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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

DAWN (Design Assistant Workstation) for advanced physical-chemical life support systems

This paper reports the results of a project supported by the National Aeronautics and Space Administration, Office of Aeronautics and Space Technology (NASA-OAST) under the Advanced Life Support Development Program. It is an initial attempt to integrate artificial intelligence techniques (via expert systems) with conventional quantitative modeling tools for advanced physical-chemical life support systems. The addition of artificial intelligence techniques will assist the designer in the definition and simulation of loosely/well-defined life support processes/problems as well as assist in the capture of design knowledge, both quantitative and qualitative. Expert system and conventional modeling tools are integrated to provide a design workstation that assists the engineer/scientist in creating, evaluating, documenting and optimizing physical-chemical life support systems for short-term and extended duration missions.

Rudokas, Mary R.↗

MADA: Multi-Agent Design Assistant

MADA (Multi-Agent Design Assistant) is a Large Language Model (LLM) powered multi-agent framework that coordinates specialized agents for complex design workflows. The system was designed for HPC workflows with the following agents in mind: 1) A Job Management Agent (JMA) launches and manages ensemble simulations on HPC systems, 2) a Geometry Agent (GA) generates meshes, and 3) an Inverse Design Agent (IDA) proposes new designs informed by simulation outcomes. Our framework reduces cumbersome manual workflow setup, and enables automated design exploration at scale. However, the software also enables users to rapidly create new multi-agent systems. Simply define new agents in a configuration file, giving each their own set of tools (via MCP), and then chat and prompt your new multi-agent system. Is

Gunnarson, BrianS [Lawrence Livermore National Lab↗

AI Design Assistant

SAND2025-01930O The AI Design Assistant uses ChatGPT to provide a natural language interface to airfoil analysis tools (XFOIL). Most of the code base is glue code, connecting XFOIL (a tool for analyzing airfoils) to the OpenAI interface. Among the more novel features are an airfoil geometry class and methods on how to extract detailed data from XFOIL. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Karcher, Cody↗

Machine learning-assisted design of metal–organic frameworks for hydrogen storage: A high-throughput screening and experimental approach

Various theoretical approaches, including big data and high-throughput screening techniques, have been explored in developing new materials due to their significant potential time-saving advantages. However, it remains a significant challenge to experimentally realize new materials that are predicted. In this study, we propose a novel materials design strategy that utilizes machine-learning (ML) techniques to predict new porous materials that show promise for hydrogen storage and are likely to be feasible to synthesize. By leveraging ML techniques and metal–organic framework (MOF) databases, we are able to predict the synthesizability of MOF structures. This is evidenced by the successful synthesis of a new vanadium-based MOF that exhibits excellent performance for cryogenic H 2 storage. Notably, the total gravimetric and volumetric H 2 uptakes are as high as 9.0 wt% and 50.0 g/L at 77 K and 150 bar. This ML-assisted materials design offers an efficient and promising approach for developing hydrogen storage materials.

08 HYDROGEN↗

Aviation System Analysis Capability Executive Assistant Design

In this technical document, we describe the design developed for the Aviation System Analysis Capability (ASAC) Executive Assistant (EA) Proof of Concept (POC). We describe the genesis and role of the ASAC system, discuss the objectives of the ASAC system and provide an overview of components and models within the ASAC system, and describe the design process and the results of the ASAC EA POC system design. We also describe the evaluation process and results for applicable COTS software. The document has six chapters, a bibliography, three appendices and one attachment.

Roberts, Eileen↗

Computer-assisted design in perceptual-motor skills research

A categorization was made of independent variables previously found to be potent in simple perceptual-motor tasks. A computer was then used to generate hypothetical factorial designs. These were evaluated in terms of literature trends and pragmatic criteria. Potential side-effects of machine-assisted research strategy were discussed.

Rogers, C. A., Jr.↗

Computationally Assisted Design of Ion-conducting Polymers for Anion Exchange Membrane Fuel Cells (2nd Year Report) [Slides]

Phosphonated polymers have been proposed as proton conductors for fuel cells; however, the anhydride formation of phosphonic acid functional groups lowers proton conductivity and hinders their use in fuel cell applications. We used calculations to support this hypothesis by correlating calculated Gibbs free energies for the formation of the anhydride with pK values of the corresponding acid. The results showed that stronger acids are less likely to form an anhydride even at elevated temperatures and supported the design of a new polymer and the high-temperature proton exchange membrane fuel cell (HT-PEMFC) that outperformed other state-of-the-art HT-PEMFCs.

30 DIRECT ENERGY CONVERSION↗

Microgrid Assisted Design for Remote Areas

In this work, we present a three-stage multiobjective mixed-integer linear programming (MILP) for the optimal expansion planning and operation of isolated multienergy microgrids in remote areas. By selecting the optimal distributed generators (DGs) and energy storage systems (ESSs) mix selection, siting, sizing, and scheduling in the remote microgrid, the proposed model is targeted to minimize the annualized total cost of microgrids while enhancing the performance of the system, i.e., minimizing the voltage deviations and line power loss. To represent the electricity and heat flow between generation resources and various electrical, heating, and cooling loads in the isolated microgrid, linearized power flow, and heat flow constraints are employed in the proposed optimization model. The available capacity of DGs and ESSs are modeled as discrete constants instead of continuous variables for practical purpose. Numerical simulation results on a remote microgrid consisting of DGs, ESSs, and various loads validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Computer-assisted design of organic synthesis

The computer programs to design synthetic pathways of organic compounds have been utilized throughout the world since the first system was reported by Corey in 1969, and the LHASA was reported in1972 to become the predominant system. Many programs have been reported mainly in the United States and Europe, and groups of corporations, especially chemical companies, have been trying to improve programs and increase the efficiency of research. In Japan, unfortunately, no concrete movement in this area has been seen. Of course, it goes without saying that these kinds of programs are effective for efficient research, but the remarkable aspect is that these can present unexpected data to the researchers to stimulate them to develop new ideas.

Kaminaka, H.↗

Program Assists Design Of Cabling

DFACS is interactive, multiuser, computer-aided-engineering software tool for system-level electrical-integration and cabling engineering. Purpose to provide engineering community with centralized data base for entering and gaining access to definitions of functions of systems, details of pin connections to circuits at subsystem and instrument ends and data on harnessing of cables. Primary objective provides instantaneous single point of interchange of information, avoiding error-prone, time-consuming, and costly multiple-path shuttling of data.

Billitti, Joseph W.↗

Halau Uma: Kahikinui Community Cultural, Educational, and Resilience Center Preliminary Design Technical Assistance Summary Report

The Kahikinui Homestead Community in Maui faces energy resilience challenges due to its remote, off-grid location. This report summarizes preliminary technical assistance to design a microgrid for six modular homes using solar PV, wind, and battery storage. Results indicate that a hybrid PV and battery system, supplemented by small wind turbines, offers a cost-effective, resilient solution supporting energy independence and disaster preparedness.

Quiroz, Jimmy Edward [Sandia National Laboratories↗

Kauhale 'O Kipapa: Kahikinui Community Cultural, Educational, and Resilience Center Preliminary Design Technical Assistance Summary Report

The Kahikinui Homestead Community in Maui faces energy resilience challenges due to its remote, off-grid location. This report summarizes preliminary technical assistance to design a microgrid for six modular homes using solar PV, wind, and battery storage. Findings show hybrid PV and battery systems, supplemented by small wind turbines, offer cost-effective, resilient solutions. This work supports enhanced energy independence and disaster preparedness for the community.

Quiroz, Jimmy Edward [Sandia National Laboratories↗

Automated Assistance for Designing Active Magnetic Bearings

MagBear12 is a computer code that assists in the design of radial, heteropolar active magnetic bearings (AMBs). MagBear12 was developed to help in designing the system described in "Advanced Active-Magnetic-Bearing Thrust-Measurement System". Beyond this initial application, MagBear12 is expected to be useful for designing AMBs for a variety of rotating machinery. This program incorporates design rules and governing equations that are also implemented in other, proprietary design software used by AMB manufacturers. In addition, this program incorporates an advanced unpublished fringing-magnetic-field model that increases accuracy beyond that offered by the other AMB-design software.

Imlach, Joseph↗

AI-assisted detector design for the EIC (AID(2)E)

Artificial Intelligence is poised to transform the design of complex, large-scale detectors like ePIC at the future Electron Ion Collider. Featuring a central detector with additional detecting systems in the far forward and far backward regions, the ePIC experiment incorporates numerous design parameters and objectives, including performance, physics reach, and cost, constrained by mechanical and geometric limits. This project aims to develop a scalable, distributed AI-assisted detector design for the EIC (AID(2)E), employing state-of-the-art multiobjective optimization to tackle complex designs. Supported by the ePIC software stack and using G EANT 4 simulations, our approach benefits from transparent parameterization and advanced AI features. The workflow leverages the PanDA and iDDS systems, used in major experiments such as ATLAS at CERN LHC, the Rubin Observatory, and sPHENIX at RHIC, to manage the compute intensive demands of ePIC detector simulations. Tailored enhancements to the PanDA system focus on usability, scalability, automation, and monitoring. Ultimately, this project aims to establish a robust design capability, apply a distributed AI-assisted workflow to the ePIC detector, and extend its applications to the design of the second detector (Detector-2) in the EIC, as well as to calibration and alignment tasks. Additionally, we are developing advanced data science tools to efficiently navigate the complex, multidimensional trade-offs identified through this optimization process.

97 MATHEMATICS AND COMPUTING↗

Program Assists Satellite Designers

Annapolis, Maryland-based designAmerica Inc., a small aerospace company specializing in the development and delivery of ground control systems for satellites and instrumentation, assisted Goddard Space Flight Center in the development of the ASIST software, a real-time command and control system for spacecraft development, integration, and operations. It was designed to be fully functional across a broad spectrum of satellites and instrumentation, while also being user friendly. The company now has rights to commercial use of the program and is offering it to government and industry satellite designers.

Source record↗

Rapid data acquisition and machine learning-assisted composition design of functionally graded alloys via wire arc additive manufacturing

Abstract The lack of high-quality datasets in materials science hinders artificial intelligence (AI)-driven alloy design. To address this challenge, wire arc additive manufacturing (WAAM) was employed to fabricate graded alloys, generating extensive data for machine learning (ML)-assisted property prediction. ML models were developed using high-throughput experiments, computational models, and genetic algorithm to optimize feature selection, successfully predicting hardness and porosity. The ML model demonstrated its efficacy by designing a gradient alloy with enhanced properties. However, scaling up revealed uncertainties in tensile property and porosity due to differences in size and thermal conditions between the designed alloy build and the gradient print used to construct the ML model. This underscores the need for uncertainty quantification and process optimization in WAAM-driven alloy design. Our work advances AI-integrated additive manufacturing, offering a rapid approach to exploring process–structure–property relationships and accelerating materials development.

Wang, Xin↗