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At least 37 records · Page 2

Cost of convenience in long-dwell public electric vehicle charging

This paper presents a comprehensive methodology for quantifying trade offs between the cost of charging at public Level-2 charging stations and the inconvenience of using those stations. The paper also includes a methodology for generating synthetic travel itineraries of tens of thousands of drivers and for sizing and placing charging infrastructure to support those itineraries. Inconvenience is quantified by a weighted sum of the time a driver spends traveling between their intended destination and the charging station; weights are derived from the activity interrupted by the driver’s need to move their car. We demonstrate a trade off between cost of charging and inconvenience by varying how far away from their destination drivers are willing to charge. Our results demonstrate the importance of access to stations and suggest that other methods for increasing access, such as increasing the spatial density of stations, could significantly impact charging cost and inconvenience. Moreover, average energy cost may be reduced by introducing managed charging, which also affects inconvenience. The framework presented here can be used to evaluate the overlapping effects of both access and charge management. Furthermore, the framework can be easily extended to include additional factors such as capital costs, enabling thorough evaluation and planning of regional Level-2 charging networks.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA

Discrete Abstractions of Hybrid Systems: Verification of Safety and Application to User-Interface Design

Human interaction with a complex control system involves the user, the automation’s discrete mode logic, and the underlying continuous dynamics of the physical system. The user-interface of such systems always displays a reduced set of information about the entire system. Designing interfaces such that all the pertinent information is available and assuring that this information is correct is important for any user-interface, but especially so for safety-critical systems such as automotive systems and autopilots. Here we describe a methodology for the analysis of hybrid control systems that incorporate user interaction, with the goal of assuring that the information provided to the user is correct. That is, the user-interface must contain all information necessary to safely complete a desired procedure or task. We begin with a hybrid system model which incorporates discrete mode logic as well as nonlinear continuous dynamics. Using a hybrid computational tool for reachability, we find the largest region of the state-space in which we can guarantee the state of the system can always remain – this is the safe region of operation. By implementing a controller for safety which arises from this computation, we mathematically guarantee that this safe region is invariant, meaning that the system will always remain within the safe region if the determined controller is used on the boundary of the safe region. Verification within a hybrid framework allows us to account for the continuous dynamics underlying the discrete representations displayed to the user. Using the computed invariant regions as discrete states, we can abstract a discrete event system from this hybrid system with safety restrictions. This abstraction can be used to determine what information must be provided on the display. Furthermore, in cases in which an interface already exists, the abstraction provides the necessary input into existing interface verification methods. We provide two examples: a car traveling through a yellow light at an intersection and an aircraft autopilot in an automatic landing/go-around maneuver. The examples demonstrate the applicability of this methodology to hybrid systems that have operational constraints we can pose in terms of safety. This methodology differs from existing work in hybrid system verification in that we directly account for the user’s interactions with the system.

Meeko Oishi

A Review on Cybersecurity Vulnerabilities for Urban Air Mobility

Recent developments of high-powered unmanned aerial vehicles (UAVs) have allowed for urban air mobility (UAM) to become a reality. While the propulsive technology of these flying cars has almost reached an economic level, the infrastructure to allow for these vehicles to operate in an urban environment is still lacking. With numerous known vulnerabilities in UAVs and commercial aircraft, manufacturers have not addressed cybersecurity in the scope of urban air mobility. This paper presents a review of several known cybersecurity vulnerabilities and previous attacks associated with the core communication systems of UAVs and aircraft. Analyzing current solutions to each threat and incorporating early concepts for UAM, this paper then presents a basic framework featuring a blockchain-based PKI with secondary navigation systems to allow for the development of secure airspace.

Urban Air Mobility

The Identification and Modeling of Visual Cue Usage in Manual Control Task Experiments

Many fields of endeavor require humans to conduct manual control tasks while viewing a perspective scene. Manual control refers to tasks in which continuous, or nearly continuous, control adjustments are required. Examples include flying an aircraft, driving a car, and riding a bicycle. Perspective scenes can arise through natural viewing of the world, simulation of a scene (as in flight simulators), or through imaging devices (such as the cameras on an unmanned aerospace vehicle). Designers frequently have some degree of control over the content and characteristics of a perspective scene; airport designers can choose runway markings, vehicle designers can influence the size and shape of windows, as well as the location of the pilot, and simulator database designers can choose scene complexity and content. Little theoretical framework exists to help designers determine the answers to questions related to perspective scene content. An empirical approach is most commonly used to determine optimum perspective scene configurations. The goal of the research effort described in this dissertation has been to provide a tool for modeling the characteristics of human operators conducting manual control tasks with perspective-scene viewing. This is done for the purpose of providing an algorithmic, as opposed to empirical, method for analyzing the effects of changing perspective scene content for closed-loop manual control tasks.

Sweet, Barbara Townsend

Spectral Irradiance Calibration in the Infrared: 3-35 microns Spectra of Three Southern Standard Stars - Part 6

We present three new absolutely calibrated continuous stellar spectra from 3 to 35 microns, constructed as far as possible from actual observed spectral fragments taken from the Kuiper Airborne Observatory (KAO), and the IRAS Low Resolution Spectrometer (LRS). These stars- alpha(sup 1) Cen, alpha TrA, and epsilon Car-augment our previous archive of complete absolutely calibrated spectra for northern K and M giants. All these spectra have a common calibration pedigree. The wavelength coverage is ideal for calibration of many existing and proposed ground-based, airborne, and satellite sensors. KAO and IRAS data in the 15-30 micron range suggest that the spectra of cool giants are close to Rayleigh-Jeans slopes. Our observations of alpha(sup 1) Cen, absolutely calibrated via our adopted Sirius model, indicate an angular diameter in very good agreement with values in the literature, demonstrating 'closure' of the set of spectra within our absolute framework. We compare our observed alpha(sup 1) Cen spectrum with a published grid of theoretical models from Kurucz, and adopt a plausible theoretical shape, that fits our spectrum, as a secondary reference spectrum in the southern sky.

Cohen, Martin

RectifHyd Version 2.0: Historical and counterfactual-climatological hydropower monthly generation totals for CONUS plants, 1980 – 2019

This dataset will contain the following files: - RectifHydV2.zip – the RectifHydV2 dataset, split into two files: o RectifHydV2_Actual_MWh.csv: Estimated actual monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 o RectifHydV2_Counterfactual_MWh.csv: Counterfactual (climate-only) monthly net generation from 590 Hydropower Plants (>10MW nameplate) in CONUS, 1980 – 2019 - RectifHydV2_code.zip: Full data processing pipeline, coded using R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/rectifhydv2 - RectifHydV2_inputs.zip: Complete set of input data used to create RectifHydV2, organized for direct entry into “/data/” directory of the RectifHydV2 reproducible data pipeline - RectifHydV2_misc.zip: - RectifHydV2_dailyRelease.csv

13 HYDRO ENERGY

Challenges in Vehicle Safety and Occupant Protection for Autonomous Electric Vertical Take-Off and Landing (eVTOL) Vehicles

The burgeoning electric Vertical Take-off and Landing (eVTOL) vehicle industry has generated a significant level of enthusiasm amongst aviation designers, manufacturers and researchers. This industry is determined to change the urban transportation paradigm from traditional ground-based vehicles (cars, taxis, buses) to air-based eVTOL vehicles which can be summoned, much like how conventional taxi services work currently. These new eVTOL vehicles are designed to be small and lightweight and operate autonomously without user intervention. There are many unknowns as to how the industry will mature. The logistics of creating a completely new category of vehicle along with its own set of rules are complex, and there are many known - and unknown - barriers to overcome. Some (of many) known barriers include airspace management, ground logistics, physical space, and, the vehicle design itself. There are many eVTOL vehicle manufacturers and organizations working these problems presently. This report will focus on one major barrier: the level of safety as it pertains to the framework of eVTOL vehicles. A high level of safety is necessary for the vehicles to gain acceptance as the public adapts to these autonomous ride-sharing services. An overview of current levels of transportation safety and some extrapolation into how eVTOL vehicles might compare is first presented. Next, a discussion categorizing the major differences between Crash Prevention and Crash Mitigation as it pertains to eVTOL vehicle safety is included with identification of current deficiencies. The report then expands into a framework for specific ideas that could use Crash Mitigation to improve vehicle safety through a crashworthy systems level approach with several designs highlighted. Finally, a brief discussion into the regulatory approach and potential guidelines as they pertain to new eVTOL vehicles is presented. Accordingly, much of the supplemental data will be taken from sources pertaining to either General Aviation (GA) aircraft, rotorcraft, or transport category aircraft, due to the lack of overarching data from eVTOL vehicles. As of this writing, the European Aviation Safety Agency has released a draft version of a VTOL Special Condition, with a comment period closing in late 2018. It is assumed that eventual expected operations and anticipated future regulations for VTOL vehicles will consist of some combination of these (and other) sources.

Littell, Justin D.

Autonomous Off-road Navigation over Extreme Terrains with Perceptually-challenging Conditions

We propose a framework for resilient autonomous navigation in perceptuallychallenging unknown environments with mobility-stressing elements such asuneven surfaces with rocks and boulders, steep slopes, negative obstacles like cliffsand holes, and narrow passages. Environments are GPS-denied and perceptuallydegradedwith variable lighting from dark to lit and obscurants (dust, fog, smoke).Lack of prior maps and degraded communication eliminates the possibility of prioror off-board computation or operator intervention. This necessitates real-time onboardcomputation using noisy sensor data. To address these challenges, we proposea resilient architecture that exploits redundancy and heterogeneity in sensing modalities.Further resilience is achieved by triggering recovery behaviors upon failure.We propose a fast settling algorithm to generate robust multi-fidelity traversabilityestimates in real-time. The proposed approach was deployed on multiple physicalsystems including skid-steer and tracked robots, high-speed RC car and legged robotsand as a part of Team CoSTAR’s effort to theDARPASubterranean Challenge, wherethe team won 2nd and 1st place in the Tunnel and Urban Circuit, respectively.

Agha-mohammadi, Ali-akbar

A Physics-Based Modeling Framework for Prognostic Studies

Prognostics and Health Management (PHM) methodologies have emerged as one of the key enablers for achieving efficient system level maintenance as part of a busy operations schedule, and lowering overall life cycle costs. PHM is also emerging as a high-priority issue in critical applications, where the focus is on conducting fundamental research in the field of integrated systems health management. The term diagnostics relates to the ability to detect and isolate faults or failures in a system. Prognostics on the other hand is the process of predicting health condition and remaining useful life based on current state, previous conditions and future operating conditions. PHM methods combine sensing, data collection, interpretation of environmental, operational, and performance related parameters to indicate systems health under its actual application conditions. The development of prognostics methodologies for the electronics field has become more important as more electrical systems are being used to replace traditional systems in several applications in the aeronautics, maritime, and automotive fields. The development of prognostics methods for electronics presents several challenges due to the great variety of components used in a system, a continuous development of new electronics technologies, and a general lack of understanding of how electronics fail. Similarly with electric unmanned aerial vehicles, electrichybrid cars, and commercial passenger aircraft, we are witnessing a drastic increase in the usage of batteries to power vehicles. However, for battery-powered vehicles to operate at maximum efficiency and reliability, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. We develop an electrochemistry-based model of Li-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles.

Li-ion Batteries

An Analysis of the Spatial Variations in the Relationship Between Built Environment and Severe Crashes

Traffic crashes significantly contribute to global fatalities, particularly in urban areas, highlighting the need to evaluate the relationship between urban environments and traffic safety. This study extends former spatial modeling frameworks by drawing paths between global models, including spatial lag (SLM), and spatial error (SEM), and local models, including geographically weighted regression (GWR), multi-scale geographically weighted regression (MGWR), and multi-scale geographically weighted regression with spatially lagged dependent variable (MGWRL). Utilizing the proposed framework, this study analyzes severe traffic crashes in relation to urban built environments using various spatial regression models within Leon County, Florida. According to the results, SLM outperforms OLS, SEM, and GWR models. Local models with lagged dependent variables outperform both the global and generic versions of the local models in all performance measures, whereas MGWR and MGWRL outperform GWR and GWRL. Local models performed better than global models, showing spatial non-stationarity; so, the relationship between the dependent and independent variables varies over space. The better performance of models with lagged dependent variables signifies that the spatial distribution of severe crashes is correlated. Finally, the better performance of multi-scale local models than classical local models indicates varying influences of independent variables with different bandwidths. According to the MGWRL model, census block groups close to the urban area with higher population, higher education level, and lower car ownership rates have lower crash rates. On the contrary, motor vehicle percentage for commuting is found to have a negative association with severe crash rate, which suggests the locality of the mentioned associations.

Alisan, Onur (ORCID:0000000193113984)

Monitoring Vegetation Health and Water Availability in Bryce Canyon National Park for Drought Stress Mitigation Planning

Bryce Canyon National Park is home to groundwater-dependent ecosystems (GDEs) that are threatened by a multidecadal drought and increased groundwater extraction due to a spike in tourism. These ecosystems contain unique species that are only found in areas where near-surface groundwater is present, such as aspen groves and willows. GDEs contribute to the high biodiversity found in Bryce Canyon, which boosts an ecosystem’s productivity and increases the overall ecological health of the park. Unfortunately, many GDEs in this area are too small to identify with traditional Earth observation platforms and are difficult to physically reach for identification and monitoring. NASA DEVELOP partnered with the National Park Service to establish a framework that both identified and assessed the health of GDEs within Bryce Canyon from 2013–2022. The team used high-resolution PlanetScope and Landsat 8 Operational Land Imager (OLI) to map springs, seeps, and GDEs. Modeled data from the Western Land Data Assimilation System (WLDAS) and in situ precipitation data were used to produce time series of climatic variables for the National Park Service to gain an understanding of how the GDEs are changing with the ongoing drought. This study is essential to the goal of the National Park Service to conserve the health of these GDEs.

Aaron Carr

Recent efforts of vapour-phase strategies for EUV resist toward high- and hyper-NA extreme ultraviolet lithography

Extreme ultraviolet lithography (EUVL, λ = 13.5 nm) is critical for sub-1 nm technology nodes but remains constrained by inherent trade-offs among resolution, line-edge roughness (LER), and sensitivity. Stochastic effects originating from photon shot noise, low-energy secondary electron blur, and the random distribution of resist components further limit its advancement toward high numerical-aperture (NA, NA = 0.55) and hyper-NA (NA ≥0.75) EUVL. While the optimization of spin-on chemically amplified resists (CARs) continues, metal-oxide resists (MORs) have emerged as strong candidates for next-generation EUVL by incorporating metals with high EUV absorption coefficients, which enhances both resist sensitivity and etch resistance during pattern transfer. Besides spin-coating, recent advances in vapour-phase techniques, such as vapour-phase infiltration (VPI), chemical vapour deposition (CVD), and molecular atomic layer deposition (MALD), offer promising pathways to achieve new resist platforms, such as dry resists, that satisfy the stringent thickness and uniformity requirements of next-generation EUVL. These methods enable the direct incorporation of metal species into existing resist matrices or the formation of hybrid inorganic–organic resist platforms, thereby improving film uniformity, etch durability, and pattern fidelity while mitigating stochastic defects. This review highlights the latest advancements in vapour-phase-synthesized EUV resists, emphasizing material design, lithographic performance, and the underlying exposure mechanisms. Although still emerging, vapour-phase strategies are paving the way for an all-dry integration framework that could improve EUV patterning workflows and meet the demands of future technology nodes.

36 MATERIALS SCIENCE

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

The Unique Capabilities of the Global Hawk Aircraft for the Study of Climate Changes

Due to unprecedented extent and flexibility of the coverage that is now attainable both in space and time, stratospheric unmanned aircraft, such as the Global Hawk (GH), offers new opportunities for the study of climate changes. The capability of performing long flights at altitudes close to the boundary conditions of radiative processes, and of following the diurnal variation of chemical species and clouds, make the GH competitive with LEO and geosynchronous satellites, and even capable of new observations that are not possible from satellites. This paper discusses how the GH can be used to make relevant advancements in most of the issues that are related to climate change studies, such as: Earth Radiation Budget, Water Cycle, Ecosystems and Upper Troposphere-Lower Stratosphere, as well as to the monitoring and control of Greenhouse Gases and Air Quality . Collaboration between NASA and Italian scientific institutions, within the framework of the US.-Italy Cooperation on Climate Change, is providing the opportunity to rapidly deploy new instruments on the GH and to possibly operate the aircraft from an Italian site in the Mediterranean area. From this area, which is considered highly vulnerable to climate change, meridional transects would allow the crossing of Polar and Sub Tropical Jets, as well as a complete crossing of the Inter Tropical Convergence Zone, while latitudinal ones would follow the influx from Asia and North America. Regions otherwise difficult to access, such as Central Africa and the Tibetan Plateau, could be reached and better investigated. An overview of these new opportunities will be given and discussed.

Cairo, F.

Extending tetrahedral network similarity to carbon: A type-I carbon clathrate stabilized by boron

Clathrates are guest/host framework compounds composed of polyhedral cages, yet despite their prevalence among tetrahedral network formers, clathrates with a carbon host lattice remain unrealized synthetic targets. Here, we report a type-I carbon-based framework—a ubiquitous clathrate structure type found throughout compounds containing tetrahedral building blocks. Following a boron-stabilization scheme based on first-principles predictions in the Ca–B–C system at high pressure, type-I Ca 8 B x C 46−x (x ≈ 9) was synthesized in the archetypal $Pm\bar{3}n$ lattice with stability derived from substitutionally disordered boron atoms on hexagonal ring framework positions. The synthesized clathrate, which is recoverable to ambient conditions, expands topological network similarity across tetrahedral systems and opens possibilities for a broad family of diamond-like, carbon-based compounds with tunable properties based on the wide potential for guest/host-atom substitutions and framework versatility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Hydropower Capacity Factor Trends & Analytics for the United States

This data repository contains all code, input data, and data generated for Turner et al. (2024)—“Hydropower capacity factors trending down in the United States”. File descriptions: – hydro-cf-trends-inputs.zip: Full set of input data used in this study, organized for direct entry into “/data” directory of hydro-cf-trends data processing pipeline. – hydro-cf-trends.zip: Full data processing pipeline, coded using the R {targets} framework. This is a snapshot release (v1.0) of the code repository stored at https://code.ornl.gov/turnersw/hydro-cf-trends/. – hydro-cf-trends-results.zip: Provides all dam level results required to reproduce results and graphics in Turner et al. (2024). Dams are identified by the “complxID” (root of the hydropower plant ID in the Existing Hydropower Assets Database, inherited from HILARRI). Results include: • dam_CF_trends.csv: Table of long-term trends in annualized capacity factors for 610 dams and modeled annualized capacity factors for 362 modeled dams (naturalized and assimilated flows). • dam_annualized_CF_gen.csv: Annualized time series of the following variables for each of 610 hydropower dams with nameplate > 5MW – Reported nameplate capacity (MW) – Implied maximum annual generation (MWh) – Reported net generation (MWh) – Computed annual capacity factor – Modeled annual capacity factor (362 modeled plants only)

13 HYDRO ENERGY

Surviving nanoscale interfacial stability in extreme thermal expansion contrast Zn(CN) 2 -epoxy resin matrix composites

Here, we report the remarkable stability at the nanoscale matrix-filler interface in a series of overall low coefficient of thermal expansion (CTE) zinc cyanide (ZC)/epoxy resin composites. These interfaces demonstrate the stability of highly contrasting materials. These composites are designed to optimize the properties of both materials: epoxy resins are valued for their high strength, superb chemical resistance, low dielectric properties, and adhesive abilities. ZC, a model flexible framework, exhibits negative thermal expansion (NTE) behavior and compensates for the epoxy resin’s detrimentally large thermal expansion values. Filled resins minimize the native 65 ppm/°C CTE values to 19 ppm/° C over a wide temperature range while maintaining linearity, yielding composites compatible with typical metal and ceramic substrates’—commonly bonded to the resin— 0–20 ppm/° C CTE values. Additionally, with significant intrinsic differences in the materials, we use wide-angle X-ray diffraction and atomic force microscopy to elucidate thermal movement. The ZC/epoxy interface is surprisingly resilient over 1,000 cycles between -55° C and 75° C, extremes typical to aerospace applications. Further, we show that the resin viscosity remains less than 21 Pa*s at up to 30 vol% ZC, an important consideration for workability. We also discuss settling distribution, glass transition temperature, flexural strength, and longevity. All results point favorably towards practical implementation in low thermal expansion application needs: filling the gap in component design.

42 ENGINEERING

Reservoir Sediment Management and Monitoring Database

Overview This dataset compiles dam sediment management and monitoring information from surveys, case studies, and journal articles. Additionally, features described by the National Inventory of Dams (i.e., presence of sluice gates) are included to indicate known infrastructure features that may address sediment releases. The location and description of records from downstream monitoring gages are catalogued in order to help with tracking conditions over time (e.g., before and after management actions, as operations change, etc.). The data help address national scale understanding of challenges and solutions related to the accumulation of sediment behind a dam as well as downstream passage. Sediment trapping causes problems as it reduces storage capacity, disrupts dam and reservoir function, impedes access for recreation, alters water quality/habitat conditions, and contributes to riverbank and coastal erosion within the reservoir. Data compilation from a variety of sources is a first step towards assessing system-wide efficacy of management solutions. This dataset was developed under the Water Power Technologies Office funded effort which began as a Seedling on Reservoir Sedimentation Data, and was supported by the Reservoir Sedimentation Modeling Framework and Data Analysis project. These projects have addressed challenges in describing sediment transport, trapping, and management at dams throughout the US. Methodology An outer join on dams/reservoirs with surveys and survey reports (documented in the RESSED database, USBR or USACE databases, project websites, etc.) with the National Inventory of Dams, based on the NIDID to determine dams with documented management and/or sluice gates. Additional dams with documented management activity were identified through review of technical articles from the past 25 years in Journal of Hydrology, Journal of Water Resources Planning and Management, Geomorphology, Journal of Hydraulic Engineering, Water, Journal of Cleaner Production, International Journal of Sediment Research, Nature Scientific Reports, Earth Surface Processes and Landforms, and Environmental Science and Pollution Research. Individual records were created for each survey or management activity documented. To evaluate downstream sediment monitoring records, the nhdPlusTools and dataRetrieval packages in R were used to find gages within 10km of each dam in the management database. Length of record and location of matched gages were retrieved for those parameters relevant to sediment concentration or total sediment discharge.

Hansen, Carly [ORNL] (ORCID:0000000193280838)