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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

BIM Interoperability Tool for Improving IFC-based Model Data Exchange Between Architectural Design and Structural Analysis for Linear Piping Components

There is a growing need in the AEC industry for the digitalization of model-based data exchange in BIM workflows. However, users continue to face difficulties exchanging data between BIM-based computer-aided design (CAD) and computer-aided engineering (CAE) software, even with the open, non-proprietary data exchange format called Industry Foundation Classes (IFC). Proposed solutions in academic research focus primarily on building systems, with comparatively little attention to piping models. Therefore, this paper introduces an interoperability tool for enabling piping model data exchange between architectural and structural analysis domains. The tool is tested using a piping model created in Autodesk Revit and shows marked improvement for IFC-based CAD-to-CAE interoperability over existing practice.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Alchemy: A Model-Based Approach for 2D to 3D Autonomous Nuclear System Design

Engineering design of nuclear power plant (NPP) piping and equipment systems frequently bypasses crucial 2D system planning, instead moving straight to 3D modeling. This often leads to designs that exceed building envelope constraints, forcing expensive and time-consuming redesigns. When 2D modeling is employed, it typically involves labor-intensive manual workflows that convert 2D drawings into 3D models, resulting in inefficiencies and errors across design iterations. These workflows further suffer from poor software interoperability and dependence on proprietary software ecosystems, thereby contributing to schedule delays and cost overruns. This paper presents Alchemy, an autonomous framework that transforms 2D system definitions into Industry Foundation Classes (IFC)-compliant 3D building information models (BIMs) for expediting nuclear facility design at the conceptual preliminary phase. Using a model-based approach, the framework treats the 2D system diagram as the central reference model employed to automatically generate all subsequent outputs, ensuring consistency between the system definition and the resulting physical design. A web-based interface enables engineers to define hierarchical system topologies including associated equipment, geometric properties, and connectivity requirements. A two-phase equipment layout optimization algorithm automatically computes collision-free spatial configurations within predefined building envelopes. An artificial intelligence (AI)-assisted pipe routing module then generates orthogonal, collision-free routing paths, allowing the user to select either an A* search-based method or an Ant Colony Optimization (ACO)-based method. All outputs are authored natively in IFC format, relying on open-source technologies and standardized formats in order to ensure extensibility and eliminate proprietary software dependencies. The proposed framework is validated on two representative pressurized-water reactor (PWR)-based case studies, for which it autonomously generates IFC-compliant 3D models in minutes, drastically reducing workflows that typically require hours of manual effort. The generated model demonstrates topologically correct equipment placement, physically plausible spatial relationships, and collision-free pipe routing consistent with known PWR loop configurations. This work represents a foundational step toward digital engineering for nuclear facility preliminary design, with future ongoing development targeting design code compliance and expanded system complexity.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Interoperability format translation and transformation between IFC architectural design file and simulation file formats

Automatically translating a building architecture file format (Industry Foundation Class) to a simulation file, in one aspect, may extract data and metadata used by a target simulation tool from a building architecture file. Interoperability data objects may be created and the extracted data is stored in the interoperability data objects. A model translation procedure may be prepared to identify a mapping from a Model View Definition to a translation and transformation function. The extracted data may be transformed using the data stored in the interoperability data objects, an input Model View Definition template, and the translation and transformation function to convert the extracted data to correct geometric values needed for a target simulation file format used by the target simulation tool. The simulation file in the target simulation file format may be generated.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2015

Interoperability format translation and transformation between IFC architectural design file and simulation file formats

Automatically translating a building architecture file format (Industry Foundation Class) to a simulation file, in one aspect, may extract data and metadata used by a target simulation tool from a building architecture file. Interoperability data objects may be created and the extracted data is stored in the interoperability data objects. A model translation procedure may be prepared to identify a mapping from a Model View Definition to a translation and transformation function. The extracted data may be transformed using the data stored in the interoperability data objects, an input Model View Definition template, and the translation and transformation function to convert the extracted data to correct geometric values needed for a target simulation file format used by the target simulation tool. The simulation file in the target simulation file format may be generated.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High Voltage Regrown GaN P-N Diodes Enabled by Defect and Doping Control

This project studied and implemented methods to form GaN p-n diodes using selective area regrowth to achieve selective area doping. Successful selective area doping of GaN p-n diodes is an enabling factor to realize more advanced devices such as vertical transistors. The general challenge to selective area regrowth of GaN is that the primary etch method, inductively coupled plasma (ICP), damages the crystal and causes high leakage when didoes are formed by regrowth on the etched surface. Our approach used low damage etch methods following ICP etch to remove crystal damage and reduced leakage in the regrown diode. This project demonstrated 1.6 kV etched-and-regrown GaN p-n diodes using planar (non-selective) regrowth and 840 V etched-and-regrown p-n diodes using selective area regrown. Enabling factors were use of a low-damage reactive ion etch (RIE) to remove damage caused by the primary ICP etch combined with a multi-step junction terminal extension (JTE) process. Deep level defect investigation quantitatively correlated a deep level near the middle of the GaN band gap with ICP etch-induced leakage that was greatly mitigated by using a slow, low damage RIE process. This research is economically feasible for commercialization because the processes used in this project, including substrate type and source, epitaxial crystal growth and fabrication techniques are all standard to the GaN semiconductor industry. The fundamental understanding and foundational ability to produce kV-class GaN p-n diodes through etch-and-regrowth provides a path to realize high power, high efficiency GaN power switches that can significantly outperform commercial devices for next-generation electrical power conversion and transmission systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Evaluation of pre-training large language models on leadership-class supercomputers

Large language models (LLMs) have arisen rapidly to the center stage of artificial intelligence as the foundation models applicable to many downstream learning tasks. However, how to effectively build, train, and serve such models for many high-stake and first-principle-based scientific use cases are both of great interests and of great challenges. Moreover, pre-training LLMs with billions or even trillions of parameters can be prohibitively expensive not just for academic institutions, but also for well-funded industrial and government labs. Furthermore, the energy cost and the environmental impact of developing LLMs must be kept in mind. Here, in this work, we conduct a first-of-its-kind performance analysis to understand the time and energy cost of pre-training LLMs on the Department of Energy (DOE)’s leadership-class supercomputers. Employing state-of-the-art distributed training techniques, we evaluate the computational performance of various parallelization approaches at scale for a range of model sizes, and establish a projection model for the cost of full training. Our findings provide baseline results, best practices, and heuristics for pre-training such large models that should be valuable to HPC community at large. We also offer insights and optimization strategies for using the first exascale computing system, Frontier, to train models of the size of GPT-3 and beyond.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

Mechanical Response of Elastomers to Magnetic Fields

Elastomeric materials represent an important class of engineering materials, which are widely used to make components of structures, machinery, and devices for vibration and noise control. Elastomeric material possessing conductive or magnetic properties have been widely used in applications such as conductive and magnetic tapes, sensors, flexible permanent magnets, etc. Our interest in these materials has focussed on understanding and controlling the magnitude and directionality of their response to applied magnetic fields. The effect of magnetic fields on the mechanical properties of these materials has not been the subject of many published studies. Our interest and expertise in controllable fluids have given us the foundation to make a transition to controllable elastomers. Controllable elastomers are materials that exhibit a change in mechanical properties upon application of an external stimuli, in this case a magnetic field. Controllable elastomers promise to have more functionality than conventional elastomers and therefore could share the broad industrial application base with conventional elastomers. As such, these materials represent an attractive class of smart materials, and may well be a link that brings the applications of modern control technologies, intelligent structures and smart materials to a very broad industrial area. This presentation will cover our research work in the area of controllable elastomers at the Thomas Lord Research Center. More specifically, the presentation will discuss the control of mechanical properties and mathematical modeling of the new materials prepared in our laboratories along with experiments to achieve adaptive vibration control using the new materials.

Munoz, B. C.↗
NASA NTRS1973

Environmental study of ERTS-1 imagery: Lake Champlain and Vermont

Environmental concerns of the State of Vermont currently being stressed include water quality in Lake Champlain and a state-wide land use and capability plan. Significant results obtained from ERTS-1 relate directly to the above concerns. Industrial water pollution and turbidity in Lake Champlain have been identified and mapped and the ERTS pollution data will be used in the developing court suit which Vermont has initiated against the polluters. ERTS imagery has also provided a foundation for updating and revising land use inventories. Major classes of land use have been identified and mapped, and substantial progress has been made toward the mapping of such land use divisions as crop and forest type, and wetlands.

Lind, A. O.↗
NASA NTRS1998

On the Wing: A Business-Class Jet

Cessna Aircraft Company was last featured in Spinoff 1991 for the Citation Jet, the industry's current best selling business jet. The newest addition to its fleet is the Citation X (ten), the largest, most complex aircraft ever produced by Cessna, which also has its basis in NASA technology. Aerodynamic design, wind tunneling testing, and airfoil performance, for example, have their foundation with NASA. The Citation X is the fastest, most efficient business jet ever built.

Source record↗
NASA NTRS1995

NASA Noise Reduction Program for Advanced Subsonic Transports

Aircraft noise is an important byproduct of the world's air transportation system. Because of growing public interest and sensitivity to noise, noise reduction technology is becoming increasingly important to the unconstrained growth and utilization of the air transportation system. Unless noise technology keeps pace with public demands, noise restrictions at the international, national and/or local levels may unduly constrain the growth and capacity of the system to serve the public. In recognition of the importance of noise technology to the future of air transportation as well as the viability and competitiveness of the aircraft that operate within the system, NASA, the FAA and the industry have developed noise reduction technology programs having application to virtually all classes of subsonic and supersonic aircraft envisioned to operate far into the 21st century. The purpose of this paper is to describe the scope and focus of the Advanced Subsonic Technology Noise Reduction program with emphasis on the advanced technologies that form the foundation of the program.

Stephens, David G.↗
DOE OSTI2016

Hybrid Ultra‐Microporous Materials for Selective Xenon Adsorption and Separation

Abstract The demand for Xe/Kr separation continues to grow due to the industrial significance of high‐purity Xe gas. Current separation processes rely on energy intensive cryogenic distillation. Therefore, less energy intensive alternatives, such as physisorptive separation, using porous materials, are required. Herein we show that an underexplored class of porous materials called hybrid ultra‐microporous materials (HUMs) affords new benchmark selectivity for Xe separation from Xe/Kr mixtures. The isostructural materials, CROFOUR‐1‐Ni and CROFOUR‐2‐Ni, are coordination networks that have coordinatively saturated metal centers and two distinct types of micropores, one of which is lined by CrO 4 2− (CROFOUR) anions and the other is decorated by the functionalized organic linker. These nets offer unprecedented selectivity towards Xe. Modelling indicates that the selectivity of these nets is tailored by synergy between the pore size and the strong electrostatics afforded by the CrO 4 2− anions.

Mohamed, Mona H.↗
DOE OSTI2023

Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops

Over the past decade, fundamental changes in artificial intelligence (AI)—from foundational to applied—have delivered dramatic insights across a wide breadth of U.S. Department of Energy (DOE) mission space. AI is helping to augment and improve scientific and engineering workflows (e.g., for control, design, and dramatic performance gains through surrogate models) in national security, the Office of Science, and DOE’s applied energy programs. The progress and potential for AI in DOE science was captured in the 2020 “AI for Science” report from the DOE laboratory community in collaboration with academia and industry. Specific scientific areas ready to further leverage the power of AI ranged from the scale and performance of computational models to data analysis to creating new classes of observations using computer vision. Since that report, the scale and scope of scientific AI have accelerated, revealing new, emergent properties that yield insights that go beyond enabling opportunities to being potentially transformative in the way that scientific problems are posed and solved. Thus, under the guidance of both the Office of Science (SC) and the National Nuclear Security Administration (NNSA), the DOE national laboratories organized a series of workshops in 2022 to gather input on new and rapidly emerging opportunities and challenges of scientific AI. This 2023 report is a synthesis of those workshops. The scientific community believes AI can have a foundational impact on a broad range of DOE missions, including science, energy, and national security. Further, DOE has unique capabilities that enable the community to drive progress in scientific use of AI, building on long-standing DOE strengths and investments in computation, data, and communications infrastructure, spanning the Energy Sciences Network (ESnet), the Exascale Computing Project (ECP), and integrative programs such as the NNSA Office of Defense Programs Advanced Simulation and Computing (ASC) and the SC Scientific Discovery through Advanced Computing (SciDAC) programs.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2015

Affordable Development and Demonstration of a Small NTR Engine and Stage: A Preliminary NASA, DOE, and Industry Assessment

In FY11, NASA formulated a plan for Nuclear Thermal Propulsion (NTP) development that included Foundational Technology Development followed by system-level Technology Demonstrations. The ongoing NTP project, funded by NASA's Advanced Exploration Systems (AES) program, is focused on Foundational Technology Development and includes 5 key task activities: (1) Fuel element fabrication and non-nuclear validation testing of heritage fuel options; (2) Engine conceptual design; (3) Mission analysis and engine requirements definition; (4) Identification of affordable options for ground testing; and (5) Formulation of an affordable and sustainable NTP development program. Performance parameters for Point of Departure designs for a small criticality-limited and full size 25 klb (sub f) (kip, or 1000 pound-force)-class engine were developed during FYs 13-14 using heritage fuel element designs for both Rover NERVA (Nuclear Engine for Rocket Vehicle Applications) Graphite Composite (GC) and Ceramic Metal (Cermet) fuel forms. To focus the fuel development effort and maximize use of its resources, the AES program decided, in FY14, that a leader-follower down-selection between GC and cermet fuel was required. An Independent Review Panel (IRP) was convened by NASA and tasked with reviewing the available fuel data and making a recommendation to NASA. In February 2015, the IRP recommended and the AES program endorsed GC as the leader fuel In FY14, a preliminary development schedule DDTE (Design Development Test and Evaluation) plan was produced by GRC (Glenn Research Center), DOE (Department of Energy) and industry for the AES program. Assumptions, considerations and key task activities are presented here. At the direction of NASA HQ (32515), NASA and DOE are to work together to formulate a detailed development plan and schedule allowing the affordable development of a small (7.5-16.5 klbf) GC engine for possible flight technology demonstration (FTD) mission within a 10-year timeframe.

Lunar Flyby Mission↗
NASA NTRS2003

NASA's National Center for Advanced Manufacturing

NASA has designated the Principal Center Assignment to the Marshall Space Flight Center (MSFC) for implementation of the National Center for Advanced Manufacturing (NCAM). NCAM is NASA s leading resource for the aerospace manufacturing research, development, and innovation needs that are critical to the goals of the Agency. Through this initiative NCAM s people work together with government, industry, and academia to ensure the technology base and national infrastructure are available to develop innovative manufacturing technologies with broad application to NASA Enterprise programs, and U.S. industry. Educational enhancements are ever-present within the NCAM focus to promote research, to inspire participation and to support education and training in manufacturing. Many important accomplishments took place during 2002. Through NCAM, NASA was among five federal agencies involved in manufacturing research and development (R&D) to launch a major effort to exchange information and cooperate directly to enhance the payoffs from federal investments. The Government Agencies Technology Exchange in Manufacturing (GATE-M) is the only active effort to specifically and comprehensively address manufacturing R&D across the federal government. Participating agencies include the departments of Commerce (represented by the National Institute of Standards and Technology), Defense, and Energy, as well as the National Science Foundation and NASA. MSFC s ongoing partnership with the State of Louisiana, the University of New Orleans, and Lockheed Martin Corporation at the Michoud Assembly Facility (MAF) progressed significantly. Major capital investments were initiated for world-class equipment additions including a universal friction stir welding system, composite fiber placement machine, five-axis machining center, and ten-axis laser ultrasonic nondestructive test system. The NCAM consortium of five universities led by University of New Orleans with Mississippi State University, Tennessee Technological University, Texas A&M University, and Virginia Polytechnic Institute and State University provided wide-ranging engineering research, new degree/curriculum programs, and a web-based lecture series. NCAM has fostered an important presence and leadership role within the national manufacturing community. Its progressive influence can be seen in government, industry and academia, and in national associations, professional organizations, conferences, workshops, and forums.

Vickers, John↗
NASA NTRS2022

UAM Research – X4: Introduction to Community Based Rules (CBRs)

Recent advances in technology have enabled industry development of new and innovative vehicle types, offering lower operating costs and highly automated functionality that facilitates the introduction of new types of operations. These include low-altitude airspace operations with small Unmanned Aircraft Systems (UASs), short distance urban and intercity operations, and high- altitude Upper Class E operations. These and other new operations are expected to result in a much higher operational tempo than is currently experienced across the National Airspace System (NAS). The projected increase in operations, as well as the introduction of new aircraft form factors and supporting technologies—including increasing autonomy—will present challenges to the existing Air Traffic Management (ATM) system, which is currently unable to cost-effectively scale and deliver needed services. In response to these challenges and opportunities, a highly automated, cooperative environment incorporating a federated network has been envisioned and described through multiple operational concepts, depicting the future operating environment as part of the NAS. Foundational to the success of this future operating environment is the establishment of common business rules and understandings across relevant stakeholders, referred to as Community Based Rules (CBRs). Development, adoption, and implementation of CBRs will require collaboration across multiple stakeholders, including operators, support services (industry), and the Federal Aviation Administration (FAA), to identify and resolve a broad range of questions and challenges. Examples of these questions include “what rules are needed?”, “how are they expressed?”, and “how will they be managed?” This document identifies and describes an initial set of questions and considerations to be examined as efforts begin to create the innovative, automated, cooperative operating environment of the future. The goal is to establish a common frame of reference to support discussions and decisions regarding the future implementation of CBRs as part of the NAS.

Community Based Rules↗
DOE OSTI2019

The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution

This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully--coupled physical model designed to address DOE mission-relevant water cycle questions. Its components include atmosphere and land (110km grid spacing), ocean and sea ice (60km in the mid-latitudes and 30km at the equator and poles), and river transport (55km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 Diagnosis, Evaluation, and Characterization of Klima (CMIP6 DECK) simulations consisting of a long pre-industrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO 2 forcing simulations. The model performs well overall with biases typical of other CMIP-class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP-class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between pre-industrial (1850) and present-day, the trajectory of the warming diverges from observations in the second half of the 20th century with a period of delayed warming followed by an excessive warming trend. Using a two-layer energy balance model, we attribute this divergence to the model's strong aerosol-related effective radiative forcing (ERF ari+aci = -1.65 W m -2 ) and high equilibrium climate sensitivity (ECS = 5.3 K).

58 GEOSCIENCES↗
DOE OSTI2022

Networks and interfaces as catalysts for polymer materials innovation

Autonomous experimental systems offer a compelling glimpse into a future where closed-loop, iterative cycles—performed by machines and guided by artificial intelligence (AI) and machine learning (ML)—play a foundational role in materials research and development. This perspective draws attention to the roles of networks and interfaces—of and between humans and machines—for the purpose of generating knowledge and accelerating innovation. Polymers, a class of materials with massive global impact, present a unique opportunity for the application of informatics and automation to pressing societal challenges. To develop these networks and interfaces in polymer science, the Community Resource for Innovation in Polymer Technology (CRIPT)—a polymer data ecosystem based on novel polymer data model, representation, search, and visualization technologies—is introduced. The ongoing co-design efforts engage stakeholders in industry, academia, and government to uncover rapidly actionable, high-impact opportunities to build networks, bridge interfaces, and catalyze innovation in polymer technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗