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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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This paper describes the work being performed under the auspices of the HPCC/ESS Grand Challenge Applications and Enabling Scaleable Computing Testbed applied to advancing computing technology to SAR interferometry and imaging science.
Coupled thermo-hydro-mechanical (THM) processes in fractured rock are playing a crucial role in geoscience and geoengineering applications. Diverse and conceptually distinct approaches have emerged over the past decades in both continuum and discontinuum perspectives leading to significant progress in their comprehending and modeling. This review paper offers an integrated perspective on existing modeling methodologies providing guidance for model selection based on the initial and boundary conditions. By comparing various models, one can better assess the uncertainties in predictions, particularly those related to the conceptual models. The review explores how these methodologies have significantly enhanced the fundamental understanding of how fractures respond to fluid injection and production, and improved predictive capabilities pertaining to coupled processes within fractured systems. It emphasizes the importance of utilizing advanced computational technologies and thoroughly considering fundamental theories and principles established through past experimental evidence and practical experience. The selection and calibration of model parameters should be based on typical ranges and applied to the specific conditions of applications. The challenges arising from inherent heterogeneity and uncertainties, nonlinear THM coupled processes, scale dependence, and computational limitations in representing field scale fractures are discussed. Realizing potential advances on computational capacity calls for methodical conceptualization, mathematical modeling, selection of numerical solution strategies, implementation, and calibration to foster simulation outcomes that intricately reflect the nuanced complexities of geological phenomena. Future research efforts should focus on innovative approaches to tackle the hurdles and advance the state-of-the-art in this critical field of study.
Recent advances in computer technology that are likely to impact finite element computations are reviewed. The characteristics of supersystems, highly parallel systems, and small systems (mini and microcomputers) are summarized. The interrelations of numerical algorithms and software with parallel architectures are discussed. A scenario is presented for future hardware/software environment and finite element systems. A number of research areas which have high potential for improving the effectiveness of finite element analysis in the new environment are identified.
Thanks to the advancements in high-performance computing, advanced modeling and simulation have become crucial in driving the development and deployment of next-generation nuclear reactors, such as small modular reactors (SMRs). SMRs offer the promise of cost-effective baseload electricity production and improved safety, while addressing some of the challenges associated with large reactor designs, such as high capital costs and extended construction timelines. As part of the Exascale Computing Project, the large-scale multiphysics simulation of an entire SMR primary system has been achieved by combining computational fluid dynamics and neutronics. In addition to the successful demonstration of full-core SMR simulations, the current study integrated the impact of natural circulation into the system. Natural circulation is the primary mechanism driving coolant circulation in SMRs. The mass flow rate in the core depends on the core power, and a numerical model has been developed to predict it. The pressure drop caused by the helical coil steam generator was also accounted for by developing a pressure drop correlation based on high-fidelity large eddy simulation results, further improving prediction accuracy. In conclusion, the results of the study demonstrate that the implemented natural circulation model is effective in predicting the responses of SMR full-core multiphysics simulations.
In 1993 we proposed a project to NASA having the goal of producing a new infrared map of our Galaxy. In particular, we proposed to reprocess the IRAS data taken in the early 1980's using modern image processing algorithms and the large Intel parallel computers of the Center for Advanced Computing Research, (at that time called the Caltech Concurrent Supercomputing Facilities - CCSF). The rationale was simple: what took approximately 100 days on a typical workstation would take less than a day on the multi-processor parallel computers, thus making a high-resolution infrared atlas of the Galaxy feasible.
The wide spectrum of needs and applications are demonstrated of computational structural mechanics. The spectrum ranges from micro structural mechanics to the optimization of the performance of aerovehicles. Critical high leveraged technologies will require engineering process modernization and automation, affordable structures and materials, and advanced computational technology. Recent advances at Rockwell International in computational structural mechanics addressed these issues and improve the ability to achieve advanced aircraft objectives.
The Internal Fluid Mechanics Division of the NASA Lewis Research Center is combining the key elements of computational fluid dynamics, aerothermodynamic experiments, and advanced computational technology to bring internal computational fluid mechanics (ICFM) to a state of practical application for aerospace propulsion systems. The strategies used to achieve this goal are to: (1) pursue an understanding of flow physics, surface heat transfer, and combustion via analysis and fundamental experiments, (2) incorporate improved understanding of these phenomena into verified 3-D CFD codes, and (3) utilize state-of-the-art computational technology to enhance experimental and CFD research. Presented is an overview of the ICFM program in high-speed propulsion, including work in inlets, turbomachinery, and chemical reacting flows. Ongoing efforts to integrate new computer technologies, such as parallel computing and artificial intelligence, into high-speed aeropropulsion research are described.
The complexity and interdependence of software on a computer system can create a situation where a solution to one problem causes failures in dependent software. In the computer industry, software problems arise and are often solved with 'quick and dirty' solutions. But in implementing these solutions, documentation about the solution or user notification of changes is often overlooked, and new problems are frequently introduced because of insufficient review or testing. These problems increase when numerous heterogeneous systems are involved. Because of this situation, a change management system plays an integral part in the maintenance of any multisystem computing environment. At the NASA Ames Advanced Computational Facility (ACF), the Online Change Management System (OCMS) was designed and developed to manage the changes being applied to its multivendor computing environment. This paper documents the research, design, and modifications that went into the development of this change management system (CMS).
Advancements in hardware and software technology are summarized with specific emphasis on spacecraft computer capabilities. Available state of the art technology is reviewed and candidate architectures are defined.
The Low Profile Diffuser (LPD) project originated as an award from the Marshall Space Flight Center (MSFC) Advanced Development (ADO) office to the Main Propulsion Systems Branch (ER22). The task was created to develop and test an LPD concept that could produce comparable performance to a larger, traditionally designed, ullage gas diffuser while occupying a smaller volume envelope. Historically, ullage gas diffusers have been large, bulky devices that occupy a significant portion of the propellant tank, decreasing the tank volume available for propellant. Ullage pressurization of spacecraft propellant tanks is required to prevent boil-off of cryogenic propellants and to provide a positive pressure for propellant extraction. To achieve this, ullage gas diffusers must slow hot, high-pressure gas entering a propellant tank from supersonic speeds to only a few meters per second. Decreasing the incoming gas velocity is typically accomplished through expansion to larger areas within the diffuser which has traditionally led to large diffuser lengths. The Fluid Dynamics Branch (ER42) developed and applied advanced Computational Fluid Dynamics (CFD) analysis methods in order to mature the LPD design from and initial concept to an optimized test prototype and to provide extremely accurate pre-test predictions of diffuser performance. Additionally, the diffuser concept for the Core Stage of the Space Launch System (SLS) was analyzed in a short amount of time to guide test data collection efforts of the qualification of the device. CFD analysis of the SLS diffuser design provided new insights into the functioning of the device and was qualitatively validated against hot wire anemometry of the exterior flow field. Rigorous data analysis of the measurements was performed on static and dynamic pressure data, data from two microphones, accelerometers and hot wire anemometry with automated traverse. Feasibility of the LPD concept and validation of the computational model were demonstrated by the test data.
Present research centers on the development of advanced computational methods for transient simulation analyses. Aircraft, launch vehicles and space structure components are potential applications, but primary focus is presently on large space structures. There are both in-house and out-of-house activities. The in-house activity centers around the development of a multibody simulation tool for truss-like structures called LATDYN for Large Angle Transient DYNamics. Multibody analysis involves articulation of structural components as well as robotic maneuvers. These items are necessary for construction (erection or deployment) of large space structures in orbit and the carrying out of certain operations on board the space station. Thus, part of the in-house activity involves the development of methods which treat the changing mass, stiffness and constraints associated with articulating systems. The out-of-house activity involves subcycling, development of large deformation/motion beam formulation, constraint stabilization and direct time integration transient algorithms in parallel computing.
Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advanced computational fluid dynamics codes, which can be computationally expensive on mainframe supercomputers. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computing environment utilizing a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package is applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.
Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advance computational fluid dynamics codes, which is computationally expensive in mainframe supercomputer. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computer on a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package has been applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.
Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advance computational fluid dynamics codes, which is computationally expensive in mainframe supercomputer. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computer on a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package has been applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.
"Similarly to artificial intelligence, which is now revolutionizing many aspects of our daily lives, Earth system digital twin technologies have the potential to revolutionize the way Earth Science research will be conducted in the future, and how results and knowledge from this research will provide information to support decision making and yield impactful societal benefits. An Earth System Digital Twin or ESDT is a dynamic and interactive information system that first provides a digital replica of the past and current states of the Earth or Earth system as accurately and timely as possible; second, allows for computing forecasts of future states under nominal assumptions and based on the current replica; and third, offers the capability to investigate many hypothetical scenarios under varying impact assumptions. In other words, an ESDT provides the integrated What-Now, What-Next, and What-If pictures of the Earth or Earth system, by continuously ingesting newly observed data and by leveraging multiple interconnected models, machine learning as well advanced computing and visualization capabilities. Digital twins have been developed in engineering since 2002, but the interest in digital twins for the Earth domain is more recent and stems from the convergence of several developments: - The huge amount of diverse data that has now been collected continuously for more than 50 years, and that is becoming more and more difficult to access, understand, and utilize. - At the same time, because of climate change and its impacts the information produced by all of this data is becoming of interest to many new non-traditional users for analyzing and predicting various phenomena. - Because of advances in computational and visualization capabilities and the parallel unprecedented development of machine learning (ML), extracting relevant information from these large amounts of data and running complex models faster has become possible. As a result, it is becoming necessary and possible to build intuitive and interactive frameworks that will enable users with various skill levels and/or organizational hierarchy levels to easily access large amounts of targeted information along with the relevant tools and models (Earth system and human activity models), to support them in analyzing and visualizing this information, to help them understand interactions among models, to visualize the potential outcomes of various impacts, and to support decision or policy making. The full power of digital twins is that, through an integrated representation and standardized tools and software technologies, the same digital replica can address the needs of multiple users at various resolutions (spatial and temporal) and for various applications (science, economic, policy, etc.) – “from farmer to scientist”. With all these interests at stake, the challenges of building optimal digital twins are many and complex. The first challenge is to determine if a Digital Twin should be global or local, and multi-domain or thematic. For example, some domains such as Climate or Weather will require a global Digital Twin or Digital Twin capabilities while science areas such as Biodiversity might be more local. We can also envision that multiple thematic ESDTs, e.g., Air Quality, Wildfires, Hydrology could be federated or provide input to other ESDTs, either on a regional level or to a more global ESDT. Overall, we can imagine a future “web” of Digital Twins co-existing in a hierarchy or in a network, and capable of being connected or federated depending on the needs. This last point brings up the very important challenge of interoperability, including standards and protocols that will need to be built into these systems from the beginning. Each individual digital twin would have full flexibility in internal construction but would need standards-based interfaces (input and output) or hooks to make it compatible with others. Another challenge when building digital twins will be to decide how to organize each digital replica. Based on the applications targeted by the DT under implementation, various amounts and types of raw data, Analysis Ready Data (ARD) and information will need to be incorporated. Depending on the required latencies and needs of the users, various solutions can be considered, including Data Cubes, Data Lakes, pointers, or computing information on demand. We envision that each ESDT will choose a solution adapted to its specific objectives. Another important challenge is the type(s) of visualization that will be used, as well as the level of interactivity and refresh rate that will be required. Again, this will depend on the objectives of the ESDT, but also on the various users’ needs. In most cases, several types of visualizations and human interfaces will need to be offered depending on the projected users of that system. In parallel to the challenges highlighted above, there are also many tools and technologies that will need to be developed or improved for all types of digital twins. Among those are improved machine learning technologies, for example providing explainability, but also ML techniques for causality and providing a better integration of physics models. Additionally, reliable uncertainty quantification methods will be needed for all ESDT components, from validating data fusion and assimilation to assessing the accuracy of ML models and weighing the values of decisions supported by those systems. This presentation introduces the ESDT concept, presents several ESDT use cases, and a proposed ESDT architecture framework, as well as various technologies being developed by the Advanced Information Systems Technology (AIST) Program."
A broad spectrum of commercial and military vehicles employ some form of inertial measurement equipment. In general this equipment has a special purpose in that it was tailored for each specific application thereby resulting in high installation and maintenance costs. Recently the emphasis has been directed toward developing low cost building blocks from which the desired inertial functions can be derived. This paper describes a National Aeronautics and Space Administration (NASA) program that combines inertial system sensor and computational advances into a flight demonstration configuration. Specifically, an inertial navigation system employing strapdown laser gyro angular rate sensors and a miniature, modular digital flight computer is described. The objective of this program is to demonstrate, via flight test evaluation, the capabilities of the advanced sensor and computer as they apply to future low cost, high reliability inertial system applications.
Electronic and optoelectronic hardware implementations of highly parallel computing architectures address several ill-defined and/or computation-intensive problems not easily solved by conventional computing techniques. The concurrent processing architectures developed are derived from a variety of advanced computing paradigms including neural network models, fuzzy logic, and cellular automata. Hardware implementation technologies range from state-of-the-art digital/analog custom-VLSI to advanced optoelectronic devices such as computer-generated holograms and e-beam fabricated Dammann gratings. JPL's concurrent processing devices group has developed a broad technology base in hardware implementable parallel algorithms, low-power and high-speed VLSI designs and building block VLSI chips, leading to application-specific high-performance embeddable processors. Application areas include high throughput map-data classification using feedforward neural networks, terrain based tactical movement planner using cellular automata, resource optimization (weapon-target assignment) using a multidimensional feedback network with lateral inhibition, and classification of rocks using an inner-product scheme on thematic mapper data. In addition to addressing specific functional needs of DOD and NASA, the JPL-developed concurrent processing device technology is also being customized for a variety of commercial applications (in collaboration with industrial partners), and is being transferred to U.S. industries. This viewgraph p resentation focuses on two application-specific processors which solve the computation intensive tasks of resource allocation (weapon-target assignment) and terrain based tactical movement planning using two extremely different topologies. Resource allocation is implemented as an asynchronous analog competitive assignment architecture inspired by the Hopfield network. Hardware realization leads to a two to four order of magnitude speed-up over conventional techniques and enables multiple assignments, (many to many), not achievable with standard statistical approaches. Tactical movement planning (finding the best path from A to B) is accomplished with a digital two-dimensional concurrent processor array. By exploiting the natural parallel decomposition of the problem in silicon, a four order of magnitude speed-up over optimized software approaches has been demonstrated.