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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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Integration of Structural Analysis and Manufacturing Process Planning for Global Optimization with Automated Fiber Placement

Design of mass-efficient composite structures intended for Automated Fiber Placement (AFP) requires close interaction between structural analysis and manufacturing process planning. Tools exist for each of these disciplines, but software interplay has been insufficient for rapid and efficient design iteration. Within the NASA Advanced Composites Consortium (ACC), the Design for Manufacturing (DFM) task has made significant progress towards linking these disciplines and respective software – HyperX (design), CAPP (process planning), and VCP (tool path generation). The initial focus in previous work was on data exchange between disciplines. The ability to both export and consume composite design and manufacturing data to and from each tool. This paper focuses on the effort to automate and streamline the connection between the tools listed above, with the goal of being able to automatically generate a composite AFP design that is mass-efficient and manufacturable. The optimization method being pursued is a bi-level approach, where each tool performs optimization within its discipline. The optimization in HyperX is focused on mass and laminate strength, while CAPP is focused on maximizing manufacturability. VCP is used to generate fiber paths for each design iteration. These sub-processes are wrapped with a global level optimization, driven by HyperX, used to converge the design. This paper describes the current state of this effort, which is a completed HyperX-VCP iteration loop and initial work on the HyperX-CAPP iteration loop. Additionally, example results are shown for a wind blade structure with double curvature.

Automated Fiber Placement↗
NASA NTRS2026

Smart Process Planning for Automated Fiber Placement

Many industries, including aerospace, automotive, wind energy, maritime, and sporting goods, rely on strong, lightweight materials called composites. These materials are made by layering fibers, which can come in the form of narrow strips or wider sheets, and setting them in a polymer matrix. One of the most advanced ways to make these parts is through automated fiber placement, where a machine lays down the fibers in precise patterns. This method can create very efficient and strong designs, but it is complex, expensive, and often depends heavily on the experience of skilled engineers. Today, the design, manufacturing, and inspection stages of composite production are usually handled separately. This separation means that important information, such as how a part will be built or what defects might occur, is not always shared between stages. As a result, parts may not be as lightweight, strong, or defect-free as possible, and the process can take longer and cost more. This research develops a smart process planning system that connects design, manufacturing, and inspection into one continuous process. Built as software that works with existing tools, the system can automatically plan how the fibers are placed, predicting and reducing defects while improving both manufacturability and strength. The system optimizes not only individual layers but also how defects are distributed across all layers, preventing them from stacking up in ways that weaken the final part. It also uses inspection results from completed parts to improve future designs, creating a feedback loop where each stage informs the others. The system was tested by designing a composite panel using this new approach and comparing it to a panel made with state-of-the-art manual planning methods. The results showed that the system could intentionally control where defects appeared and increase the efficiency of the planning process. By unifying design, manufacturing, and inspection, this research shows a way to make advanced composite manufacturing more efficient, consistent, and cost-effective. This approach lowers the barrier to using automated fiber placement and opens the door for its wider adoption not only in aerospace but also in industries such as automotive, wind energy, maritime, and sporting goods, where strong and lightweight structures are essential.

Computer-Aided Process Planning↗
DOE OSTI2016

Automated Work Package: Initial Wireless Communication Platform Design, Development, and Evaluation

The Department of Energy’s Light Water Reactor Sustainability Program is developing the scientific basis to ensure long-term reliability, productivity, safety, and security of the nuclear power industry in the United States. The Instrumentation, Information, and Control (II&C) pathway of the program aims to increase the role of advanced II&C technologies to achieve this objective. One of the pathway efforts at Idaho National Laboratory (INL) is to improve the work packages execution process by replacing the expensive, inefficient, bulky, complex, and error-prone paper-based work orders with automated work packages (AWPs). An AWP is an automated and dynamic presentation of the work package designed to guide the user through the work process. It is loaded on a mobile device, such as a tablet, and is capable of communicating with plant equipment and systems to acquire plant and procedure states. The AWP replaces those functions where a computer is more efficient and reliable than a human. To enable the automatic acquisition of plant data, it is necessary to design and develop a prototype platform for data exchange between the field instruments and the AWP mobile devices. The development of the platform aims to reveal issues and solutions generalizable to large-scale implementation of a similar system. Topics such as bandwidth, robustness, response time, interference, and security are usually associated with wireless communication. These concerns, along with other requirements, are listed in an earlier INL report. Specifically, the targeted issues and performance aspects in this work are relevant to the communication infrastructure from the perspective of promptness, robustness, expandability, and interoperability with different technologies.

Automated Work Packages↗
DOE OSTI2018

Expected Improvements in Work Truck Efficiency Through Connectivity and Automation

This presentation focuses on the potential impact of connected and automated technologies on commercial vehicle operations. It includes topics such as the U.S. Department of Energy's Energy Efficient Mobility Systems (EEMS) program and the Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Initiative. It also describes National Renewable Energy Laboratory (NREL) research findings pertaining to the potential energy impacts of connectivity and automation and stresses the need for integration and optimization to take advantage of the benefits offered by these transformative technologies while mitigating the potential negative consequences.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Modeling and Optimization of Trip Level Energy Consumption and Charging Management for Connected Automated Electric Vehicles

This will be a presentation for a tutorial session in 2019 ITEC based on reviewing the publicly existing work in the literature. Trip aware energy consumption and charging management for electric vehicles is a key component to ensure sustainability of electrified transportation. The upcoming vehicle communication and autonomous driving technologies will provide opportunities to achieve more intelligent management strategies. This tutorial will introduce the state-to-art technologies that are being designed for optimizing the trip level energy cost and recharging operations of connected automated electric vehicles (CAEVs). The information needs, modeling, control and optimization techniques for optimal trip level energy management will be introduced. Opportunities and benefits from vehicle communication and automation will be discussed. In general, three main sub-topics will be presented in detail: first, advanced EV energy consumption modeling and prediction technologies; second, energy efficient driving technologies, e.g. eco-driving and eco-routing, etc.; third, optimally automatic charging decision making for CAEVs. Following these details, the research challenges, opportunities for co-optimization between the energy consumption and energy recharging of CAEVs will be illustrated in this tutorial.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Automated Mobility Districts - A Conceptual Definition: Preprint

An automated mobility district (AMD) provides for the movement of people and goods within a district through the use of fleets of roboticized vehicles as the primary mobility system. The concept of an AMD has precursors deployed in a few places around the world, in which the circulation within a dense urban district, such as a business and residential center or a major activity center like an airport terminal complex is accomplished using a fully automated transport system(s).

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Automation and Use of Robotics for Decommissioning Tasks - 18322

Decommissioning across the globe is being executed largely by manual labor. The Organization for Economic Co-operation and Development (OECD) has concluded that the nuclear industry has not fully exploited or implemented current technological capabilities, and relies on sometimes outdated technology to perform decommissioning tasks [1]. To address this issue, EPRI recently published the report Evaluation of System Automation and Robotics for Decommissioning Applications (EPRI 3002010599) [2]. To facilitate wide usage of the guidance by technology developers, the report is publicly available at no cost. The use of more efficient and effective decommissioning technologies and processes could reduce the decommissioning project schedule and therefore reduce the period-dependent costs incurred throughout the decommissioning project. Such systems may also offer a substantial benefit with respect to worker safety and radiation exposure reduction. However, tasks for which use of such systems is beneficial must be carefully considered, being robust and generally trouble free to operate in the demanding environment of commercial power plant decommissioning. A review of the major tasks involved in the decommissioning of a nuclear power plant is presented, with a critical assessment of the benefits for the use of robotics and/or automation. Recommendations for areas of future research and development are identified. The results of this project will be beneficial to global organizations working on development of engineered systems for decommissioning applications by providing a focus on priority tasks. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Automated Work Package: Initial Wireless Communication Platform Design, Development, and Evaluation

The Department of Energy's Light Water Reactor Sustainability Program is developing the scientific basis to ensure long-term reliability, productivity, safety, and security of the nuclear power industry in the United States. The Instrumentation, Information, and Control (II and C) pathway of the program aims to increase the role of advanced II and C technologies to achieve this objective. One of the pathway efforts at Idaho National Laboratory (INL) is to improve the work packages execution process by replacing the expensive, inefficient, bulky, complex, and error-prone paper-based work orders with automated work packages (AWPs). An AWP is an automated and dynamic presentation of the work package designed to guide the user through the work process. It is loaded on a mobile device, such as a tablet, and is capable of communicating with plant equipment and systems to acquire plant and procedure states. The AWP replaces those functions where a computer is more efficient and reliable than a human. To enable the automatic acquisition of plant data, it is necessary to design and develop a prototype platform for data exchange between the field instruments and the AWP mobile devices. The development of the platform aims to reveal issues and solutions generalizable to large-scale implementation of a similar system. Topics such as bandwidth, robustness, response time, interference, and security are usually associated with wireless communication. These concerns, along with other requirements, are listed in an earlier INL report. Specifically, the targeted issues and performance aspects in this work are relevant to the communication infrastructure from the perspective of promptness, robustness, expandability, and interoperability with different technologies. The development of a prompt system entailed significant performance optimization, including the use of parallel processing, parallel communication, modularity, noise filtering, and frequency tuning. A robust system was achieved by enforcing a persistent continuous data exchange that automatically detects and conveys a failure of any link or component in any part of the system, and that automatically restores the communication once the link or component is restored. An expandable topology was enabled by modularity and load sharing. The number of servers, mobile devices, and field instruments is not limited from a system structure point of view. The system interoperability was achieved by enforcing the independence of the field communication application from the mobile device application. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Commissioning of Robotic Inspection and Automated Analysis System for Assay of Gas Diffusion Piping - 19500

Robotic, in-pipe, nondestructive assay (NDA) is a revolutionary and important means for measuring, analyzing, and reporting radioactive holdup deposits in enrichment piping. This innovation promises vast advantages for efficiency, safety, and cost savings. Payoff, however, lies in utilization much more than innovation. Crossing that threshold from a technical capability to an everyday tool occurs only after rigorous commissioning, adoption, and infusion. This must meet the highest standard, and there can be no compromise. Certification of a new NDA technology must meet the highest standards for quality, safety, and efficacy. Prior to this work, there was no precedent of procedure and method for certification of a robotic methodology for this purpose. The best of robotics had not certified NDA. The best of NDA had not certified robotics. Hence, a great deal of discovery, resourcefulness, and collaboration contributed to this success. This paper chronicles the first-of-kind chartering, co-development, testing, documentation, and site integration that certified this trailblazing in-pipe, robotic NDA. Commissioning had to demonstrate and certify end-to-end NDA automation from robot traversal to computer analysis to report generation of contaminated process piping at the Portsmouth, Ohio gaseous diffusion facility. This was a rigorous campaign of tests, evaluations, and documentation. Highlights included multiple tests in four elevated pipes exercised the gamut of NDA and robotic capabilities. Each of the four test pipes presented a unique loading of U-235. The tests demonstrated operations in both 30- inch and 42-inch diameter pipes with varying lengths and terminated by a variety of valves and fittings. Tests in a fifth pipe at floor level demonstrated deployment and applicability for pipes at this ground height and robot recognition of another fitting type. All operations, calibration, deployment, auto-reporting, and analysis were handled by Portsmouth site personnel. These tests concluded a series of component-level acceptance tests which certified all constituent technologies and operational features. Test metrics included comparison of reported to ground truth results and assessment of data quality from quality assurance and replicate measurement comparison. Beyond the radiometry associated with any NDA method, this unique commissioning path exercised and evaluated all the robotic features that are intrinsic to automation. These include odometry, geometric modeling, autonomy, remote launch and recovery, and end-to-end data flow. Each of these required verification and certification. These evaluations were first-of-kind for the decommissioning community, requiring innovation and resourcefulness in their own right. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Automated Label‐Free Assay for Viral Detection and Inhibitor Screening via Biomembrane‐Functionalized Microelectrode Arrays

Most virus infection assays have indirect readout such as virus number following entry (e.g., PCR, cell lysis). While effective, these technologies are labor‐intensive, require specialized environments (e.g., sterile or RNA‐free), and detect later‐stage viral events like lysis or cell death, lacking sensitivity to early fusion events. To address these limitations, we present biologically relevant 2D membrane materials, host‐cell‐derived supported lipid bilayers (hcd‐SLBs), integrated with organic microelectrode arrays (OMEAs) for detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) fusion. By overexpressing angiotensin‐converting enzyme 2 (ACE2) receptors on the native membranes, the platform functions as a viral sensor capable of detecting virus pseudo particles (VPPs) through the late pathway. Additionally, hcd‐SLBs extracted from human lung epithelium expressing native ACE2 detect fusion events through the early pathway. The platform's utility as a drug‐screening tool is demonstrated by testing antibodies targeting either the ACE2 on the host membrane or the viral spike (S) proteins. To enhance the throughput, microfluidics are integrated for automation and OMEAs are incorporated within each channel, miniaturizing the testing units. This system supports high‐throughput data generation, automation, and scalability, providing an efficient platform for viral fusion detection that advances the study of pathogen‐host interactions and accelerates antiviral drug discovery.

Biology↗
DOE OSTI2023

High-Throughput Automated Exploration of Phase Growth Behaviors in Quasi-2D Formamidinium Metal Halide Perovskites

Quasi-2D metal halide perovskites (MHPs) are an emerging material platform for sustainable functional optoelectronics, but the uncontrollable, broad phase distribution remains a critical challenge for applications. Nevertheless, the basic principles for controlling phases in quasi-2D MHPs remain poorly understood, due to the rapid crystallization kinetics during the conventional thin-film fabrication process. In this work, a high-throughput automated synthesis-characterization-analysis workflow is implemented to accelerate material exploration in formamidinium (FA)-based quasi-2D MHP compositional space, revealing the early-stage phase growth behaviors fundamentally determining the phase distributions. Upon comprehensive exploration with varying synthesis conditions including 2D:3D composition ratios, antisolvent injection rates, and temperatures in an automated synthesis-characterization platform, it is observed that the prominent n = 2 2D phase restricts the growth kinetics of 3D-like phases—α-FAPbI 3 MHPs with spacer-coordinated surface—across the MHP compositions. Thermal annealing is a critical step for proper phase growth, although it can lead to the emergence of unwanted local PbI 2 crystallites. Additionally, fundamental insights into the precursor chemistry associated with spacer-solvent interaction determining the quasi-2D MHP morphologies and microstructures are demonstrated. The high-throughput study provides comprehensive insights into the fundamental principles in quasi-2D MHP phase control, enabling new control of the functionalities in complex materials systems for sustainable device applications.

2D perovskites↗
DOE OSTI2023

Black carbon emissions from modern automated cordwood stoves for space heating

Wood burning stove design is improving as regulation become stricter for particulate matter emissions. Here, this study describes results of black carbon (BC) emissions from three modern automated wood stoves when tested in common failure modes using a test protocol that included cold-starts, high and low fuel loading densities, and use of overly large pieces of fuel. Emission sampling was performed using a dilution sampling system in tandem with an aethalometer to measure BC with high time resolution. Results show that the time-weighted average BC emission rates were 0.91, 4.30, and 1.74 g/h for the three stoves tested (A, B, and C respectively), the values, both higher and lower than the United States 2020 certification test emission limit of 2.5 g/h. The results demonstrate good performance overall, given the rigorous nature of the testing protocol used. The aethalometer data showed that the performance was relatively poor during cold-start, when the fuel was ignited and combusted without a coalbed, and when stoves failed to optimize air delivery due to specific loading and output conditions. During the cold-start test section, the average BC emission rate was seven times higher than the overall average for Stove A, 10 times above the average for Stove B, and two times above the average emission rate for Stove C. Calculations of the Average Angstrom Absorption Exponent (AAE) of the exhaust aerosol showed little correlation with BC concentration. The results show that automation results in a quantifiable reduction in particular BC emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software

The open-source statistical mechanics software described here, Arkane–Automated Reaction Kinetics and Network Exploration–facilitates computations of thermodynamic properties of chemical species, high-pressure limit reaction rate coefficients, and pressure-dependent rate coefficient over multi-well molecular potential energy surfaces (PES) including the effects of collisional energy transfer on phenomenological kinetics. Arkane can use estimates to fill in information for molecules or reactions where quantum chemistry information is missing. The software solves the internal energy master equation for complex unimolecular reaction systems. Inputs to the software include converged electronic structure computations performed by the user using a variety of supported software packages (Gaussian, Molpro, Orca, TeraChem, Q-Chem, Psi4). The software outputs high-pressure limit rate coefficients and pressure-dependent phenomenological rate coefficients, as well as computed thermodynamic properties (enthalpy, entropy, and constant pressure heat capacity) with added energy corrections. Some of the key features of Arkane include treatment of 1D, 2D or ND hindered internal rotation modes, treatment of free internal rotation modes, quantum tunneling effect consideration, transition state theory (TST) and Rice-Ramsperger-Kassel-Marcus (RRKM) rate coefficient computations, master equation solution with four implemented methods, inverse-Laplace transform of high-pressure limit rate coefficients into the energy domain, energy corrections based on bond-additivity or isodesmic reactions, automated and efficient PES exploration, and PES sensitivity analysis. The present work describes the design of Arkane, how it should be used, and refers to the theory that it employs. Arkane is distributed via the RMG-Py software suite (https://github.com/ReactionMechanismGenerator/RMG-Py).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Automated detection of photovoltaic cleaning events: A performance comparison of techniques as applied to a broad set of labeled photovoltaic data sets

Extracting accurate soiling loss information from photovoltaic (PV) production data first requires segmenting the time series data per natural or manually occurring cleaning events. Maintenance logs are often incomplete, rain data are often unavailable, and the debate on rain thresholds for cleaning and dew or wind cleanings is still ongoing. The present work aims to overtake these issues by improving automated methods to detect these cleaning events and therefore improve extraction of soiling loss information. Time series power production data from 22 PV inverters were labeled for natural or manually occurring cleaning events. The data sets were carefully selected to include varying degrees of soiling, cleaning events, and noise. Several algorithms, including filtering logic and change point detection, were examined for efficacy at detecting the labeled cleanings. All the methods introduced except for changepoint detection showed significant improvement at detecting the labeled cleaning events per the mean F 1 score. Furthermore, the highest performing cleaning detection algorithm achieved an absolute increase in the mean F 1 score of 43% over the default version of the RdTools stochastic rate and recovery (SRR) algorithm. The highest performing algorithm included irradiance filtering and a cleaning detection threshold, adjusted based on the 40-day centered rolling median of the absolute day-to-day deviations in the daily performance index (PI). Furthermore, these improvements are promising as cleaning detection is an essential step in the automated analysis of PV soiling.

14 SOLAR ENERGY↗
DOE OSTI2025

UnigeneFinder: An Automated Pipeline for Gene Calling From Transcriptome Assemblies Without a Reference Genome

ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use.

Xue, Bo [Plant Resilience Institute Michigan State↗
DOE OSTI2018

Additive Manufacturing – A New Challenge for Automation and Robotics

Additive manufacturing (AM) is a rapidly growing technology descended from the first stereolithography systems. AM describes a variety of material deposition technologies for forming objects in a digital manner layer-by-layer under computer control. Now commonly known as 3D printing, AM quickly branched out into several key directions – material extrusion, sheet lamination, direct energy deposition, vat polymerization, powder bed fusion, binder jetting, and material jetting. The common factor in all AM branches is a foundation in robotics and automation. While most of the mechanical 3D printing structures are based on simple gantry systems, there are Gough-Stewart platforms and, more recently, six or more DoF manipulator-based systems that have been developed. Currently available commercial systems are based on open-loop control with minimum sensing capabilities; the latest systems in development are starting to take advantage of complex feedback loops and layers of advanced sensing and data logging. The Manufacturing Demonstration Facility of Oak Ridge National Laboratory is leading the efforts in applying advanced robotics in the creation of large-scale 3D printers. The recent demonstration of an additively manufactured excavator at the CONEXPO 2017 exhibition in Las Vegas showed that the use of cutting edge robotics and automation is essential for the next generation of additive systems. The future of AM will heavily rely on advanced robotics, machine learning, and the internet of things. This paper summarizes progress in AM; presents the practical aspects, challenges, and lessons learned in developing robotic-based AM systems; and outlines the needs and future directions of robotics for AM.

Nycz, Andrzej↗
DOE OSTI2018

Single-Center Experience Implementing the LOINC-RSNA Radiology Playbook for Adult Abdomen/Pelvis CT and MR Procedures Using a Semi-Automated Method

The LOINC-RSNA Radiology Playbook represents the future direction of standardization for radiology procedure names. We developed a software solution (“RadMatch”) utilizing Python 2.7 and FuzzyWuzzy, an open-source fuzzy string matching algorithm created by SeatGeek, to implement the LOINC-RSNA Radiology Playbook for adult abdomen and pelvis CT and MR procedures performed at our institution. Execution of this semi-automated method resulted in the assignment of appropriate LOINC numbers to 86% of local CT procedures. For local MR procedures, appropriate LOINC numbers were assigned to 75% of these procedures whereas 12.5% of local MR procedures could only be partially mapped. For the standardized local procedures, only 63% of CT and 71% of MR procedures had corresponding RadLex Playbook identifier (RPID) codes in the LOINC-RSNA Radiology Playbook, which limited the utility of RPID codes. RadMatch is a semi-automated open-source software tool that can assist radiology departments seeking to standardize their radiology procedures via implementation of the LOINC-RSNA Radiology Playbook.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Ensuring Safety of Hydraulic Equipment at the Votkinsk Hydroelectric Power Plant with an Automated Diagnostic Monitoring System

Experience with the use of an automated diagnostic monitoring system for the technical condition and safety of concrete structures at the Votkinsk HPP is discussed. The automated system for monitoring the state of the hydraulic engineering systems has been developed to increase the accuracy, reliability, and efficiency of the data from instrumental observations during operation of the plant.

42 ENGINEERING↗