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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Overview of NLR Automated Mobility District Implementation Research - Phases I, II, and III. The Convergence of Automation, Electrification, and On-Demand Services: Enabling Resilient Automated Mobility Districts

A research program by the National Renewable Energy Laboratory has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings, referred to as Automated Mobility Districts (AMDs). An AMD emphasizes the deployment of automated vehicles (AV) passenger transport services within a dense urban setting and other major activity centers with intense passenger origin-destination demand patterns, such as those found in large business districts, airports, and university and medical campuses. Phase I and II surveyed 10 early deployment sites and subsequently collected and evaluated the lessons learned from these early deployment sites, with particular attention to fleet operations, impacts of service reliability, and vehicle technology evolution as the field of companies was being progressively winnowed by the challenges of full automation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimized anion exchange column isolation of zirconium-89 (89Zr) from yttrium cyclotron target: Method development and implementation on an automated fluidic platform

Zirconium-89 (89Zr), produced by the (p,n) reaction from naturally monoisotopic yttrium (natY), is a promising positron emitting isotope for immunoPET imaging. Its long half-life of 78.4 h is sufficient for evaluating slow physiological processes. A prototype automated fluidic system, coupled to on-line and in-line detectors, has been constructed to facilitate development of new 89Zr purification methodologies. The highly reproducible reagent delivery platform and near-real time monitoring of column effluents allows for efficient method optimization. The separation of Zr from dissolved Y metal targets was evaluated using several anion exchange resins. Each resin was evaluated against its ability to quantitatively capture Zr from a load solution that is high in dissolved Y. The most appropriate anion exchange resin for this application was identified, and the separation method was optimized. The method is capable of a high Y decontamination factor (>105) and has been shown to separate Fe, an abundant contaminant in Y foils, from the 89Zr elution fraction. Finally, the performance of the method was evaluated using cyclotron bombarded Y foil targets. The separation method was shown to achieve >95% recovery of the 89Zr present in the foils. The 89Zr eluent, however, was in a chemical matrix not immediately conducive to labeling onto proteins. The main intent of this study was to develop a tandem column 89Zr purification process, wherein the anion exchange column method described here is the first separation in a dual-column purification process.

Zirconium-89, ImmunoPET, medical isotope, automati↗

DESCQA: An Automated Validation Framework for Synthetic Sky Catalogs

The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys. The catalogs have diverse applications, such as investigating signatures of fundamental physics in cosmological observables, understanding the effect of systematic uncertainties on measured signals and testing mitigation strategies for reducing these uncertainties, aiding analysis pipeline development and testing, and survey strategy optimization. The list of applications is growing with improvements in the quality of the catalogs and the details that they can provide. Given the importance of simulated catalogs, it is critical to provide rigorous validation protocols that enable both catalog providers and users to assess the quality of the catalogs in a straightforward and comprehensive way. For this purpose, we have developed the DESCQA framework for the Large Synoptic Survey Telescope Dark Energy Science Collaboration as well as for the broader community. The goal of DESCQA is to enable the inspection, validation, and comparison of an inhomogeneous set of synthetic catalogs via the provision of a common interface within an automated framework. Here in this paper, we present the design concept and first implementation of DESCQA. In order to establish and demonstrate its full functionality we use a set of interim catalogs and validation tests. We highlight several important aspects, both technical and scientific, that require thoughtful consideration when designing a validation framework, including validation metrics and how these metrics impose requirements on the synthetic sky catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗

Safe Operations at Roadway Junctions - Design Principles from Automated Guideway Transit

Herein this paper describes a system-level view of a fully automated transit system comprising a fleet of automated vehicles (AVs) in driverless operation, each with an SAE level 4 Automated Driving System, along with its related safety infrastructure and other system equipment. This AV system-level control is compared to the automatic train control system used in automated guideway transit technology, particularly that of communications-based train control (CBTC). Drawing from the safety principles, analysis methods, and risk assessments of CBTC systems, comparable functional subsystem definitions are proposed for AV fleets in driverless operation. With the prospect of multiple AV fleets operating within a single automated mobility district, the criticality of protecting roadway junctions requires an approach like that of automated fixed-guideway transit systems, in which a guideway switch zone "interlocking" at each junction location deconflicts railway traffic, affirming safe passage. The analogous AV protection safety subsystem is defined as fail-safe equipment that monitors roadway intersections and junctions, communicates traffic signal status, perceives and communicates alerts and signals to AV connected vehicles concerning potential unsafe conditions, and performs related primary safety functions. Conclusions are drawn that the AV protection roadway intersection functions must be performed by local roadside equipment dedicated to protecting each roadway intersection and junction. Further, it is concluded that the communications technology connecting the infrastructure with the vehicle to perform this vital, fail-safe protection should meet specific functional and performance criteria.

33 ADVANCED PROPULSION SYSTEMS↗

Vehicle Automation Benefits and Challenges for Passenger Transport System Beyond Automated Driving

The National Renewable Energy Laboratory has been researching the implementation of fully automated passenger transport systems to be operated within dense urban settings, referred to as Automated Mobility Districts, based on roadway vehicle automation as opposed to track or train-based automation. This research, now in its third phase, is presently addressing the full spectrum of benefits and challenges of full automation of passenger transport systems with respect to fleet electrification and the associated multimodal, large fleet operational management, benefits beyond simply automating the driving tasks. The focal points summarized in the paper and presentation address the benefit-analysis of fleet automation to address added complexities imposed on the multi-fleet operational management when there is a simultaneous implementation of an on-demand service mode that connects with and optimizes the effectiveness of legacy transit systems and new sub-regional autonomous vehicle fleets, with specific emphasis on enhanced ability to better meet peak ridership demand. The research also begins to address challenges in operations arising from lack of personnel present to handle unexpected customer and system needs. Combined, this research articulates vehicle automation benefits and challenges beyond simply automating the driving tasks, addressing additional operational benefits automation provides to address the added complexities imposed by electrification and on-demand modes of operation.

33 ADVANCED PROPULSION SYSTEMS↗

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗

Automated correlative segmentation of large Transmission X-ray Microscopy (TXM) tomograms using deep learning

Highlights: • A unique automated segmentation approach for large 3D nanotomography datasets obtained by Transmission X-ray Microscopy (TXM) in an Al-Cu alloy. • Automated segmentation using a Convolutional Neural Network (CNN) architecture based on a deep learning approach was employed. • This extremely versatile technique is capable of emulating the manual segmentation process effectively. • Quantitative comparison between manual segmentation and CNN architecture established the accuracy of this automated technique. • Its ability to robustly process ultra-large volumes of data in relatively small time frames can exponentially accelerate tomographic data analysis. - Abstract: A unique correlative approach for automated segmentation of large 3D nanotomography datasets obtained using Transmission X-ray Microscopy (TXM) in an Al-Cu alloy has been introduced. Automated segmentation using a Convolutional Neural Network (CNN) architecture based on a deep learning approach was employed. This extremely versatile technique is capable of emulating the manual segmentation process effectively. Coupling this technique with post-scanning SEM imaging ensured precise estimation of 3D morphological parameters from nanotomography. The segmentation process as well as subsequent analysis was expedited by several orders of magnitude. Quantitative comparison between segmentation performed manually and using the CNN architecture established the accuracy of this automated technique. Its ability to robustly process ultra-large volumes of data in relatively small time frames can exponentially accelerate tomographic data analysis, possibly opening up novel avenues for performing 4D characterization experiments with finer time steps.

36 MATERIALS SCIENCE↗

Optimizing Fleet Operations in Automated Mobility Districts: Serving On-Demand Mobility with Automated Electric Shuttles

On-demand transportation services have seen a dramatic rise in the past decade, thanks to technology. Connected and automated vehicle (CAV) technology holds potential for a major transformation in the on-demand mobility services landscape.The timeline for fully automated vehicles (AVs) to reach the critical market share is still uncertain. In the short term, many cities in the United States and abroad are testing low-speed automated electric shuttles (AES) as a shared on-demand mobility service in geo-fenced regions. An automated mobility district (AMD) is a campus-sized implementation of connected/automated vehicle technology to realize the full benefits of a fully electric automated mobility service within a confined region or district. Building on this concept, an AMD toolkit is under development at the National Renewable Energy Laboratory (NREL) to inform a campus-or district-sized implementation in which automated electric shuttles (AES). This research extends the functionality of the AMD toolkit by developing a mathematical program to optimize the operations of an AES fleet in an on-demand service configuration.

25 ENERGY STORAGE↗

Learning from Automation Surprises and "Going Sour" Accidents: Progress on Human-Centered Automation

Advances in technology and new levels of automation on commercial jet transports has had many effects. There have been positive effects from both an economic and a safety point of view. The technology changes on the flight deck also have had reverberating effects on many other aspects of the aviation system and different aspects of human performance. Operational experience, research investigations, incidents, and occasionally accidents have shown that new and sometimes surprising problems have arisen as well. What are these problems with cockpit automation, and what should we learn from them? Do they represent over-automation or human error? Or instead perhaps there is a third possibility - they represent coordination breakdowns between operators and the automation? Are the problems just a series of small independent glitches revealed by specific accidents or near misses? Do these glitches represent a few small areas where there are cracks to be patched in what is otherwise a record of outstanding designs and systems? Or do these problems provide us with evidence about deeper factors that we need to address if we are to maintain and improve aviation safety in a changing world? How do the reverberations of technology change on the flight deck provide insight into generic issues about developing human-centered technologies and systems (Winograd and Woods, 1997)? Based on a series of investigations of pilot interaction with cockpit automation (Sarter and Woods, 1992; 1994; 1995; 1997a, 1997 b), supplemented by surveys, operational experience and incident data from other studies (e.g., Degani et al., 1995; Eldredge et al., 1991; Tenney et al., 1995; Wiener, 1989), we too have found that the problems that surround crew interaction with automation are more than a series of individual glitches. These difficulties are symptoms that indicate deeper patterns and phenomena concerning human-machine cooperation and paths towards disaster. In addition, we find the same kinds of patterns behind results from studies of physician interaction with computer-based systems in critical care medicine (e.g., Moll van Charante et al., 1993; Obradovich and Woods, 1996; Cook and Woods, 1996). Many of the results and implications of this kind of research are synthesized and discussed in two comprehensive volumes, Billings (1996) and Woods et al. (1994). This paper summarizes the pattern that has emerged from our research, related research, incident reports, and accident investigations. It uses this new understanding of why problems arise to point to new investment strategies that can help us deal with the perceived "human error" problem, make automation more of a team player, and maintain and improve safety.

Woods, David D.↗

Will Vehicle Automation Accelerate or Decelerate Electrification: Modeling Demand for Automated Electric Vehicles

Automation may induce more travel demand, posing a threat to energy security and environmental quality unless the induced travel demand is served with more efficient or clean fuel technologies. This study attempts to analyze whether automation may promote or discourage market acceptance of plug-in electric vehicles. A consumer choice model called MA3T-MC is developed to cover automated vehicles by expanding the existing MA3T model that focuses only on fuel type choices. Key findings include: 1) automation may increase sales shares of gasoline conventional vehicles and decrease shares of efficient vehicles including HEVs and PHEVs, due to greater energy cost savings for less efficient vehicles. 2) Automation may increase market shares of BEVs, due to the “free” range extension from the efficiency improvement by automation. 3) consumer heterogeneity is important in quantifying the national impact of automation on sales shares by fuel types and the total energy use.

Lin, Zhenhong↗

JOINT APPOINTEE: Evolution of ferroelectric properties in SmxBi1-xFeO3 via automated Piezoresponse Force Microscopy across combinatorial spread libraries

Combinatorial spread libraries offer a innovative approach to explore the evolution of material properties over broad concentration, temperature, and growth parameter spaces. However, traditional limitation of this approach is the requirement for the read-out of functional properties across the library. Here we develop automated Piezoresponse Force Microscopy (PFM) for the exploration of combinatorial spread libraries and demonstrate its application in the SmxBi1-xFeO3 system with the ferroelectric-antiferroelectric morphotropic phase boundary. This approach relies on the synergy of the quantitative nature of PFM and the implementation of automated experiments that allow PFM-based sampling over macroscopic samples. The concentration dependence of pertinent ferroelectric parameters has been determined and used to develop the mathematical framework based on Ginzburg-Landau theory describing the evolution of these properties across the concentration space. We pose that a combination of automated scanning probe microscope and combinatorial spread library approach will emerge as an efficient research paradigm to close the characterization gap in the high-throughput materials discovery. We make the data sets open to the community and hope that this will stimulate other efforts to interpret and understand the physics of these systems.

Automated Microscopy, Combinatorial Library, Ferro↗

An Automated Vehicle Fuel Economy Benefits Evaluation Framework Using Real-World Travel and Traffic Data

Increasing automation is a consistent development trend in the automobile industry. However, real-world evaluation of the operational and energy consumption differences between automated vehicles and comparable manually driven vehicles has been limited. This study helps fill the information gap by comparing the operation and fuel economy of vehicles in adaptive cruise control (ACC) and non-ACC modes based on large-scale field test data collected by Volvo Car Corporation (Volvo Cars) from vehicles traveling on the designated 'Drive Me' project road network in Gothenburg, Sweden. The test vehicles' travel data are classified by driving mode (ACC vs. non-ACC) and driving conditions, which refer to traffic speed and road grade in this study. The results from the data logging fleet are used to estimate the aggregate fuel consumption differences at the Drive Me road-network level for vehicles traveling in ACC vs. non-ACC mode based on appropriately weighting the total amount of travel that took place on the network under different driving conditions. At the ACC penetration levels observed in the field test data, vehicles tended to drive more smoothly in ACC mode than in non-ACC mode. The corresponding travel-weighted fuel consumption rate for vehicles in ACC mode was about 5%-7% lower than for vehicles in non-ACC mode when traveling at similar conditions. Sensitivity analyses impart confidence in this result, and in the future, the established evaluation framework could be used to objectively quantify potential on-road fuel consumption impacts from vehicles with even higher levels of automated driving capability.

33 ADVANCED PROPULSION SYSTEMS↗

Data Trend Shifts Induced by Method of Concentration for Trace Metals in Seawater: Automated Online Preconcentration vs Borohydride Reductive Coprecipitation of Nearshore Seawater Samples for Analysis of Ni, Cu, Zn, Cd, and Pb via ICP-MS

This research compares performance, reproducibility, and detection limits of ambient seawater analysis for trace metals using both borohydride reductive co-precipitation and an automated chelation column (seaFAST™ 2) co-preconcentration for matrix interferent elimination on total and dissolved grab samples in nearshore to marine waters, over a broad concentration range, prior to ICP-MS injection. A move to an online preconcentration method both minimizes sample preparation, and eliminates correction errors when accounting for trace impurities in precipitated samples, induced via reagents. The reproducability of the online preconcentration method described, coupled with low blanks and method detection limits (MDLs), demonstrates an effective move to an automated procedure using ethylenediaminetriacetic and iminodiacetate acid chelation exchange resin and multi-analyte determination via ICP-MS for total and dissolved Ni, Cu, Zn, Cd, and Pb in marine water samples. Average CASS-5 recoveries using the online preconcentration method (n=9) were 109±7%, 104±5%, 103±7%, 101±3%, and 86±8% respectively. The MDLs obtained from the automated method for Ni, Cu, Zn, Cd and Pb were 3.3, 1.8, 13.5, 4, and 10 times lower, respectively, than for the Borohydride method. There were statistically significant differences between the methods for CASS-5 recoveries of Ni, Cu, Zn (p < 0.0001), and Pb (p = 0.0024). Comparison of methods gave high concordance (rC = 0.90) between methods for total and dissolved Ni, Cu, Zn, and Pb, and total Cd.

seaFAST, borohydride, seawater, Ethylenediaminetet↗

Automated ICRF heating surrogate modeling via machine learning

This work introduces automated machine learning workflows that address critical bottlenecks in surrogate model development for Ion Cyclotron Range of Frequencies (ICRF) heating applications. The automated framework includes data analysis tools that transform raw datasets into actionable insights in seconds, replacing weeks of manual exploratory effort and ensuring consistent, reproducible dataset characterization. By integrating advanced hyperparameter optimization (HPO) methods including Bayesian optimization via BoTorch and Tree-structured Parzen Estimators (TPE), the framework significantly reduces model development time from weeks to hours, decreasing computational cost and required expertise, while enabling high-accuracy surrogate models. Compared to traditional hyperparameter scanning (HPS) techniques such as methodical, randomized, and grid searches, HPO methods achieve superior convergence and predictive performance, even when compared to already well-tuned reference models. On NSTX High Harmonic Fast Wave (HHFW) heating datasets, both Random Forest Regressor (RFR) and neural network surrogates demonstrate improved accuracy, achieving R 2 values beyond 0.97 and 0.98, respectively. The results show that while HPO gains are modest for robust architectures like RFR, they become essential for more sensitive models such as neural networks, highlighting the trade-offs across optimization strategies. Through automated workflows that eliminate manual hyperparameter tuning and require minimal ML expertise, this work enables widespread adoption of high-fidelity surrogate models across the fusion community for real-time plasma control, uncertainty quantification, rapid experimental scenario development, and integrated system optimization.

Sanchez-Villar, Alvaro [Princeton Plasma Physics L↗

Automated data processing architecture for the Gemini Planet Imager Exoplanet Survey

The Gemini Planet Imager Exoplanet Survey (GPIES) is a multiyear direct imaging survey of 600 stars to discover and characterize young Jovian exoplanets and their environments. We have developed an automated data architecture to process and index all data related to the survey uniformly. An automated and flexible data processing framework, which we term the Data Cruncher, combines multiple data reduction pipelines (DRPs) together to process all spectroscopic, polarimetric, and calibration data taken with GPIES. With no human intervention, fully reduced and calibrated data products are available less than an hour after the data are taken to expedite follow up on potential objects of interest. The Data Cruncher can run on a supercomputer to reprocess all GPIES data in a single day as improvements are made to our DRPs. A backend MySQL database indexes all files, which are synced to the cloud, and a front-end web server allows for easy browsing of all files associated with GPIES. To help observers, quicklook displays show reduced data as they are processed in real time, and chatbots on Slack post observing information as well as reduced data products. Together, the GPIES automated data processing architecture reduces our workload, provides real-time data reduction, optimizes our observing strategy, and maintains a homogeneously reduced dataset to study planet occurrence and instrument performance.

79 ASTRONOMY AND ASTROPHYSICS↗

Process development for automated solar cell and module production. Task 4: Automated array assembly

A process sequence which can be used in conjunction with automated equipment for the mass production of solar cell modules for terrestrial use was developed. The process sequence was then critically analyzed from a technical and economic standpoint to determine the technological readiness of certain process steps for implementation. The steps receiving analysis were: back contact metallization, automated cell array layup/interconnect, and module edge sealing. For automated layup/interconnect, both hard automation and programmable automation (using an industrial robot) were studied. The programmable automation system was then selected for actual hardware development.

Source record↗

Modeling Increased Complexity and the Reliance on Automation: FLightdeck Automation Problems (FLAP) Model

This paper highlights the development of a model that is focused on the safety issue of increasing complexity and reliance on automation systems in transport category aircraft. Recent statistics show an increase in mishaps related to manual handling and automation errors due to pilot complacency and over-reliance on automation, loss of situational awareness, automation system failures and/or pilot deficiencies. Consequently, the aircraft can enter a state outside the flight envelope and/or air traffic safety margins which potentially can lead to loss-of-control (LOC), controlled-flight-into-terrain (CFIT), or runway excursion/confusion accidents, etc. The goal of this modeling effort is to provide NASA's Aviation Safety Program (AvSP) with a platform capable of assessing the impacts of AvSP technologies and products towards reducing the relative risk of automation related accidents and incidents. In order to do so, a generic framework, capable of mapping both latent and active causal factors leading to automation errors, is developed. Next, the framework is converted into a Bayesian Belief Network model and populated with data gathered from Subject Matter Experts (SMEs). With the insertion of technologies and products, the model provides individual and collective risk reduction acquired by technologies and methodologies developed within AvSP.

Ancel, Ersin↗