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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 973 records · Page 54

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NASA NTRS1981

Space Shuttle - A new era in transportation

After a brief historical review of the economics of expendable-booster, commercial-payload operations to date, and a description of the Space Shuttle system's design, operational capabilities, and mission profile, the payload flight assignments, materials processing experiments, and Spacelab I material science experiment are detailed. Among the Materials Processing in Space (MPS) fields for investigation are crystal growth from vapor and solution, the production of magnetic composites and metal foams, laser host glasses and metallic glasses, non-buoyancy-driven convections, unidirectional solidification of eutectics, and the solidification of immiscible alloys. Emphasis is put on the long-term, commercial usefulness of such studies, with attention to historical precedents such as the Skylab, Apollo and Apollo-Soyuz programs.

Dunbar, B. J.↗

NASA NTRS1991

Overview presentation to SSTAC/ARTS Review Committee

An overview of the Materials and Structures Integrated Technology Plan (ITP) is presented in outline and graphic form. The base R&T funding and the Civil Space Program work breakdown structure is given. Current programs, state-of-the-art, and technology needs are described for each of several research areas including space materials, space structures and structural dynamics, aerothermal materials and structures, computational materials science and chemistry, power and propulsion materials, space environmental effects, thermal protection systems, and space debris.

Venneri, Samuel L.↗

NASA NTRS1997

Microgravity Environment Characterization Program

The Microgravity Science and Applications Division (MSAD), a division within NASA's Office of Life and Microgravity Science and Applications, sponsors a broad range of space-based research in biotechnology, combustion science, fluid physics, fundamental physics, and materials science. To better understand and exploit the orbital environment, MSAD has developed methods and hardware to characterize accelerations on microgravity experiment carriers. MSAD supports research to verify analytically derived acceleration requirements for experiments and provides vibration isolation for sensitive experiments. The Microgravity Measurement and Analysis Project (MMAP), supported by MSAD, incorporates four projects: the Space Acceleration Measurement System (SAMS), the Orbital Acceleration Research Experiment (OARE), the SAMS for International Space Station (SAMS-II), and the Principal Investigator Microgravity Services (PIMS). SAMS was developed to record microgravity accelerations and the OARE was developed to record very low-frequency microgravity accelerations on-board the NASA Orbiters. The SAMS is also used for cooperative investigations on the Russian Mir space station. The SAMS-II is being developed for the same function on-board the International Space Station (ISS). PIMS utilizes microgravity acceleration data to develop a description of each microgravity mission's acceleration environment and to support microgravity investigators in interpreting possible effects of the acceleration environment on their experiments. These elements of the MSAD program will be used to define acceleration requirements for future Orbiter and ISS payloads. This paper describes the MMAP and summarizes the products and services available to principal investigators and other users. This paper also presents some microgravity acceleration characterization results from the last six years of Orbiter microgravity missions.

DeLombard, Richard↗

NASA NTRS1998

In-Space Rapid Manufacturing

In-space manufacturing objectives are: (1) Develop and demonstrate capability to directly fabricate components in space using rapid prototyping technology - ceramics (alumina, silicon nitride, zirconia), metallics (stainless, inconel, etc.), high strength/temperature plastics (PEEK). and ABS plastics (starting point). (2) Perform material science experiments on rapid prototyping candidate materials in microgravity.

Cooper, Kenneth G.↗

NASA NTRS2001

[Activities of ICASE}

This report summarizes research conducted at ICASE in applied mathematics, computer science, fluid mechanics, and structures and material sciences during the period October 1, 2000 through March 31, 2001.

Bushnell, Dennis M.↗

NASA NTRS2002

[Activities of ICASE]

This report summarizes research conducted at ICASE in applied mathematics, computer science, fluid mechanics, and structures and material sciences during the period April 1, 2001 through September 30, 2001.

Bushnell, Dennis M.↗

NASA NTRS2003

Syntactic Metals: A Survey of Current Technology

Syntactic metals are a relatively new development in materials science. Several approaches to synthesizing these materials have been tried, and the handful of researchers in this field are beginning to make progress in defining useful compositions and processes. Syntactic metals can provide materials with dramatically improved specific strength and stiffness over their parent alloys, while retaining the isotropy that makes ordinary metals preferable to fiber-reinforced laminated composites in many applications. This paper reviews syntactic material concepts in general, the current state of the art (including the author's own work in syntactic aluminum), and the direction of future developments.

Erikson, Ray↗

NASA NTRS2000

NASA Tech Briefs, January 2000

Topics include: Data Acquisition; Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Bio-Medical; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Information Sciences; Books and reports.

Source record↗

NASA NTRS2010

Instrument for Measuring Thermal Conductivity of Materials at Low Temperatures

With the advance of polymer and other non-metallic material sciences, whole new series of polymeric materials and composites are being created. These materials are being optimized for many different applications including cryogenic and low-temperature industrial processes. Engineers need these data to perform detailed system designs and enable new design possibilities for improved control, reliability, and efficiency in specific applications. One main area of interest is cryogenic structural elements and fluid handling components and other parts, films, and coatings for low-temperature application. An important thermal property of these new materials is the apparent thermal conductivity (k-value).

Fesmire, James↗

NASA NTRS2010

Materials Development: Pitfalls, Successes, and Lessons

The incorporation of new or improved materials in aerospace systems, or indeed any systems, can yield tremendous payoffs in the system performance or cost, and in many cases can be enabling for a mission or concept. However, the availability of new materials requires advance development, and too often this is neglected or postponed, leaving a project or mission with little choice. In too many cases, the immediate reaction is to use what was used before; this usually turns out not to be possible and results in large sums of money, and amounts of time, being expended on reinvention rather than development of a material with extended capabilities. Material innovation and development is time consuming, with some common wisdom claiming that the timeline is at least 20 years. This time expands considerably when development is stopped and restarted, or knowledge is lost. Down selection of materials is necessary, especially as the Technical Readiness Level (TRL) increases. However, the costs must be considered and approaches should be taken to retain knowledge and allow for restarting the development process. Regardless of the exact time required, it is clear that it is necessary to have materials, at all stages of development, in a research and development pipeline and available for maturation as required. This talk will discuss some of theses issues, including some of the elements for a development path for materials. Some history of materials developments will be included. The usefulness of computational materials science, as a route to decreasing material development time, will be an important element of this discussion. Collaboration with outside institutions and nations is also critical for innovation, but raises the issues of intellectual property and protections, and national security (ITAR rules, for example).

Johnson, Sylvia M.↗

NASA NTRS2021

Optimal Experimental Design With Fast Neural Network Surrogate Models

Designing optimal experiments minimizes the uncertainty of results and maximizes the efficient use of resources. Herein, machine learning surrogate models and the approximate coordinate exchange (ACE) algorithm are used to determine optimum experimental designs over large or arbitrarily restrictive design spaces. Optimal experimental design is particularly salient in materials science where experiments are expensive and material properties must often be inferred indirectly. The proposed framework is demonstrated by finding optimal experiments with which the hidden constituent properties of composite materials can be most efficiently inferred from observable experimental outcomes. The optimum experimental design is given by an information-theoretic criteria, which maximizes the conditional mutual information between the hidden properties and the expected experimental outcomes. To perform tractable optimization a neural network is trained as a surrogate model to mimic a physics based simulation, which can calculate the expected experimental outcome based on a candidate experimental design and sampled constituent properties. The ACE algorithm is used to optimize over large design spaces with many tests and controlled parameters where an exhaustive search would be intractable even with the surrogate model. Using this approach, optimal experimental designs that are consistent with those produced by heuristic knowledge and established best practices are found; then optimal designs in larger design spaces where heuristic knowledge is unavailable are examined.

machine learning↗

NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

Introduction The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗

NASA NTRSDate not supplied

NASA’s Comprehensive Databases for Materials Selection (MAPTIS) and Low-Gravity Experiments (PSI)

In the realm of advancing technological change the convergence of materials science and scientific inquiry stands as a testament to humanity’s insatiable curiosity. To assist in this endeavor the National Aeronautics and Space Administration (NASA) provides curated access to two unique databases. Physical Sciences Informatics (PSI) is an online database that houses completed physical science reduced-gravity experiments. Whereas Materials and Processes Technical Information System (MAPTIS) contains several other databases that relate to aerospace materials and processes. Equipped with curated access to these databased provided by the NASA scientists and engineers are furnished with invaluable resources needed to propel technological change.

PSI↗

NASA NTRSDate not supplied

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is an open source framework for image-based simulation, primarily used to determine effective properties based on material microstructure. PuMA was originally developed for the study of NASA thermal protection materials; however, many of the solvers in PuMA have applicability to a broad range of materials science applications. PuMA version 3.2 computes material surface area, pore diameters, effective thermal conductivity, continuum and rarefied tortuosity, and permeability. For anisotropic materials, PuMA can estimate material orientation and compute anisotropic thermal conductivity and elasticity. In this talk, a brief overview of the PuMA software and underlying methods will be presented, as well as some recent and ongoing developments, including the use of immersed boundary methods for image-based simulation and the development of a new weave segmentation tool, called TomoSAM. Cut-Cell method for heat and mass transfer For simulations on complex microstructures, traditional unstructured meshing techniques often prove to be difficult and time-intensive. Voxel-based solvers, which represent the surface as a staircase structure, are relatively simple to implement but can lose accuracy when feature resolution is poor. In this work, we present a novel 3D cut-cell method for solving the variable coefficient Poisson equation on complex microstructures, suitable for the determination of effective thermal conductivity or tortuosity of a material. The method uses a Marching Cubes/Marching Squares surface reconstruction to create cut-cells and determine geometric quantities. A flux-correction method is extended to 3D, with least squares gradient reconstruction, to solve for the boundary fluxes in the cut-cells. Verification cases show the solver achieves globally 2nd order accuracy on complex microstructures. TomoSAM TomoSAM, a module of the PuMA software, has been developed as a plugin for 3D Slicer, a software platform used for 3D image processing and visualization. It utilizes the Segment Anything Model (SAM), a deep learning model capable of identifying objects and generating image masks based on minimal user input. This feature enables efficient segmentation of complex 3D datasets, particularly of woven materials, from tomography or similar imaging methods, reducing the need for manual segmentation.

Tomography↗

DOE OSTI2018

An Assessment of U.S.-Based Electron-Ion Collider Science

The Committee on U.S.-Based Electron-Ion Collider Science Assessment was asked by the Department of Energy (DOE), in its statement of task, to assess the scientific justification for a U.S. domestic electron-ion collider (EIC) facility and to evaluate the importance and urgency of the science that an EIC would address to both nuclear science and the physical sciences more broadly. The committee’s task also included assessing the role of an EIC in the global context, including its relationship to other facilities within the United States and around the world. Lastly, the committee was asked to assess the broader impacts of an EIC, including on U.S. science leadership. The full statement of task is included in Appendix A. In summary, the committee finds a compelling scientific case for such a facility. The science questions that an EIC will answer are central to completing an understanding of atoms as well as being integral to the agenda of nuclear physics today. In addition, the development of an EIC would advance accelerator science and technology in nuclear science; it would also benefit other fields of accelerator-based science and society, from medicine through materials science to elementary particle physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Finalizing Construction of a New Data Center at BNL

Computational science, data management and analysis have been key factors in the success of Brookhaven National Laboratory's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source II (NSLS-II), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, Lattice Quantum Chromodynamics (LQCD) and Materials Science, as well as our participation in international research collaborations, such as the ATLAS experiment at Europe's Large Hadron Collider (LHC) at CERN (Switzerland) and the Belle II experiment at KEK (Japan). The construction of a new data center is an acknowledgement of the increasing demand for computing and storage services at BNL in the near term and enable the Lab to address the needs of the future experiments at the High-Luminosity LHC at CERN and the Electron-Ion Collider (EIC) at BNL in the long term.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2022

Application of the Continuum Damage Mechanics Wilshire-Cano-Stewart (WCS) Model

In this study, the applications of the continuum damage mechanics-based Wilshire-Cano-Stewart (WCS) model are explored to predict rupture time, minimum-creep-strain-rate (MCSR), damage, damage evolution, and creep deformation. Increase knowledge in manufacturing methods has pushed the limit of material science and the development of new materials. Conventional testing is required to qualify materials against creep which according to the ASME B&PV III code, 10,000+ hours of experiments are necessary for each heat before materials are put into service. This process is costly and not feasible for new materials. As an alternative, models have been employed to predict creep behaviors and reduce the amount of time necessary for material qualification. Many models have been developed to predict distinct creep behaviors and the question of which model is best remains. Amongst current models, the WCS model has emerge with the ability to predict multiple behaviors using an explicit analytical approach with the ability to predict long-term creep. In this study the novel continuum damage mechanics WCS is employed in multiple applications. The goals of the study are (a) to discuss and determine the framework of the WCS model and validated it mathematically and using parametric simulations, (b) applied the model to accelerated creep data to show the capabilities of the model with non-conventional data, and (c) applied a novel numerical method, the datum temperature method (DTM) to show the model extrapolations and interpolations capabilities with limited and reduce data sets. To accomplish these goals, data is gathered for alloy P91 and Inconel 718 to develop and post-audit validate the model. The benefits of using the WCS model is that it provides an explicit stress and temperature dependency ideal for extrapolations, the coupled equations are suitable for finite element analysis (FEA) implementation, and it follows an explicit calibration approach. The model also proves that it can be applied to accelerated testing data and using the DTM.

Cano, Jaime A↗

DOE OSTI2022

Real-time 3D analysis during electron tomography using tomviz

The demand for high-throughput electron tomography is rapidly increasing in biological and material sciences. However, this 3D imaging technique is computationally bottlenecked by alignment and reconstruction which runs from hours to days. We demonstrate real-time tomography with dynamic 3D tomographic visualization to enable rapid interpretation of specimen structure immediately as data is collected on an electron microscope. Using geometrically complex chiral nanoparticles, we show volumetric interpretation can begin in less than 10 minutes and a high-quality tomogram is available within 30 minutes. Real-time tomography is integrated into tomviz, an open-source and cross-platform 3D data analysis tool that contains intuitive graphical user interfaces (GUI), to enable any scientist to characterize biological and material structure in 3D.

36 MATERIALS SCIENCE↗