usually designed for the worst-case EMI mitigation and usually overkill for a PES operating under reduced load condition. The control scheme outlined in this article offers EMI mitigation across wide operating regions without compromising PES regulation. Moreover, it does so by use of switching sequences that guarantee the reachability of the PES dynamics using an advanced Lyapunov-function-based approach. SBC is a powerful tool to generate control actions for a PES based on multivariate PES state constraints. Hence, contemporary EMI regulatory standards are used as constraints in the SBC formulation to operate the PES under wide operating regime while autonomously mitigating the EMI levels. The work may be of paramount importance for operating the ultra-fast-transition recent wide-bandgap semiconductor devices like GaN–FET and SiC MOSFET under higher power with increasing switching frequencies, which is usually desirable for increased power density and reduced switching losses. Here, a hardware Cuk–PES operated ´ with GaN–FETs is fabricated and is used for case illustration. It is shown by experimental results how SBC mitigate DM and CM EMI noise of the PES while maintaining regulation even for the higher order nonminimum phase PES, while reducing sensor requirements using state observer derived from the switching model of the PES.

42 ENGINEERING↗

SPARROW: A Steam Propelled Autonomous Retrieval Robot for Ocean Worlds

This paper presents the results of a NIAC Phase I study into the use of a propulsively hopping robot for the exploration of Europa’s rugged, icy surface. Named the“Steam Propelled Retrieval Robot for Ocean Worlds,” SPARROW is a multi-thruster robot passively gimballed within a protective, spherical shell, which enables it to freely rotate, self-right, and tumble over chaotic terrains. SPARROW is envisioned as a soccerball-sized payload to a primary lander mission. Europa’s abundant surface ice would be harvested as an in situ propellant source. The principal objective of SPARROW would be to increase the science return of a Europa landed asset by enabling access to distal, spatially distributed geologic units. The design of mobility systems for Europa is challenging, due in part to its almost entirely unconstrained surface topography and strength. Images returned by Voyager and Galileo yielded resolutions on the order of hundreds of meters per pixel, with localized regions reaching 6 meters per pixel—still far larger than a typical rover. A key benefit of SPARROW’s hopping, impact-tolerant design, is that it eliminates the need for a piori information on the terrain topography and surface strength; no surface reaction forces are required for motion. In this context, SPARROW is entirely terrain agnostic. In this paper we detail the results of three study objectives: i) to quantify the energy required to collect surface ice, change its phase, and maintain propellant temperature, ii) to identify control and estimation strategies that enable SPARROW to successfully reach, and return from, regions of scientific interest, and iii) to characterize the impact of SPARROW’s range on likely science return. Five water-based propellant architectures are presented alongside their mass, power, and volume requirements. Monte Carlo simulations of SPARROW hopping and tumbling over 1 km of glacial ice are summarized, characterizing SPARROW’s sensitivity to uncertainty in: initial conditions, thrust control, and cage-terrain interaction. Finally, a science traceability matrix is presented, which details the effect of sortie range on three science goals: constraining Europa’s evolutionary morphology, assessing sub-surface ocean habitability, and searching for life and/or biosignatures.

Phillips, Cynthia↗

A New Vehicle-to-Vehicle Communication System: Visual-Enhanced Cooperative Traffic Operations

The advent of Connected and Autonomous Vehicles (CAVs) has highlighted the necessity for robust communication systems between vehicles and their environment. This study introduces a novel vehicle-to-vehicle (V2V) communication system, termed the Visual-Enhanced Cooperative Traffic Operations (VECTOR) system. The VECTOR system addresses the need for robust communication by converting dynamic data (including velocity and yaw angle data) into binary code, which is displayed on an LED panel mounted on the top of the vehicle. Following vehicles detect this panel and decode the information using a camera, implementing a visual-based communication method. VECTOR system employs a comprehensive five-module process. Initially, polynomial fitting techniques are applied to velocity data over fixed time intervals using third-degree polynomials, with validation via R² and MSE metrics. The second module converts velocity and yaw angle data into binary form, thereby enhancing detection and processing efficiency. The third module focuses on improving detection stability across various environmental conditions to enhance traffic safety. The fourth module decodes the binary data back into trajectory information, ensuring the fidelity of velocity and yaw angles. The final module integrates eco-control through the VECTOR system, employing advanced control algorithms to minimize energy consumption in CAVs. Experimental evaluations conducted using a modified CAV test platform based on the Lincoln MKZ demonstrate the feasibility and efficiency of the VECTOR system, achieving a 75% R-squared accuracy rate in replicating original velocity data. This methodology not only highlights potential applications but also underscores significant implications for advancing CAV technology.

Ma, Ke↗

Autonomous Inspection of Geologic Repositories: Current State of the Art and Future Directions

Geological repositories for nuclear waste, including spent nuclear fuel, present a significant challenge for traditional International Atomic Energy Agency (IAEA) safeguards tools due to their inaccessibility and demanding operational conditions. The IAEA has been working closely with Member State organizations currently involved in repository construction and planning, including Euratom, the Finnish and Swedish regulatory authorities, and relevant facility operators. However, the verification challenge remains unsolved, and there persists an out- standing need for tools and approaches that will help the IAEA verify that no nuclear material is diverted from a repository environment. The challenge is also not static. Activities must encompass verification of the design, prior to and during the construction/operation phase, and post backfill. Throughout these various phases, it is imperative that the IAEA maintains a continuity of knowledge (CoK) of all material including information on material inventory and flow. This paper highlights these challenges and outlines how they might be addressed by using remote or autonomous vehicles. Specifically, we discuss the current state of the art in robotic autonomy for known or partially known environment mapping and patrolling, as well as shared autonomy, where humans collaborate with closed loop autonomation to complete tasks. We explore the feasibility of using rovers for these verification tasks, along with the challenges associated with system implementation. Hardware and software suggestions are provided based on the adoption of similar technologies in other comparable areas and ability to close technical gaps. Lastly, human-robotic interactions are considered based on the challenges of the environment of the repository and effective deployment and continued operation of the robot system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗