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Introduction: A Data Centric Vision for the long-term future; Community White Paper - Software and Computing tools; The changing landscape of computing even quantum computing; How much has been reflected in this conference… my observations
The control of flexible spacecraft is a difficult problem because of large number of elastic modes; low value, closely-spaced frequencies; very small damping; and uncertainties in math models. The traditional design approach is to design the structure first and then to design the control system. This view-graph presentation develops a methodology for spacecraft design which addresses control/structure interaction issues, produces technology for simultaneous control/structure design, and translates into algorithms and computational tools for practical integrated computer-aided design.
A major component of any liquid propellant rocket is the propellant injection system. Issues of interest include the degree of liquid vaporization and its impact on the combustion process, the pressure and temperature fields in the combustion chamber, and the cooling of the injector face and chamber walls. The Finite Difference Navier-Stokes (FDNS) code is a primary computational tool used in the MSFC Computational Fluid Dynamics Branch. The branch has dedicated a significant amount of resources to development of this code for prediction of both liquid and solid fuel rocket performance. The FDNS code is currently being upgraded to include the capability to model liquid/gas multi-phase flows for fuel injection simulation. An important aspect of this effort is benchmarking the code capabilities to predict existing experimental injection data. The objective of this MSFC/ASEE Summer Faculty Fellowship term was to evaluate the capabilities of the modified FDNS code to predict flow fields with liquid injection. Comparisons were made between code predictions and existing experimental data. A significant portion of the effort included a search for appropriate validation data. Also, code simulation deficiencies were identified.
The Bio- Visualization, Imaging and Simulation (BioVIS) Technology Center at NASA's Ames Research Center is dedicated to developing and applying advanced visualization, computation and simulation technologies to support NASA Space Life Sciences research and the objectives of the Fundamental Biology Program. Research ranges from high resolution 3D cell imaging and structure analysis, virtual environment simulation of fine sensory-motor tasks, computational neuroscience and biophysics to biomedical/clinical applications. Computer simulation research focuses on the development of advanced computational tools for astronaut training and education. Virtual Reality (VR) and Virtual Environment (VE) simulation systems have become important training tools in many fields from flight simulation to, more recently, surgical simulation. The type and quality of training provided by these computer-based tools ranges widely, but the value of real-time VE computer simulation as a method of preparing individuals for real-world tasks is well established. Astronauts routinely use VE systems for various training tasks, including Space Shuttle landings, robot arm manipulations and extravehicular activities (space walks). Currently, there are no VE systems to train astronauts for basic and applied research experiments which are an important part of many missions. The Virtual Glovebox (VGX) is a prototype VE system for real-time physically-based simulation of the Life Sciences Glovebox where astronauts will perform many complex tasks supporting research experiments aboard the International Space Station. The VGX consists of a physical display system utilizing duel LCD projectors and circular polarization to produce a desktop-sized 3D virtual workspace. Physically-based modeling tools (Arachi Inc.) provide real-time collision detection, rigid body dynamics, physical properties and force-based controls for objects. The human-computer interface consists of two magnetic tracking devices (Ascention Inc.) attached to instrumented gloves (Immersion Inc.) which co-locate the user's hands with hand/forearm representations in the virtual workspace. Force-feedback is possible in a work volume defined by a Phantom Desktop device (SensAble inc.). Graphics are written in OpenGL. The system runs on a 2.2 GHz Pentium 4 PC. The prototype VGX provides astronauts and support personnel with a real-time physically-based VE system to simulate basic research tasks both on Earth and in the microgravity of Space. The immersive virtual environment of the VGX also makes it a useful tool for virtual engineering applications including CAD development, procedure design and simulation of human-system systems in a desktop-sized work volume.
A computational tool named SUPIN has been developed to design and analyze external-compression supersonic inlets for aircraft at cruise speeds from Mach 1.6 to 2.0. The inlet types available include the axisymmetric outward-turning, two-dimensional single-duct, two-dimensional bifurcated-duct, and streamline-traced Busemann inlets. The aerodynamic performance is characterized by the flow rates, total pressure recovery, and drag. The inlet flowfield is divided into parts to provide a framework for the geometry and aerodynamic modeling and the parts are defined in terms of geometric factors. The low-fidelity aerodynamic analysis and design methods are based on analytic, empirical, and numerical methods which provide for quick analysis. SUPIN provides inlet geometry in the form of coordinates and surface grids useable by grid generation methods for higher-fidelity computational fluid dynamics (CFD) analysis. SUPIN is demonstrated through a series of design studies and CFD analyses were performed to verify some of the analysis results.
All subsurface stress measurement methods available for deep subsurface applications are indirect and involve a significant amount of uncertainty. Quantifying these uncertainties is critical for applications where the state of stress is a component of a risk analysis with significant safety, environmental, and economic considerations. A publicly available and open source tool called the State of Stress Analysis Tool (SOSAT) has been developed to aid in performing a Bayesian uncertainty quantification and geomechanical risk analysis using many types of commonly available data. A new feature of this tool is using data from the FutureGen 2.0 site. The new feature of the tool was uses information about the absence or presence of borehole breakouts to constrain the state of stress. This new feature allows the user to specify probability distributions for the relevant parameters such as the drilling mud pressure, temperature, and the formation strength properties. The tool computes the posterior joint probability distribution of the horizontal principal stresses. Using random samples from this posterior distribution the tool then computes the probability of activating a critically oriented fault at a range of pore pressures. This latter feature can be used to aid in the assessment of the risk of induced seismicity and leakage in geologic carbon sequestration and enhanced geothermal systems.
Uncertainty quantification (UQ) has become more critical in aerospace engineering due to the growing dependence on computational tools for design optimization and performance analyses of aerospace vehicles. Even though the significance of UQ in assessing the credibility of computational analyses is well recognized, its costs and complexity impede its integration into standard practices, particularly in computational fluid dynamics (CFD) and other fluid analyses. This paper presents a UQ study for low-fidelity computational aerodynamics analyses with XFOIL and mfoil (i.e., the MATLAB version of XFOIL with several implementation modifications); these tools are utilized widely in both research and education. The main contributions of this paper are as follows: 1) improved precision in quantifying the uncertainty of the baseline Monte Carlo results used to benchmark surrogate modeling techniques for UQ, 2) quantification of the effect of the implementation differences between XFOIL and mfoil on solution quantities of interest (QoIs), such as lift and pitching moment coefficients, and 3) development of an open-source UQ library for use with XFOIL and mfoil, which has educational values and helps promote UQ for fluid analyses with aerospace applications. Results and discussions revolve around cases 1-4 of the challenge problem posed by the AIAA Fluid Dynamics Technical Committee’s Uncertainty Quantification Discussion Group (UQDG). In case 3, this work employs CFDverify, an open-source solution verification software, to quantify the discretization error and evaluate the extrapolated QoIs based on the grid convergence index (GCI). This UQ study differentiates itself from previous studies in the rigor of handling baseline Monte Carlo uncertainty and in including mfoil, which is a more accessible alternative to XFOIL. Finally, despite the growing computing power, low-fidelity computational tools remain valuable, such as for aerodynamic shape optimization at Mach numbers below 0.65 and low-to-mid Reynolds numbers.
With the increasing costs of physics experiments and simultaneous increase in availability and maturity of computational tools it is not surprising that computational fluid dynamics (CFD) is playing an increasingly important role, not only in post-test investigations, but also in the early stages of experimental planning. This paper describes a CFD-based effort executed in close collaboration between computational fluid dynamicists and experimentalists to develop a virtual experiment during the early planning stages of the Enhanced Injection and Mixing project at NASA Langley Research Center. This projects aims to investigate supersonic combustion ramjet (scramjet) fuel injection and mixing physics, improve the understanding of underlying physical processes, and develop enhancement strategies and functional relationships relevant to flight Mach numbers greater than 8. The purpose of the virtual experiment was to provide flow field data to aid in the design of the experimental apparatus and the in-stream rake probes, to verify the nonintrusive measurements based on NO-PLIF, and to perform pre-test analysis of quantities obtainable from the experiment and CFD. The approach also allowed for the joint team to develop common data processing and analysis tools, and to test research ideas. The virtual experiment consisted of a series of Reynolds-averaged simulations (RAS). These simulations included the facility nozzle, the experimental apparatus with a baseline strut injector, and the test cabin. Pure helium and helium-air mixtures were used to determine the efficacy of different inert gases to model hydrogen injection. The results of the simulations were analyzed by computing mixing efficiency, total pressure recovery, and stream thrust potential. As the experimental effort progresses, the simulation results will be compared with the experimental data to calibrate the modeling constants present in the CFD and validate simulation fidelity. CFD will also be used to investigate different injector concepts, improve understanding of the flow structure and flow physics, and develop functional relationships. Both RAS and large eddy simulations (LES) are planned for post-test analysis of the experimental data.
There are many individual computational tools and methods used to analyze and design components of a rocket engine thrust chamber assembly (TCA) 11,21. To analyze and design a thrust chamber assembly these tools are usually used in sequence while communication of information between these tools is usually done manually. Each component of a TCA is usually designed and optimized individually with limited considerations on system optimized design. This approach is often iterative and can be prone to error. Also at present, expert knowledge of each tool is required. The objective of this software development effort is to select, integrate and automate the best tools into an easy-to-use computational package, the Thrust Chamber Analysis Toolkit (TCAT). This tool will provide a seamless process to analyze and design all or individual components of a thrust chamber assembly. This paper describes the current status of the MAT software development. The selected component codes and their capabilities are briefly described. User and module interfaces and integration status are presented. MAT pre- and post-processing added options are presented and overall MAT capabilities are demonstrated with the results of sample cases. Ongoing and planned model validation efforts are also described. Finally, the MAT future plan options are discussed.
A concerted effort has been underway over the past several years to evolve computational capabilities for modeling aircraft loss-of-control under the NASA Aviation Safety Program. A principal goal has been to develop reliable computational tools for predicting and analyzing the non-linear stability & control characteristics of aircraft near stall boundaries affecting safe flight, and for utilizing those predictions for creating augmented flight simulation models that improve pilot training. Pursuing such an ambitious task with limited resources required the forging of close collaborative relationships with a diverse body of computational aerodynamicists and flight simulation experts to leverage their respective research efforts into the creation of NASA tools to meet this goal. Considerable progress has been made and work remains to be done. This paper summarizes the status of the NASA effort to establish computational capabilities for modeling aircraft loss-of-control and offers recommendations for future work.
This paper describes initial results from an ongoing activity comparing two aerodynamic analysis tools: OVERFLOW, a Navier-Stokes flow solver, and FlightStream, a viscous surface-vorticity, unstructured panel method flow solver. Both tools are applied to analyses of an unblown wing and a propeller-blown wing, and then comparisons are performed between the predicted aerodynamic loads and moments from each tool. Computational performance and efficiencies of each tool and their usability in conceptual and preliminary air vehicle design are also discussed. A description of the workflow, underlying theoretical foundations, and best practices are provided. In comparing FlightStream and OVERFLOW, reasonable agreement between predicted performance is observed for flow regimes of interest at high angle of attack prior to stall, including blown wing aero-propulsive effects on lift augmentation and stall delay. In the post-stall regions, FlightStream appears to underestimate the effects of turbulent flow separation that contribute heavily to drag. However, as expected for a high-fidelity, time-accurate solver, the setup and computation time are substantially greater for OVERFLOW than for FlightStream.
This paper describes initial results from an ongoing activity comparing two aerodynamic analysis tools: OVERFLOW, a Navier-Stokes flow solver, and FlightStream, a viscous surface-vorticity, unstructured panel method flow solver. Both tools are applied to analyses of an unblown wing and a propeller-blown wing, and then comparisons are performed between the predicted aerodynamic loads and moments from each tool. Computational performance and efficiencies of each tool and their usability in conceptual and preliminary air vehicle design are also discussed. A description of the workflow, underlying theoretical foundations, and best practices are provided. In comparing FlightStream and OVERFLOW, reasonable agreement between predicted performance is observed for flow regimes of interest at high angle of attack prior to stall, including blown wing aero-propulsive effects on lift augmentation and stall delay. In the post-stall regions, FlightStream appears to underestimate the effects of turbulent flow separation that contribute heavily to drag. However, as expected for a high-fidelity, time-accurate solver, the setup and computation time are substantially greater for OVERFLOW than for FlightStream.
We introduce ToPolyAgent, a multi-agent AI framework for performing coarse-grained molecular dynamics (MD) simulations of topological polymers through natural language instructions. By integrating large language models (LLMs) with domain-specific computational tools, ToPolyAgent supports both interactive and autonomous simulation workflows across diverse polymer architectures, including linear, ring, brush, and star polymers, as well as dendrimers. The system consists of four LLM-powered agents: a Config Agent for generating initial polymer–solvent configurations, a Simulation Agent for executing LAMMPS-based MD simulations and conformational analyses, a Report Agent for compiling markdown reports, and a Workflow Agent for streamlined autonomous operations. Interactive mode incorporates user feedback loops for iterative refinements, while autonomous mode enables end-to-end task execution from detailed prompts. We demonstrate ToPolyAgent's versatility through case studies involving diverse polymer architectures under varying solvent conditions, thermostats, and simulation lengths. Furthermore, we highlight its potential as a research assistant by directing it to investigate the effect of interaction parameters on the linear polymer conformation, and the influence of grafting density on the persistence length of the brush polymer. By coupling natural language interfaces with rigorous simulation tools, ToPolyAgent lowers barriers to complex computational workflows and advances AI-driven materials discovery in polymer science. It lays the foundation for autonomous and extensible multi-agent scientific research ecosystems.
During the past year, a great deal of effort was focused on the enhancement and refinement of the computational tools developed as part of our previous NASA grant. In particular, the interface mollification algorithm developed earlier was extended to incorporate the effects of surface-rheological properties in order to allow the study of thermocapillary flows in the presence of surface contamination. These tools will be used in the computational component of the proposed research in the remaining years of this grant. A detailed description of the progress made in this area is provided elsewhere. Briefly, the method developed allows for the convection and diffusion of bulk-insoluble surfactants on a moving and deforming interface. The novelty of the method is its grid independence: there is no need for front tracking, surface reconstruction, body-fitted grid generation, or metric evaluations; these are all very expensive computational tasks in three dimensions. For small local radii of curvature there is a need for local grid adaption so that the smearing thickness remains a small fraction of the radius of curvature. A special Neumann boundary condition was devised and applied so that the calculated surfactant concentration has no variations normal to the interface, and it is hence truly a surface-defined quantity. The discretized governing equations are solved subsequently using a time-split integration scheme which updates the concentration and the shape successively. Results demonstrate excellent agreement between the computed and exact solutions.
We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.
Distributed computing has been regarded as the future of high performance computing. Nationwide high speed networks such as vBNS are becoming widely available to interconnect high-speed computers, virtual environments, scientific instruments and large data sets. One of the major issues to be addressed with distributed systems is the development of computational tools that facilitate the efficient execution of parallel applications on such systems. These tools must exploit the heterogeneous resources (networks and compute nodes) in distributed systems. This paper presents a tool, called PART, which addresses this issue for mesh partitioning. PART takes advantage of the following heterogeneous system features: (1) processor speed; (2) number of processors; (3) local network performance; and (4) wide area network performance. Further, different finite element applications under consideration may have different computational complexities, different communication patterns, and different element types, which also must be taken into consideration when partitioning. PART uses parallel simulated annealing to partition the domain, taking into consideration network and processor heterogeneity. The results of using PART for an explicit finite element application executing on two IBM SPs (located at Argonne National Laboratory and the San Diego Supercomputer Center) indicate an increase in efficiency by up to 36% as compared to METIS, a widely used mesh partitioning tool. The input to METIS was modified to take into consideration heterogeneous processor performance; METIS does not take into consideration heterogeneous networks. The execution times for these applications were reduced by up to 30% as compared to METIS. These results are given in Figure 1 for four irregular meshes with number of elements ranging from 30,269 elements for the Barth5 mesh to 11,451 elements for the Barth4 mesh. Future work with PART entails using the tool with an integrated application requiring distributed systems. In particular this application, illustrated in the document entails an integration of finite element and fluid dynamic simulations to address the cooling of turbine blades of a gas turbine engine design. It is not uncommon to encounter high-temperature, film-cooled turbine airfoils with 1,000,000s of degrees of freedom. This results because of the complexity of the various components of the airfoils, requiring fine-grain meshing for accuracy. Additional information is contained in the original.
The goal of the work reported herein is to develop and validate computational tools to be used for the design of planar and non-planar wing geometries for minimum induced drag. Because of the iterative nature of the design problem, it is important that, in addition to being sufficiently accurate for the problem at hand, these tools need to be reasonably fast and computationally efficient. Toward this end, a method of predicting induced drag in the presence of a free wake has been coupled with a panel method. The induced drag prediction technique is based on the application of the Kutta-Joukowski law at the trailing edge. Until now, the use of this method has not been fully explored and pressure integration and Trefftz-plane calculations favored. As is shown in this report, however, the Kutta-Joukowski method is able to give better results for a given amount of effort than the more commonly used techniques, particularly when relaxed wakes and non-planar wing geometries are considered. Using these methods, it is demonstrated that a reduction in induced drag can be achieved through non-planar wing geometries. It remains to determine what overall drag reductions are possible when the induced drag reduction is traded-off against increased wetted area. With the design methodology that is described herein, such trade studies can be performed in which the non-linear effects of the free wake are taken into account.
During the lifetime of the project, the PIPER at the University of Utah worked in collaboration with the team from the partner institutions to establish a set of software tools for analyzing and improving the performance parallel computing tools. These activities complement and complete the work performed by the other X-Stack 2 projects with the definition of a common data models and computing infrastructures, which have been a central element in the targeted performance analysis pipeline and new programming models. The University of Utah team have focused mainly on developing data analysis and visualization systems to facilitate exploration, comparison and evaluation of the behavior and performance of complex algorithms in modern HPC infrastructures. This is involved several demonstrations of the performance achieved and presentation of the results in a way that facilitates the users understand bottlenecks and ways to overcome them. One major focus of the University of Utah activities has been the analysis of the performance characteristics of Fat-Tree and Dragonfly topology networks. The work involved the development of practical visualization systems especially in collaboration with the team at LLNL, and published several papers and gave invited talks at prestigious venues such as the Salishan Conference on High-Speed Computing or the International Conference on High Performance Computing, Data, and Analytics. In addition, the university of Utah team has advanced the core activities on analyzing the performance characteristics of I/O and other data movement systems and their practical use for scaling Uintah and other simulation codes poised for use in the exascale computing environments of the future.