SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
The development and use of a digital computer simulation of the proposed wind tunnel facility is described. The feasibility of automatic control of wind tunnel airspeed and other parameters was examined. Specifications and implementation recommendations for a computer based automatic control and monitoring system are presented.
An analytical computer simulation program for dynamic modeling of low-contact-ratio spur gear systems is presented. The procedure computes the static transmission error of the gears operating under load and uses a fast Fourier transform to generate the frequency spectrum of the static transmission error at various tooth profile modifications. The dynamic loading response of an unmodified (perfect involute) gear pair was compared with that of gears with various profile modifications. Correlations were found between various profile modifications and the resulting dynamic loads. An effective error, obtained from frequency domain analysis of the static transmission error of the gears, gave a very good indication of the optimum profile modification to reduce gear dynamic loading. Design curves generated by dynamic simulation at various profile modifications are given for gear systems operated at various loads. Optimum profile modifications can be determined from these design curves for improved gear design.
An analytical computer simulation program for dynamic modeling of low-contact-ratio spur gear systems is presented. The procedure computes the static transmission error of the gears operating under load and uses a fast Fourier transform to generate the frequency spectrum of the static transmission error at various tooth profile modifications. The dynamic loading response of an unmodified (perfect involute) gear pair was compared with that of gears with various profile modifications. Correlations were found between various profile modifications and the resulting dynamic loads. An effective error, obtained from frequency domain analysis of the static transmission error of the gears, gave a very good indication of the optimum profile modification to reduce gear dynamic loading. Design curves generated by dynamic simulation at various profile modifications are given for gear systems operated at various loads. Optimum profile modifications can be determined from these design curves for improved gear design.
It has been proposed that a Doppler lidar be placed in a polar orbit and scanned to provide estimates of lower tropospheric winds twice per day and with a spatial resolution of 300 km. Initial feasibility studies conducted primarily by NOAA and NASA presented an optimistic outlook for a space based lidar. The technology appeared within reach and initial computer simulations suggested that acceptable accuracies could be obtained. Those early studies exposed, however, several potential problem areas which included: (1) the algorithms for computing the wind vectors did not perform well when there were coherent gradients in the wind fields; and (2) the lifetime and power requirements of the lidar put severe restrictions on the pulse repetition frequency (PRF). These two basic problems are currently being addressed by a Doppler lidar simulation study focussed upon three primary objectives: (1) to develop optimum scan parameters and shot patterns for a satellite-based Doppler lidar; (2) to develop robust algorithms for computing wind vectors from lidar returns; and (3) to evaluate the impact of coherent mesoscale structures (wind gradients, clouds, aerosols) on up-scale wind estimates. An overview is provided of the simulation efforts with particular emphasis upon rationale and methodology. Since this research is currently underway, any results shown are meant only as evidence of progress.
Failure of a dam can have subtle beginnings. A small crack or dislocation at the interface of the concrete dam and the surrounding embankment soil initiated by, for example, a seismic or an explosive event can lead to a catastrophic failure of the dam. The dam may ‘self-rehabilitate’ if a properly designed granular filter is engineered around the embankment. Currently, the design criteria for such filters have only been based on experimental studies. We demonstrate the numerical prediction of filter effectiveness at the soil grain scale. This joint LLNL-ERDC basic research project, funded by the Department of Homeland Security’s Science and Technology Directorate (DHS S&T), consists of validating advanced high performance computer simulations of soil erosion and transport of grain- and dam-scale models to detailed centrifuge and soil erosion tests. Validated computer predictions highlight that a resilient filter is consistent with the current design specifications for dam filters. These predictive simulations, unlike the design specifications, can be used to assess filter success or failure under different soil or loading conditions and can lead to meaningful estimates of the timing and nature of full-scale dam failure.
The Collaborative-Virtual Environment Simulation Tool (C-VEST) software was developed for use in a NASA project entitled "3-D Interactive Digital Virtual Human." The project is oriented toward the use of a comprehensive suite of advanced software tools in computational simulations for the purposes of human-centered design of spacecraft missions and of the spacecraft, space suits, and other equipment to be used on the missions. The C-VEST software affords an unprecedented suite of capabilities for three-dimensional virtual-environment simulations with plug-in interfaces for physiological data, haptic interfaces, plug-and-play software, realtime control, and/or playback control. Mathematical models of the mechanics of the human body and of the aforementioned equipment are implemented in software and integrated to simulate forces exerted on and by astronauts as they work. The computational results can then support the iterative processes of design, building, and testing in applied systems engineering and integration. The results of the simulations provide guidance for devising measures to counteract effects of microgravity on the human body and for the rapid development of virtual (that is, simulated) prototypes of advanced space suits, cockpits, and robots to enhance the productivity, comfort, and safety of astronauts. The unique ability to implement human-in-the-loop immersion also makes the C-VEST software potentially valuable for use in commercial and academic settings beyond the original space-mission setting.
Livermore researchers prepare for a full-scale asteroid deflection experiment using computer simulations.
In the Applied Aerosciences and CFD branch at Johnson Space Center, computational simulations are run that face many challenges. Two of which are the ability to customize software for specialized needs and the need to run simulations as fast as possible. There are many different tools that are used for running these simulations and each one has its own pros and cons. Once these simulations are run, there needs to be software capable of visualizing the results in an appealing manner. Some of this software is called open source, meaning that anyone can edit the source code to make modifications and distribute it to all other users in a future release. This is very useful, especially in this branch where many different tools are being used. File readers can be written to load any file format into a program, to ease the bridging from one tool to another. Programming such a reader requires knowledge of the file format that is being read as well as the equations necessary to obtain the derived values after loading. When running these CFD simulations, extremely large files are being loaded and having values being calculated. These simulations usually take a few hours to complete, even on the fastest machines. Graphics processing units (GPUs) are usually used to load the graphics for computers; however, in recent years, GPUs are being used for more generic applications because of the speed of these processors. Applications run on GPUs have been known to run up to forty times faster than they would on normal central processing units (CPUs). If these CFD programs are extended to run on GPUs, the amount of time they would require to complete would be much less. This would allow more simulations to be run in the same amount of time and possibly perform more complex computations.
The design space for inertial confinement fusion (ICF) experiments is vast, and experiments are extremely expensive. Researchers rely heavily on computer simulations to explore the design space in search of high-performing implosions. However, ICF multiphysics codes must make simplifying assumptions, and thus deviate from experimental measurements for complex implosions. For more effective design and investigation, simulations require input from past experimental data to better predict future performance. In this work, we describe a cognitive simulation method for combining simulation and experimental data into a common, predictive model. This method leverages a machine learning technique called “transfer learning,” the process of taking a model trained to solve one task, and partially retraining it on a sparse dataset to solve a different, but related task. In the context of ICF design, neural network models are trained on large simulation databases and partially retrained on experimental data, producing models that are far more accurate than simulations alone. Here, we demonstrate improved model performance for a range of ICF experiments at the National Ignition Facility and predict the outcome of recent experiments with less than 10% error for several key observables. We discuss how the methods might be used to carry out a data-driven experimental campaign to optimize performance, illustrating the key product—models that become increasingly accurate as data are acquired.
Savannah River National Laboratory (SRNL) started a multi-year project, the PreCalc Project, to develop a computational simulation of a plutonium oxide (PuO 2 ) production facility with the objective to study the fundamental relationships between morphological and physicochemical properties. This report provides a detailed baseline process description to be used by SRNL personnel and collaborators to facilitate the initial design and construction of the simulation. The PreCalc Project team selected the HB-Line Plutonium Finishing Facility as the basis for a nominal baseline process since the facility is operational and significant model validation data can be obtained. The process boundary as well as process and facility design details necessary for multi-scale, multi-physics models are provided.
The effects of noise and vibration on pilot performance are described. Pilot subjects were required to fly VTOL commercial IFR schedules using the computer simulation facilities. The routes flown simulated closely metropolitan routes flown currently by a helicopter airline. The duration of simulator flights ranged from 3 to 8 hours. Subjects were exposed to noise sound pressure levels ranging from 74dB (ambient) to 100dB and 17 Hz vibration stimuli ranging from .1 g to .3 g measured at the floor directly beneath the pilot's seat. Despite subject reports of extreme fatigue in these long flights, performance did not degrade. A curve of performance shows a slow improvement for the first three hours of exposure and a slight loss in performance during the remainder of the flight. As environmental stress conditions (noise, vibration, and time in the simulator) increased, subject performance improved. Within the limits of this study, the higher the stress the better the performance.
A method is presented for open loop guidance of a solar electric propulsion spacecraft to geosynchronsus orbit. The method consists of determining the thrust vector profiles on the ground with an optimization computer program, and performing updates based on the difference between the actual trajectory and that predicted with a precision simulation computer program. The motivation for performing the guidance analysis during the mission planning phase is discussed, and a spacecraft design option that employs attitude orientation constraints is presented. The improvements required in both the optimization program and simulation program are set forth, together with the efforts to integrate the programs into the ground support software for the guidance system.
A method is presented for open loop guidance of a solar electric propulsion spacecraft to geosynchronous orbit. The method consists of determining the thrust vector profiles on the ground with an optimization computer program, and performing updates based on the difference between the actual trajectory and that predicted with a precision simulation computer program. The motivation for performing the guidance analysis during the mission planning phase is discussed, and a spacecraft design option that employs attitude orientation constraints is presented. The improvements required in both the optimization program and simulation program are set forth, together with the efforts to integrate the programs into the ground support software for the guidance system.
The flow field in and around the nozzle afterbody section of a hypersonic vehicle was computationally simulated. The compressible, Reynolds averaged, Navier Stokes equations were solved by an implicit, finite volume, characteristic based method. The computational grids were adapted to the flow as the solutions were developing in order to improve the accuracy. The exhaust gases were assumed to be cold. The computational results were obtained for the two dimensional longitudinal plane located at the half span of the internal portion of the nozzle for over expanded and under expanded conditions. Another set of results were obtained, where the three dimensional simulations were performed for a half span nozzle. The surface pressures were successfully compared with the data obtained from the wind tunnel tests. The results help in understanding this complex flow field and, in turn, should help the design of the nozzle afterbody section.
An object-oriented event-driven immersive Virtual environment is described for the creation of virtual labs (VLs) for simulating physical experiments. Discussion focuses on a number of aspects of the VLs, including interface devices, software objects, and various applications. The VLs interface with output devices, including immersive stereoscopic screed(s) and stereo speakers; and a variety of input devices, including body tracking (head and hands), haptic gloves, wand, joystick, mouse, microphone, and keyboard. The VL incorporates the following types of primitive software objects: interface objects, support objects, geometric entities, and finite elements. Each object encapsulates a set of properties, methods, and events that define its behavior, appearance, and functions. A container object allows grouping of several objects. Applications of the VLs include viewing the results of the physical experiment, viewing a computer simulation of the physical experiment, simulation of the experiments procedure, computational steering, and remote control of the physical experiment. In addition, the VL can be used as a risk-free (safe) environment for training. The implementation of virtual structures testing machines, virtual wind tunnels, and a virtual acoustic testing facility is described.
Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist’s toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy but are computationally expensive and scale poorly to large systems, while classical force fields are cheap and scalable, but lack transferability to new systems. Machine learning can be used to achieve the best of both approaches. Here we train a general-purpose neural network potential (ANI-1ccx) that approaches CCSD(T)/CBS accuracy on benchmarks for reaction thermochemistry, isomerization, and drug-like molecular torsions. This is achieved by training a network to DFT data then using transfer learning techniques to retrain on a dataset of gold standard QM calculations (CCSD(T)/CBS) that optimally spans chemical space. The resulting potential is broadly applicable to materials science, biology, and chemistry, and billions of times faster than CCSD(T)/CBS calculations.
The quality of the powder bed is known to be one of the main factors that influence the quality of the part being manufactured by powderbed- based additive manufacturing processes. For example, in the laser powder bed fusion process, it has been demonstrated that improving the powder bed density and homogeneity improves the final quality of the part. Understanding powder spreading dynamics in the powder-bed-based additive manufacturing processes is critical for designing spreading structures and spreading parameters, identifying defect formation mechanisms in the powder bed, and guiding the design of optimized feedstock powders. Extensive efforts have been devoted to understand the fundamental mechanism of the powder flow and spreading process. Various powder flow testers were used to study the flow behavior of powders used in additive manufacturing. However, the powder flow conditions in flow meters are different from those in real additive manufacturing conditions. Models have also been developed to simulate and study the spreading process. The discrete element method (DEM) is currently the main tool for computationally simulating the spreading process. However, these models are based on many physical assumptions. Visible light cameras have been used recently to conduct in-situ study of powder spreading in additive manufacturing. Due to the limited resolution and penetration depth of visible light, it is extremely difficulty to study the particle-scale powder spreading dynamics. Here, to overcome the challenges of studying powder spreading dynamics under real additive manufacturing conditions, we developed an experimental approach to study the particle-scale powder spreading process with high spatial and temporal resolution using the high-speed high-energy X-ray imaging facility at beamline 32-ID-B of the APS. Figure 1 shows an overview of the research setup. It is composed of a vacuum chamber (building environment), an automatic powder spreading system, a laser system, an X-ray source (X-ray outlet), and an X-ray detection/imaging system.
Previous work on multilevel techniques for compression and reduction of scientific data is extended to the case of data given on unstructured meshes in two and three dimensions. The centerpiece of the work is a decomposition algorithm which is shown to be optimal, in terms of both storage and operational complexity, applicable to unstructured grids in both two and three dimensions, and which implicitly gives a Riesz basis that can be exploited to reduce the data while maintaining rigorous bounds on the loss incurred. The flexibility of the approach is illustrated by applications to potential flow around an airfoil and the effect of compression on quantities of interest relevant to airfoil design; compression of computational simulation of a nonlinear reaction-diffusion system with special attention given to the problem of time series reduction; and, data from a simulation of magnetically confined plasma in a fusion reactor reduced so as to preserve the electric field computed from the data.