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Dr. Tu will talk about the current and future missions of NASA in aviation and space, provide an overview of NASA’s Ames Research Center located in Silicon Valley, CA, and discuss his personal journey starting as a student intern in the earlier days of computational fluid dynamics.
Think of some examples of repair in everyday life. Maybe you had a car accident and took your car to the body shop. Maybe the head came off your child’s doll and you had to glue it back on. Maybe the handle of your shovel cracked and you wrapped the cracked area with duct tape to hold it together. These are examples of what could be called reactive repair, where an unexpected accident initiates a sequence of action and decision-making that ends in repair. In these cases, most of the thinking and planning surrounding repair takes place after a breakdown has been identified. This type of repair is often taken to be distinct from deliberate design, as it occurs within the context of technology that is already in operation, often has an improvisational character, and may be performed by end users or technicians rather than credentialed experts. But does repair always have to be reactive? And if not, what does this tell us about the distinction between design and repair, and their respective roles in shaping technological change? The short answer is that repair, like design, can play a dynamic and forward-looking role in shaping technological trajectories – not only stabilizing existing systems, but anticipating change and generating new technological futures.
The substantial increase in data volume and complexity expected from future experiments will require significant investment to prepare experimental algorithms. These algorithms include physics object reconstruction, calibrations, and processing of observational data. In addition, the changing computing architecture landscape, which will be primarily composed of heterogeneous resources, will continue to pose major challenges with regard to algorithmic migration. Portable tools need to be developed that can be shared among the frontiers (e.g., for code execution on different platforms) and opportunities, such as forums or cross-experimental working groups, need to be provided where experiences and lessons learned can be shared between experiments and frontiers. At the same time, individual experiments also need to invest considerable resources to develop algorithms unique to their needs (e.g., for facilities dedicated to the experiment), and ensure that their specific algorithms will be able to efficiently exploit external heterogeneous computing facilities. Common software tools represent a cost-effective solution, providing ready-to-use software solutions as well as a platform for R&D work. These are particularly important for small experiments which typically do not have dedicated resources needed to face the challenges imposed by the evolving computing technologies. Workforce development is a key concern across frontiers and experiments, and additional support is needed to provide career opportunities for researchers working in the field of experimental algorithm development. Finally, cross-discipline collaborations going beyond high-energy physics are a key ingredient to address the challenges ahead and more support for such collaborations needs to be created. This report targets future experiments, observations and experimental algorithm development for the next 10-15 years.
Several two- and three-dimensional external and internal flow problems solved on the STAR-100 and CYBER-203 vector processing computers are described. The flow field was described by the full Navier-Stokes equations which were then solved by explicit finite-difference algorithms. Problem results and computer system requirements are presented. Program organization and data base structure for three-dimensional computer codes which will eliminate or improve on page faulting, are discussed. Storage requirements for three-dimensional codes are reduced by calculating transformation metric data in each step. As a result, in-core grid points were increased in number by 50% to 150,000, with a 10% execution time increase. An assessment of current and future machine requirements shows that even on the CYBER-205 computer only a few problems can be solved realistically. Estimates reveal that the present situation is more storage limited than compute rate limited, but advancements in both storage and speed are essential to realistically calculate three-dimensional flow.
Two research activities directed at hypersonic vehicle configurations are currently underway. The first involves the validation of a number of classical local surface inclination methods commonly employed in preliminary design studies of hypersonic flight vehicles. Unlike studies aimed at validating such methods for predicting overall vehicle aerodynamics, this effort emphasizes validating the prediction of forces and moments for flight control studies. Specifically, several vehicle configurations for which experimental or flight-test data are available are being examined. By comparing the theoretical predictions with these data, the strengths and weaknesses of the local surface inclination methods can be ascertained and possible improvements suggested. The second research effort, of significance to control during take-off and landing of most proposed hypersonic vehicle configurations, is aimed at determining the change due to ground effect in control effectiveness of highly swept delta planforms. Central to this research is the development of a vortex-lattice computer program which incorporates an unforced trailing vortex sheet and an image ground plane. With this program, the change in pitching moment of the basic vehicle due to ground proximity, and whether or not there is sufficient control power available to trim, can be determined. In addition to the current work, two different research directions are suggested for future study. The first is aimed at developing an interactive computer program to assist the flight controls engineer in determining the forces and moments generated by different types of control effectors that might be used on hypersonic vehicles. The first phase of this work would deal in the subsonic portion of the flight envelope, while later efforts would explore the supersonic/hypersonic flight regimes. The second proposed research direction would explore methods for determining the aerodynamic trim drag of a generic hypersonic flight vehicle and ways in which it can be minimized through vehicle design and trajectory optimization.
Mixed solvents (i.e., binary or higher order mixtures of ionic or nonionic liquids) play crucial roles in chemical syntheses, separations, and electrochemical devices because they can be tuned for specific reactions and applications. Apart from fully explicit solvation treatments that can be difficult to parameterize or computationally expensive, there is currently no well-established first-principles regimen for reliably modeling atomic-scale chemistry in mixed solvent environments. We offer our perspective on how this process could be achieved in the near future as mixed solvent systems become more explored using theoretical and computational chemistry. We first outline what makes mixed solvent systems far more complex compared to single-component solvents. An overview of current and promising techniques for modeling mixed solvent environments is provided. We focus on so-called hybrid solvation treatments such as the conductor-like screening model for real solvents and the reference interaction site model, which are far less computationally demanding than explicit simulations. We also propose that cluster-continuum approaches rooted in physically rigorous quasi-chemical theory provide a robust, yet practical, route for studying chemical processes in mixed solvents.
The MOOSE-based reactor physics code Griffin was assessed on a heterogeneous pin-resolved model of a prototype lead-cooled fast reactor assembly. This model was developed in preparation for future use in MOOSE-based multiphysics calculations for computing hot channel factors. Heterogeneous multigroup cross sections were prepared using the fast reactor multi-group cross section processing code MC{sup 2}-3 using a two-step method. Griffin simulations were performed using the DFEM-SN solver on 576 cores on Argonne's LCRC cluster. Diffusion-based acceleration methods were applied (NDA and CMFD). Reference solutions were generated with continuous energy MCNP and the hybrid MOC/finite element solver PROTEUS-MOC for code-to-code comparison. Space-angle convergence studies were conducted to observe convergence in k-eigenvalue and axial pin power distributions. The fully resolved Griffin calculation was within 68 pcm of the MCNP eigenvalue and exhibited max 1.2% relative error in the axial pin power distribution. Griffin produced nearly identical results to PROTEUS-MOC when using the same 9-group multigroup cross-section set. Griffin demonstrated favorable scaling in wall-clock time and memory usage when using diffusion-based acceleration methods. Griffin is capable of simulating the pin-resolved heterogeneous LFR assembly with good accuracy and performance, and is suitable for future use in coupled high-fidelity hot channel factor simulations. (authors)
The motivation for Computational Aeroelasticity (CA) and the elements of one type of the analysis or simulation process are briefly reviewed. The need for streamlining and improving the overall process to reduce elapsed time and improve overall accuracy is discussed. Further effort is needed to establish the credibility of the methodology, obtain experience, and to incorporate the experience base to simplify the method for future use. Experience with the application of a variety of Computational Aeroelasticity programs is summarized for the transonic flutter of two wings, the AGARD 445.6 wing and a typical business jet wing. There is a compelling need for a broad range of additional flutter test cases for further comparisons. Some existing data sets that may offer CA challenges are presented.
The success of high energy physics programs relies heavily on accurate detector simulations and beam interaction modeling. The increasingly complex detector geometries and beam dynamics require sophisticated techniques in order to meet the demands of current and future experiments. Common software tools used today are unable to fully utilize modern computational resources, while data-recording rates are often orders of magnitude larger than what can be produced via simulation. In this paper, we describe the state, current and future needs of high energy physics detector and beamline simulations and related challenges, and we propose a number of possible ways to address them.
Discussed here is the future direction of various levels of engineering turbulence modeling related to computational fluid dynamics (CFD) computations for propulsion. For each level of computation, there are a few turbulence models which represent the state-of-the-art for that level. However, it is important to know their capabilities as well as their deficiencies in order to help engineers select and implement the appropriate models in their real world engineering calculations. This will also help turbulence modelers perceive the future directions for improving turbulence models. The focus is on one-point closure models (i.e., from algebraic models to higher order moment closure schemes and partial differential equation methods) which can be applied to CFD computations. However, other schemes helpful in developing one-point closure models, are also discussed.
Nonlinear optical (NLO) crystals with superior properties are significant for advancing laser technologies and applications. Introducing rare earth metals to borates is a promising and effective way to modify the electronic structure of a crystal to improve its optical properties in the visible and ultraviolet range. In this work, we computationally discover inversion symmetry breaking in EuBa 3 (B 3 O 6 ) 3 , which was previously identified as centric, and demonstrate noncentrosymmetry via synthesizing single crystals for the first time by the floating zone method. We determine the correct space group to be P 6¯. The material has a large direct bandgap of 5.56 eV and is transparent down to 250 nm. The complete anisotropic linear and nonlinear optical properties were also investigated with a d 11 of ∼0.52 pm/V for optical second harmonic generation. Further, it is Type I and Type II phase matchable. This work suggests that rare earth metal borates are an excellent crystal family for exploring future deep ultraviolet (DUV) NLO crystals. It also highlights how first principles computations combined with experiments can be used to identify noncentrosymmetric materials that have been wrongly assigned to be centrosymmetric.
This is a presentation to be made at the University of Tokyo. The Idaho National Laboratory is creating the next-generation reliability- and risk-assessment methods and tools that support risk-informed decision-making by combining physics-based models with probabilistic quantification approaches. Integrating these two worlds of physics and probability using a simulation framework leads us to predictions based upon an approach called “computational risk assessment” which will serve as the technical basis for the future of reliability and risk approaches. The driving factors for this new approach includes: temporal (timing issues), spatial (location issues), mechanistic (physics issues), and topological (complexity issues). By combining phenomenology directly with stochastic quantification, we are able to perform advanced uncertainty analysis directly on both parameters and models. In addition, new tools allow for the creation of reduced order models that mimic high-fidelity engineering models while still permitting the realization of thousands of simulation iterations in short run-times on current workstation-class computers. While these advanced methods and tools can provide increased realism in our engineering safety and risk approaches, their greater benefit is to provide a risk-informed engineering framework for design and operation. This talk will briefly review the history of risk assessment and risk-informed applications, describe some of the current research and development found at the Idaho National Laboratory, and discuss potential future applications and approaches for advanced methods and tools.
NREL’s sustainable mobility research is moving beyond vehicles and roads, investigating the best way to get people and goods where they need to go with maximum convenience, efficiency, and affordability while minimizing traffic congestion. Integrated research efforts span a variety of technologies—connected and autonomous vehicles and infrastructure; new materials and devices for top performance, efficiency, reliability, and durability; high-performance computing and machine learning; controls that integrate vehicles with energy, road, communication, building, and mass-transit systems; communities of the future, from rural to megacities; and consumer behavior and new models of car ownership.
An analysis of current computer usage by major water resources users was made to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era. The analysis showns significant impact due to the utilization and processing of ERTS CCT's data.
Principal water resources users were surveyed to determine the impact of remote data streams on hydrologic computer models. Analysis of responses demonstrated that: most water resources effort suitable to remote sensing inputs is conducted through federal agencies or through federally stimulated research; and, most hydrologic models suitable to remote sensing data are federally developed. Computer usage by major water resources users was analyzed to determine the trends of usage and costs for the principal hydrologic users/models. The laws and empirical relationships governing the growth of the data processing loads were described and applied to project the future data loads. Data loads for ERTS CCT image processing were computed and projected through the 1985 era.
To facilitate and solve the prediction problem, awareness of the current state and health of the system is key, since it is necessary to perform condition-based system health predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditional. In case of next generation electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. In order to tackle and solve the prediction problem, it is essential to have awareness of the current health state of the system, especially since it is necessary to perform condition-based predictions. To be able to predict the future state of the system, it is also required to possess knowledge of the current and future operational conditions and flight profiles for accurate estimation of end-of-discharge (EOD) for the batteries. Similar framework can be implemented to other complex systems and subsystems. Our research approach is to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system, subsystem swell as component levels. Given models of the current and future system behavior, a general approach of model-based prognostics is discussed as a solution to the prediction problem and further for decision making. Data driven prognostics approaches have been equally used with good results in the past, where respective approaches have their own challenges to tackle. This limits their applicability to complex real-world domains: (a) high complexity or incompleteness of physics-based models and (b) limited representativeness of the training dataset for data-driven models. With the advent of internet of things for data collection and increased use of ML algorithms, hybrid approaches are the next avenue to reduce the challenges and achieve better results. An hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, we use physics-based performance models to infer unobservable model parameters related to the system's components health solving a calibration problem.
In an effort to develop occupant protection standards for future multipurpose crew vehicles, the National Aeronautics and Space Administration (NASA) has looked to evaluate the test device for human occupant restraint with the modification kit (THOR‐K) anthropomorphic test device (ATD) in relevant impact test scenarios. With the allowance and support of the National Highway Traffic Safety Administration, NASA has performed a series of sled impact tests on the latest developed THOR‐K ATD. These tests were performed to match test conditions from human volunteer data previously collected by the U.S. Air Force. The objective of this study was to evaluate the THOR‐K finite element (FE) model and the Total HUman Model for Safety (THUMS) FE model with respect to the tests performed. These models were evaluated in spinal and frontal impacts against kinematic and kinetic data recorded in ATD and human testing. Methods: The FE simulations were developed based on recorded pretest ATD/human position and sled acceleration pulses measured during testing. Predicted responses by both human and ATD models were compared to test data recorded under the same impact conditions. The kinematic responses of the models were quantitatively evaluated using the ISO‐metric curve rating system. In addition, ATD injury criteria and human stress/strain data were calculated to evaluate the risk of injury predicted by the ATD and human model, respectively. Results: Preliminary results show well‐correlated response between both FE models and their physical counterparts. In addition, predicted ATD injury criteria and human model stress/strain values are shown to positively relate. Kinematic comparison between human and ATD models indicates promising biofidelic response, although a slightly stiffer response is observed within the ATD. Conclusion: As a compliment to ATD testing, numerical simulation provides efficient means to assess vehicle safety throughout the design process and further improve the design of physical ATDs. The assessment of the THOR‐K and THUMS FE models in a spaceflight testing condition is an essential first step to implementing these models in the computational evaluation of spacecraft occupant safety. Promising results suggest future use of these models in the aerospace field.
Collier Research and Development Corporation received a one-of-a-kind computer code for designing exotic hypersonic aircraft called ST-SIZE in the first ever Langley Research Center software copyright license agreement. Collier transformed the NASA computer code into a commercial software package called HyperSizer, which integrates with other Finite Element Modeling and Finite Analysis private-sector structural analysis program. ST-SIZE was chiefly conceived as a means to improve and speed the structural design of a future aerospace plane for Langley Hypersonic Vehicles Office. Including the NASA computer code into HyperSizer has enabled the company to also apply the software to applications other than aerospace, including improved design and construction for offices, marine structures, cargo containers, commercial and military aircraft, rail cars, and a host of everyday consumer products.