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All sources NASA NTRS DOE OSTI

DOE OSTI2025

Multi-agent AI collaboration for digital twin development and assessment

Developing a digital twin (DT) model involves different steps that encompass formulating requirements, model development, implementation, and assessment with respect to real applications. Human expertise is required to coordinate and implement different steps in the DT development and assessment process. However, certain parts of this process can be automated using artificial intelligence (AI) agents for efficient workflow development. In this work, we test and analyze a multiagent AI collaboration with humans in the loop to automate different elements of the DT development and assessment process. To implement the workflow for multiagent AI DT development and assessment, we use Autogen, a multiagent framework developed by Microsoft. Autogen offers a modular and flexible framework for configuring and designing task-specific multiagent workflows. In this framework, large language models (LLMs) form the core intelligence of the AI agents where the quality and performance of the automated element is governed by the inherent capabilities and knowledge base of the LLM. We use retrieval augmented generation to supplement the LLM with relevant domain-specific information for DT requirement formulation. We illustrate this multiagent workflow using a case study on a thermal energy storage system, focusing on how AI agents can collaborate with humans to expedite and optimize different elements of DT development and assessment process.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2014

Engine Power Turbine and Propulsion Pod Arrangement Study

A study has been conducted for NASA Glenn Research Center under contract NNC10BA05B, Task NNC11TA80T to identify beneficial arrangements of the turboshaft engine, transmissions and related systems within the propulsion pod nacelle of NASA's Large Civil Tilt-Rotor 2nd iteration (LCTR2) vehicle. Propulsion pod layouts were used to investigate potential advantages, disadvantages, as well as constraints of various arrangements assuming front or aft shafted engines. Results from previous NASA LCTR2 propulsion system studies and tasks performed by Boeing under NASA contracts are used as the basis for this study. This configuration consists of two Fixed Geometry Variable Speed Power Turbine Engines and related drive and rotor systems (per nacelle) arranged in tilting nacelles near the wing tip. Entry-into-service (EIS) 2035 technology is assumed for both the engine and drive systems. The variable speed rotor system changes from 100 percent speed for hover to 54 percent speed for cruise by the means of a two speed gearbox concept developed under previous NASA contracts. Propulsion and drive system configurations that resulted in minimum vehicle gross weight were identified in previous work and used here. Results reported in this study illustrate that a forward shafted engine has a slight weight benefit over an aft shafted engine for the LCTR2 vehicle. Although the aft shafted engines provide a more controlled and centered CG (between hover and cruise), the length of the long rotor shaft and complicated engine exhaust arrangement outweighed the potential benefits. A Multi-Disciplinary Analysis and Optimization (MDAO) approach for transmission sizing was also explored for this study. This tool offers quick analysis of gear loads, bearing lives, efficiencies, etc., through use of commercially available RomaxDESIGNER software. The goal was to create quick methods to explore various concept models. The output results from RomaxDESIGNER have been successfully linked to Boeing spreadsheets that generate gear tooth geometry in Catia 3D environment. Another initial goal was to link information from RomaxDESIGNER (such as hp, rpm, gear ratio) to populate Boeing's parametric weight spreadsheet and create an automated method to estimate drive system weight. This was only partially achieved due to the variety of weight models, number of manual inputs, and qualitative assessments required. A simplified weight spreadsheet was used with data inputs from RomaxDESIGNER along with manual inputs to perform rough weight calculations.

Robuck, Mark↗

DOE OSTI2025

An open control sequence specification to scale building demand flexibility via analytics software

For over two decades, researchers and practitioners have showcased the ability of large commercial buildings to provide grid services by shedding or shifting load. Various utility demand response (DR) and virtual power plant (VPP) programs throughout the United States are presently utilizing these demand-side resources. However, growth of these programs have been limited, in part due to the high cost necessary to integrate the DR control strategies into the building automation system (BAS). Implementing these strategies involves adjusting control sequences, necessitating dozens of hours of customized programming per building, limiting their adoption to large organizations and progressive owners. Recent efforts by researchers and industry have demonstrated the capability of energy management and information systems (EMIS), originally designed for fault detection and diagnostics, to interface with existing BAS and perform supervisory control to optimize building operations. While these approaches are quickly being adopted by industry, demand flexibility (DF) control strategies remain limited in product offerings. One of the challenges is the lack of documented best-practice DF sequences, despite the rich literature on field implementations. This paper develops a new open-specification for a zone-based temperature adjustment shed strategy for commercial building HVAC systems, describing the specification’s implementation in two EMIS tools in both experimental and field settings. Both implementations successfully reduced electric load by at least 40% on average during the called event, while maintaining temperature limits. This study’s detailed process from specification to deployment shows the potential for scalability as well as highlights challenges related to integration with heterogeneous BAS products.

Granderson, Jessica↗

DOE OSTI2024

Towards Automated Generation of Chiplet-Based Systems

The Software Defined Architectures (SODA) Synthesizer is an open-source compiler-based tool able to automatically generate domain-specialized systems targeting Application- Specific Integrated Circuits (ASICs) or Field Programmable Gate Arrays (FPGAs) starting from high-level programming. SODA is composed of a high-level frontend, SODA-OPT, which leverages the multilevel intermediate representation (MLIR) framework to interface with productive programming tools (e.g., machine learning frameworks), identify kernels suitable for acceleration, and perform high-level optimizations, and of a state-of-the-art high-level synthesis backend, Bambu from the PandA framework, to generate custom accelerators. One specific application of the SODA Synthesizer is the generation of accelerators to enable ultra-low latency inference and control on autonomous systems for scientific discovery (e.g., electron microscopes, sensors in particle accelerators, etc.). This talk will discuss ongoing work on the SODA synthesizer to enable no-human-in-the-loop generation and design space exploration of the chiplets for highly specialized artificial intelligence accelerators. Connecting these highly specialized chiplets to general-purpose cores or programmable accelerators will allow to quickly deploy autonomous systems for scientific discovery.

Limaye, Ankur M.↗

NASA NTRS2012

NASA Space Biology Plant Research for 2010-2020

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA's Space Biology research will optimize ISS research utilization, develop and demonstrate technology and hardware that will enable new science, and contribute to the base of fundamental knowledge that will facilitate development of new tools for human space exploration and Earth applications. By taking these steps, NASA will energize the Space Biology user community and advance our knowledge of the effect of the space flight environment on living systems.

Levine, H. G.↗

NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗

DOE OSTI2023

The Integration of Wi-Fi Location-Based Services to Optimize Energy Efficient Commercial Building Operations

This project investigated and demonstrated the use of Wi-Fi Location-Based Services (LBS) to perform occupancy sensing in commercial buildings. Wi-Fi LBS can be used to detect the presence of Wi-Fi enabled mobile devices and laptops that accompany occupants as they move through the building. These signals can be used to determine occupant presence, head count, and location. When integrated with the building automation system, this emerging technology approach can be used to manage other connected systems such as lighting and HVAC to reduce energy usage in the building and improve occupant comfort. An open source location detection algorithm was developed, which uses data collected from three or more Wi-Fi access points to determine the presence and estimate the location of mobile devices and laptops. Access points can detect Wi-Fi enabled devices even if they are not connected to the existing Wi-Fi network. Building occupancy is determined based on the presence, location, and movement of these devices through the space. From lab and small-scale in-situ testing, the Location Detection Algorithm (LDA) was found to be accurate to within 10 feet and could be further refined by tuning the algorithm for the specific space characteristics such as layout and obstructions (walls, furniture, etc.). An open source method to integrate the occupancy data with existing building automations systems was investigated. The Wi-Fi occupancy sensing approach was then demonstrated and validated at commercial buildings located in Saint Paul, MN; Madison, WI; New York City; and Fort Worth, TX.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Data-based and secure switched cyber–physical systems

In this work, we develop a completely model-free moving target defense framework for the detection and mitigation of sensor and/or actuator attacks in cyber–physical systems with dynamics that evolve in discrete-time. We incorporate an intrusion detection mechanism based on an approximate dynamic programming technique that learns the policies for optimal regulation and optimal tracking while simultaneously defending against actuator and sensor attacks in a model-free fashion. Switching rules are leveraged to force proactive and reactive defense mechanisms as well as, guarantee the stability of the equilibrium point. Finally, as a case study, we apply the proposed moving target defense framework to a DC–DC converter that is used in electric vehicles.

42 ENGINEERING↗

DOE OSTI2021

The Demand-Side Opportunity: The Roles of Distributed Solar and Building Energy Systems in a Decarbonized Grid

Building energy systems represent a significant and largely untapped demand-side grid resource. Buildings use about 75% of electricity in the United States, including around 80% of peak demand, meaning that changes in building energy use have significant implications for grid operations. Building energy technologies-including energy-efficient devices, flexible loads, and energy storage-can be coordinated and aggregated to perform similar functions as centralized grid assets. Recent advances in information and communication (ICT) technologies have significantly improved building energy technology automation, coordination, and aggregation capabilities. With declining costs and technological advances, building energy systems can increasingly compete with conventional grid assets such as natural gas plants. Building energy technologies enable the deployment of distributed solar photovoltaics (DPV). Energy-efficient buildings allow DPV to meet greater shares of building load while flexible loads and energy storage can reshape building load profiles to optimize the on-site use of DPV. Optimized on-site use of DPV increases the value proposition for DPV adoption and can help utilities cost-effectively integrate higher levels of DPV penetration. Together, DPV and building energy technologies could help grids achieve deep decarbonization more quickly and cost-effectively.

14 SOLAR ENERGY↗

NASA NTRS1972

The optimal control of merging aircraft-derivation of the hybrid air traffic controller.

The Federal Aviation Administration has initiated a program to automate its existing manual air traffic handling procedures. One procedure, whose automation is expected to increase controller efficiency by 2.6 to 2.9 times, is known as aircraft merging. This procedure is concerned with the merging of N aircraft, which are distributed among K feeder routes, into one or more final routes. The question of obtaining an exactly realizable and easily implementable automatic controller for merging is discussed. The optimal control of a linear system with state and control constraints is considered.

Schatz, J. G.↗

NASA NTRS1990

A proposal to demonstrate production of salad crops in the space station mockup facility with particular attention to space, energy, and labor constraints

A desire for fresh vegetables for consumption during long term space missions has been foreseen. To meet this need in a microgravity environment within the limited space and energy available on Space Station requires highly productive vegetable cultivars of short stature to optimize vegetable production per volume available. Special water and nutrient delivery systems must also be utilized. As a first step towards fresh vegetable production in the microgravity of Space Station, several soil-less capillary action media were evaluated for the ability to support growth of two root crops (radish and carrot) which are under consideration for inclusion in a semi-automated system for production of salad vegetables in a microgravity environment (Salad Machine). In addition, productivity of different cultivars of radish was evaluated as well as the effect of planting density and cultivar on carrot production and size. Red Prince radish was more productive than Cherry Belle and grew best on Jiffy Mix Plus. During greenhouse studies, vermiculite and rock wool supported radish growth to a lesser degree than Jiffy Mix Plus but more than Cellular Rooting Sponge. Comparison of three carrot cultivars (Planet, Short n Sweet, and Goldinhart) and three planting densities revealed that Short n Sweet planted at 25.6 sq cm/plant had the greatest root fresh weight per pot, the shortest mean top length, and intermediate values of root length and top fresh weight per pot. Red Prince radish and Short n Sweet carrot showed potential as productive cultivars for use in a Salad Machine. Results of experiments with solid capillary action media were disappointing. Further research must be done to identify a solid style capillary action media which can productively support growth of root crops such as carrot and radish.

Brooks, Carolyn A.↗

NASA NTRS1994

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.

Hein, C.↗

NASA NTRS2019

Workload Considerations in Urban Air Mobility

Urban air mobility (UAM) is receiving increased attention in aviation as a system for passenger and cargo-carrying new entrants in urban airspace. In order to develop a safe and efficient system, numerous possible concepts of operation for UAM are being explored throughout industry and research domains, the features and assumptions of which may differ according to near, medium and far term operations. Much of the current research into the development of UAM has dominantly focused on technological and engineering capabilities, such as vehicle development. Although these areas of research are essential to furthering UAM, research into the role of the human operator in UAM is limited. The research described in this paper aims to begin to address this gap by investigating the capabilities and implications of human operators as traffic managers in the UAM system, focusing on near-term UAM operations. A human in the loop air traffic control simulation was used to investigate the effect of UAM traffic density, airspace routes and communication procedures on subjective workload and efficiency-related task performance. Findings indicate that medium and high-density operations were associated with high workload. A reduction in verbal communications through a letter of agreement, and optimized routes, were associated with reduced workload and increased performance efficiency. However, even with these adjustments, reported workload remained high, particularly during the high-density scenario. Future research should focus on the human operator roles and responsibilities, and the amount of involvement, in UAM system management. Particular focus should be directed on the impact of reduced human operator involvement and increased automation, on the safety and efficiency of UAM operations and the integration of UAM with traditional air traffic management.

Edwards, Tamsyn↗

DOE OSTI2026

Dynamic analysis of fully constrained Cable-Driven Parallel Robots for automated prefabricated component installation

This paper presents a dynamic analysis and validation framework to assess a fully constrained six-anchor Cable-Driven Parallel Robot (CDPR) for automated installation of prefabricated facade components. Compared with conventional eight-anchor systems, the six-anchor configuration simplifies setup and reduces cost, but it also reduces control authority, shrinks the wrench-feasible workspace, and tightens orientation limits. Consequently, it is unclear a priori whether dynamically feasible trajectories exist to move the end effector from pickup to the facade. A constrained trajectory optimization is formulated to enforce the system dynamics, cable-tension bounds, and pose/velocity limits, and the framework is evaluated in simulation at three levels: (i) an idealized reference model, (ii) a lab-scale prototype model incorporating measured anchor misalignments and identified damping, and (iii) a full-scale three-story building model with load decomposition for structural feasibility checks. Across these scenarios, the analysis shows that optimal, constraint-satisfying trajectories exist that move the end effector from pickup to installation while maintaining a near-plumb, level orientation at the final pose. Collectively, this multi-scale dynamic analysis and validation framework supports the deployment readiness of the six-anchor CDPR and provides a prototype-based sensitivity case study of how measured anchor placement deviations affect feasibility.

CDPR↗

DOE OSTI2026

Diabatization with Electrostatic Embedding for Studying Photophysics in Organic Molecular Crystals

Highly emissive organic molecular crystals find applications in several areas, such as organic electronics, solar cells, and sensors. Understanding the excited-state mechanisms underlying these applications is essential for optimizing and controlling them effectively. Exciton models coupled with nonadiabatic dynamics, particularly quantum dynamics, provide crucial insights into photochemical and photophysical processes in molecular crystals. Nevertheless, there remains a lack of general tools and automated workflows to facilitate such simulations. In this paper, we present a computational strategy to investigate the photoactivated dynamics of organic molecular crystals, bridging methodologies traditionally used for molecular systems and materials science, with a particular focus on the interplay between local excitations and charge transfer (CT) processes. We have implemented an interface between the fromage and Overdia programs, enabling the construction of vibronic Hamiltonians for molecular crystals within an excited-state ONIOM(QM:QM′) framework, incorporating long-range electrostatics through a RESP-based Ewald summation. Fragment-based diabatization provides a route to quantum dynamics simulations in weak-to-intermediate coupling regimes. The method was applied to the photophysics of dibenzo[g,p]chrysene (DBC) crystals using time-dependent DFT. The fromage/ Overdia interface was employed to compute the couplings of local excitations and CT states for 18 unique DBC dimers in the crystal and to quantify the influence of electrostatic embedding, which was found to be modest (10−20%). Simulations on π-stacked dimers reproduced the small red shift observed experimentally from solution to crystal, attributed to electronic interactions among fixed monomers rather than crystal electrostatics. Quantum dynamics simulations revealed ultrafast population transfer from bright local excitations to CT states. This approach establishes a robust framework linking molecular and solid-state excited-state dynamics, with potential applications for studying excitations, defects, and impurities in molecular crystals.

Crystals↗

DOE OSTI2020

ADETS User Manual

ADETS (Automated DEpletion Transport System) calculates coupled neutronic/isotopic results for nuclear systems and produces a large number of criticality and burnup results based on various material feed/removal specifications, power(s), and time intervals. ADETS is a fully automated tool that links the LANL MCNP Monte Carlo transport code with the SCALE system, specifically ORIGEN-ARP (radioactive decay and burnup code). Additionally, ADETS can compute the dose at various distances of the reactor using a point gamma source, whose characteristics are computed by ORIGEN-ARP. In addition, ADETS is fully coupled with the Uncertanty Quantification, Probabilistic Risk Assessment, Parameter Optimization and Data Analysis code RAVEN (developed at the Idaho National Laboratory as well). RAVEN is released with ADETS but MCNP and SCALE (ORIGEN-ARP) are not included.

42 ENGINEERING↗

DOE OSTI2024

Transmission Interconnection Roadmap: Transforming Bulk Transmission Interconnection by 2035

The U.S. electricity system is amid a rapidly occurring and widespread energy transition. Regional, Tribal, state, and customer demand for new energy resources, combined with favorable policies, is driving a rapid rise of interconnection requests. Interconnection processes will need to evolve to handle this larger number of requests today and into the future, as policy and economic drivers continue to motivate significant resource development. This roadmap identifies and organizes nearer- and longer-term solutions to enable transmission interconnection processes to meet this expected demand, and it is intended for a diverse audience of stakeholders participating within transmission interconnection processes. The roadmap is a result of the Interconnection Innovation e-Xchange (i2X) program launched by the U.S. Department of Energy (DOE) in June 2022 to convene stakeholders and address interconnection challenges. The roadmap is organized into four primary goal areas, each important to the overall i2X mission to enable a simpler, faster, and fairer interconnection of clean energy resources while enhancing the reliability, resiliency, and security of our electric grid. The first goal aims to improve interconnection data transparency, to aid interconnection customers’ ability to screen and site potential projects, better enable third-party modeling, facilitate more process automation, enhance competition while ensuring equitable outcomes, and enable benchmarking, tracking, and auditing of interconnection processes and reforms. The second goal covers solutions to improve queue management practices, affected system studies, fair processes, and workforce development. The third goal incorporates solutions that aim to improve cost allocation, reduce costs to electricity consumers, enhance the coordination between transmission planning and the interconnection process, and optimize the rightsizing of transmission investment through improvements in interconnection studies. The fourth and final goal aims to reduce the performance issues not identified during interconnection studies by updating technical requirements within interconnection studies, models, and tools while also improving industry interconnection standards.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1977

Spraylon fluorocarbon encapsulation for silicon solar cell arrays

A development program was performed for evaluating, modifying, and optimizing the Lockheed formulated liquid transparent filmforming Spraylon fluorocarbon protective coating for silicon solar cells and modules. The program objectives were designed to meet the requirements of the low-cost automated solar cell array fabrication process. As part of the study, a computer program was used to establish the limits of the safe working stress in the coated silicon solar cell array system under severe thermal shock.

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