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At least 739 records · Page 41

Profile modification to minimize spur gear dynamic loading

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.

Lin, Hsiang Hsi↗

Profile modification to minimize spur gear dynamic loading

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.

Lin, H. H.↗

Integrated flow and structural modeling for rocket engine component test facility propellant systems

A set of PC-based computational Dynamic Fluid Flow Simulation models is presented for modeling facility gas and cryogenic systems. Data obtained provide important information regarding performance envelope parameters for the facility using different engine components; time-dependent valve setting for controlling steady-state, quasi-steady state, and transient profiles; optimum facility pipe and pipe component sizes and parameters; momentum transfer loads; and fluid conditions at critical points. A set of COSMIC NASTRAN-based finite element models is also presented to evaluate the loads and stresses on test facility piping systems from fluid and gaseous effects, thermal chill down, and occasional wind loads. The models are based on Apple Macintosh software which makes it possible to change numerous parameters.

Dequay, L.↗

An Efficient Time-Domain Model to Simulate Parametric Resonances in a Floating Body Free to Move in Six Degrees of Freedom: Preprint

We present a computationally efficient time-domain model capable of simulating parametric resonances in a floating body in waves. The model assumes all wave forces to be linear, but the inertia and restoring forces acting on the body are expanded to second order in body motions. The simulation speed on a standard computer is approximately 40 times faster than real time. The model is applied to a soft-moored floating axisymmetric body which absorbs energy through heave, but is otherwise free to move in six degrees of freedom. Under certain conditions, we show that the body responds parametrically with large amplitudes not only in surge and pitch, but also in sway, roll, and yaw, provided it is given some small initial displacement in one of these out-of-plane modes. The predictions are confirmed by simulations using state-of-the-art nonlinear Froude-Krylov and computational fluid dynamics models.

parametric resonance↗

Optimum spaceborne computer system design by simulation

A deterministic digital simulation model is described which models the Automatically Reconfigurable Modular Multiprocessor System (ARMMS), a candidate computer system for future manned and unmanned space missions. Use of the model as a tool in configuring a minimum computer system for a typical mission is demonstrated. The configuration which is developed as a result of studies with the simulator is optimal with respect to the efficient use of computer system resources, i.e., the configuration derived is a minimal one. Other considerations such as increased reliability through the use of standby spares would be taken into account in the definition of a practical system for a given mission.

Williams, T.↗

ESIM_DSN Web-Enabled Distributed Simulation Network

In this paper, the eSim(sup DSN) approach to achieve distributed simulation capability using the Internet is presented. With this approach a complete simulation can be assembled from component subsystems that run on different computers. The subsystems interact with each other via the Internet The distributed simulation uses a hub-and-spoke type network topology. It provides the ability to dynamically link simulation subsystem models to different computers as well as the ability to assign a particular model to each computer. A proof-of-concept demonstrator is also presented. The eSim(sup DSN) demonstrator can be accessed at http://www.jsc.draper.com/esim which hosts various examples of Web enabled simulations.

Bedrossian, Nazareth↗

Integration methods where force is obtained from the smoothed gravitational field.

Discussion of the possibilities to study the dynamics of collisionless stellar systems by condensing the large number of stars that such systems may contain into a smaller number of superparticles and using numerical or computer models to perform computer experiments simulating Vlasov phenomena by following the simultaneous motion of a large number of superparticles. A computer model for disks of stars and a two-dimensional rod model are considered.

Hohl, F.↗

NASA Models of Space Radiation Induced Cancer, Circulatory Disease, and Central Nervous System Effects

The risks of late effects from galactic cosmic rays (GCR) and solar particle events (SPE) are potentially a limitation to long-term space travel. The late effects of highest concern have significant lethality including cancer, effects to the central nervous system (CNS), and circulatory diseases (CD). For cancer and CD the use of age and gender specific models with uncertainty assessments based on human epidemiology data for low LET radiation combined with relative biological effectiveness factors (RBEs) and dose- and dose-rate reduction effectiveness factors (DDREF) to extrapolate these results to space radiation exposures is considered the current "state-of-the-art". The revised NASA Space Risk Model (NSRM-2014) is based on recent radio-epidemiology data for cancer and CD, however a key feature of the NSRM-2014 is the formulation of particle fluence and track structure based radiation quality factors for solid cancer and leukemia risk estimates, which are distinct from the ICRP quality factors, and shown to lead to smaller uncertainties in risk estimates. Many persons exposed to radiation on earth as well as astronauts are life-time never-smokers, which is estimated to significantly modify radiation cancer and CD risk estimates. A key feature of the NASA radiation protection model is the classification of radiation workers by smoking history in setting dose limits. Possible qualitative differences between GCR and low LET radiation increase uncertainties and are not included in previous risk estimates. Two important qualitative differences are emerging from research studies. The first is the increased lethality of tumors observed in animal models compared to low LET radiation or background tumors. The second are Non- Targeted Effects (NTE), which include bystander effects and genomic instability, which has been observed in cell and animal models of cancer risks. NTE's could lead to significant changes in RBE and DDREF estimates for GCR particles, and the potential effectiveness of radiation mitigator's. The NSRM- 2014 approaches to model radiation quality dependent lethality and NTE's will be described. CNS effects include both early changes that may occur during long space missions and late effects such as Alzheimer's disease (AD). AD effects 50% of the population above age 80-yr, is a degenerative disease that worsens with time after initial onset leading to death, and has no known cure. AD is difficult to detect at early stages and the small number of low LET epidemiology studies undertaken have not identified an association with low dose radiation. However experimental studies in mice suggest GCR may lead to early onset AD. We discuss modeling approaches to consider mechanisms whereby radiation would lead to earlier onset of occurrence of AD. Biomarkers of AD include amyloid beta (A(Beta)) plaques, and neurofibrillary tangles (NFT) made up of aggregates of the hyperphosphorylated form of the micro-tubule associated, tau protein. Related markers include synaptic degeneration, dentritic spine loss, and neuronal cell loss through apoptosis. Radiation may affect these processes by causing oxidative stress, aberrant signaling following DNA damage, and chronic neuroinflammation. Cell types to be considered in multi-scale models are neurons, astrocytes, and microglia. We developed biochemical and cell kinetics models of DNA damage signaling related to glycogen synthase kinase-3(Beta) (GSK3(Beta)) and neuroinflammation, and considered multi-scale modeling approaches to develop computer simulations of cell interactions and their relationships to A(Beta) plaques and NFTs. Comparison of model results to experimental data for the age specific development of A(Beta) plaques in transgenic mice will be discussed.

Cucinotta, Francis A.↗

Improving Schrödinger Equation Implementations with Gray Code for Adiabatic Quantum Computers

We reformulate the continuous-space Schrödinger equation in terms of spin Hamiltonians. For the kinetic energy operator, the critical concept facilitating the reduction in model complexity is the idea of position encoding. A binary encoding of position produces a spin-1/2 Heisenberg-like model and yields exponential improvement in space complexity when compared to classical computing. Encoding with a binary reflected Gray code (BRGC), and a Hamming-distance-2 Gray code (H2GC) reduces the model complexity down to the 𝑋⁢𝑍 and transverse Ising model, respectively. For 𝐴 qubits BRGC yields 2 𝐴 positions and is reduced to its 2-local form with O⁡(𝐴) ancillary qubits. H2GC yields 2 𝐴/2+1 positions with O⁡(𝐴 2 ) three-local penalty terms. We also identify the bijective mapping between diagonal unitaries and the Walsh series, producing the mapping of any real potential to a series of 𝑘 -local Ising models through the fast Walsh transform. Finally, in a finite volume, we provide some numerical evidence to support the claim that the total time needed for adiabatic evolution is protected by the infrared cutoff of the system. As a result, initial state preparation from a free-field wave function to an interacting system is expected to exhibit polynomial time complexity with volume and constant scaling with respect to lattice discretization for all encodings. For H2GC, if the evolution starts with the transverse Hamiltonian due to hardware restrictions, then penalties are dynamically introduced such that the low-lying spectrum reproduces the energy levels of the Laplacian. The adiabatic evolution of the penalty Hamiltonian is therefore sensitive to the ultraviolet scale. It is expected to exhibit polynomial time complexity with lattice discretization, or exponential time complexity with respect to the number of qubits given a fixed volume.

97 MATHEMATICS AND COMPUTING↗

Self-Pressurization and Spray Cooling Simulations of the Multipurpose Hydrogen Test Bed (MHTB) Ground-Based Experiment

This paper presents a CFD (computational fluid dynamics) model for simulating the self-pressurization of a large scale liquid hydrogen storage tank. In this model, the kinetics-based Schrage equation is used to account for the evaporative and condensing interfacial mass flows. Laminar and turbulent approaches to modeling natural convection in the tank and heat and mass transfer at the interface are compared. The flow, temperature, and interfacial mass fluxes predicted by these two approaches during tank self-pressurization are compared against each other. The ullage pressure and vapor temperature evolutions are also compared against experimental data obtained from the MHTB (Multipuprpose Hydrogen Test Bed) self-pressurization experiment. A CFD model for cooling cryogenic storage tanks by spraying cold liquid in the ullage is also presented. The Euler- Lagrange approach is utilized for tracking the spray droplets and for modeling interaction between the droplets and the continuous phase (ullage). The spray model is coupled with the VOF (volume of fluid) model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. Droplet ullage heat and mass transfer are modeled. The flow, temperature, and interfacial mass flux predicted by the model are presented. The ullage pressure is compared with experimental data obtained from the MHTB spray bar mixing experiment. The results of the models with only droplet/ullage heat transfer and with heat and mass transfer between the droplets and ullage are compared.

cryogenic fluid storage↗

Development of an Optimized Gasoline Surrogate Formulation for PACE Experiments and Simulations

New powertrain solutions are needed to address societal challenges stemming in part from a transportation sector which relies heavily on combustion of conventional hydrocarbon fuels like gasoline. One way to advance new solutions is through predictive simulations. Predictive simulations can potentially limit the extent of experimental validations, reduce time spent in engineering design cycles, unlock new strategies for high efficiency combustion with power density, and minimize tailpipe emissions. However, the simulation tools currently available are either too computationally expensive, inadequate in their accuracy, or a combination of the two. A DOE-funded consortium of national laboratories called the Partnership to Advance Combustion Engines (PACE) seeks to address this gap by rapidly delivering new knowledge and tools which enable market-competitive powertrain solutions for light-duty vehicles. Approaches to modeling combustion in powertrain systems typically incorporate computational fluid dynamics (CFD) simulations with chemical kinetic models. These CFD simulations generally use surrogate fuels featuring a limited number of existing components in a reduced kinetic model to limit computational costs. Such surrogate fuels often sacrifice matching several or more combustion and physical properties of the target gasoline fuel. Validation of surrogate fuels is also often only pursued for a small subset of standard metrics such as research or motor octane number (RON, MON). The purpose of this project is to develop an optimal E10 gasoline surrogate fuel suitable for tasks across PACE to facilitate rapid common analysis and progression toward consortium goals. This project received contributions from tasks led by eight PACE principal investigators. The project funding here reflects all tasks under Pitz, whose tasks also contributed to additional PACE projects. Based on the optimal gasoline surrogate fuel composition, a reduced chemical kinetic model will be shared with PACE researchers, industry, and the broader combustion community.

33 ADVANCED PROPULSION SYSTEMS↗

Race conditions and data partitioning: risks posed by common errors to reproducible parallel simulations

When parallel algorithms for simulation were introduced in the 1970s, their development and use interested only experts in parallel computation. This circumstance changed as multi-core processors became commonplace, putting a parallel computer into the hands of every modeler. A natural outcome is growing interest in parallel simulation among persons not intimately familiar with parallel computing. At the same time, parallel simulation tools continue to be developed with the implicit assumption that the modeler is knowledgeable about parallel programming. The unintended consequence is a rapidly growing number of users of parallel simulation tools that are unlikely to recognize when the interaction of race conditions, partitioning strategies, and simultaneous action in their simulation models make results non-reproducible, thereby calling into question the validity of conclusions drawn from the simulation data. Here, we illustrate the potential dangers of exposing parallel algorithms to users who are not experts in parallel computation with example models constructed using existing parallel simulation tools. By doing so, we hope to refocus tool developers on usability, even if this new focus incurs loss of some performance.

97 MATHEMATICS AND COMPUTING↗

Cycle-averaged dynamics of a periodically driven, closed-loop circulation model

Time-varying elastance models have been used extensively in the past to simulate the pulsatile nature of cardiovascular waveforms. Frequently, however, one is interested in dynamics that occur over longer time scales, in which case a detailed simulation of each cardiac contraction becomes computationally burdensome. In this paper, we apply circuit-averaging techniques to a periodically driven, closed-loop, three-compartment recirculation model. The resultant cycle-averaged model is linear and time invariant, and greatly reduces the computational burden. It is also amenable to systematic order reduction methods that lead to further efficiencies. Despite its simplicity, the averaged model captures the dynamics relevant to the representation of a range of cardiovascular reflex mechanisms. c2004 Elsevier Ltd. All rights reserved.

Non-NASA Center↗

Cometary activity, discrete outgassing areas, and dust-jet formation

Conceptual models for various types of features observed in cometary comae (jets, spirals, halos, fans, etc.), their computer simulation, and the hydrodynamic models for jet formation are critically reviewed, and evidence for anisotropic, strongly collimated flows of ejecta emanating from discrete active regions (vents) on the rotating cometary nuclei is presented. Techniques employed to generate synthetic comet images that simulate the features observed are described, and their relevance to the primary objects of coma-morphology studies is discussed. Modeling of temporal variations in the water emission from discrete active regions suggests that production curves asymmetric with respect to perihelion should be commonplace. Critical comparisons with the activity profiles of Enke's comet and with light curves of disappearing comets and comets that undergo outbursts are presented. Recent developments in the understanding of the processes that cause the nongravitational perturbations of cometary motions are reviewed, and the observed discontinuities are identified with the birth of new sources and/or deactivation of old vents.

Sekanina, Z.↗

Modular Manufacturing Simulator: Users Manual

The Modular Manufacturing Simulator (MMS) has been developed for the beginning user of computer simulations. Consequently, the MMS cannot model complex systems that require branching and convergence logic. Once a user becomes more proficient in computer simulation and wants to add more complexity, the user is encouraged to use one of the many available commercial simulation systems. The (MMS) is based on the SSE5 that was developed in the early 1990's by the University of Alabama in Huntsville (UAH). A recent survey by MSFC indicated that the simulator has been a major contributor to the economic impact of the MSFC technology transfer program. Many manufacturers have requested additional features for the SSE5. Consequently, the following features have been added to the MMS that are not available in the SSE5: runs under Windows, print option for both input parameters and output statistics, operator can be fixed at a station or assigned to a group of stations, operator movement based on time limit, part limit, or work-in-process (WIP) limit at next station. The movement options for a moveable operators are: go to station with largest WIP, rabbit chase where operator moves in circular sequence between stations, and push/pull where operator moves back and forth between stations. This user's manual contains the necessary information for installing the MMS on a PC, a description of the various MMS commands, and the solutions to a number of sample problems using the MMS. Also included in the beginning of this report is a brief discussion of technology transfer.

Source record↗

A Unique Computational Algorithm to Simulate Probabilistic Multi-Factor Interaction Model Complex Material Point Behavior

The Multi-Factor Interaction Model (MFIM) is used to evaluate the divot weight (foam weight ejected) from the launch external tanks. The multi-factor has sufficient degrees of freedom to evaluate a large number of factors that may contribute to the divot ejection. It also accommodates all interactions by its product form. Each factor has an exponent that satisfies only two points--the initial and final points. The exponent describes a monotonic path from the initial condition to the final. The exponent values are selected so that the described path makes sense in the absence of experimental data. In the present investigation, the data used was obtained by testing simulated specimens in launching conditions. Results show that the MFIM is an effective method of describing the divot weight ejected under the conditions investigated.

Chamis, Christos C.↗

Validation and Calibration of Energy Models with Real Vehicle Data from Chassis Dynamometer Experiments

Accurate estimation of vehicle fuel consumption typically requires detailed modeling of complex internal powertrain dynamics, often resulting in computationally intensive simulations. However, many transportation applications-such as traffic flow modeling, optimization, and control-require simplified models that are fast, interpretable, and easy to implement, while still maintaining fidelity to physical energy behavior. This work builds upon a recently developed model reduction pipeline that derives physics-like energy models from high-fidelity Autonomie vehicle simulations. These reduced models preserve essential vehicle dynamics, enabling realistic fuel consumption estimation with minimal computational overhead. While the reduced models have demonstrated strong agreement with their Autonomie counterparts, previous validation efforts have been confined to simulation environments. This study extends the validation by comparing the reduced energy model's outputs against real-world vehicle data. Focusing on the MidSUV category, we tune the baseline Autonomie model to closely replicate the characteristics of a Toyota RAV4. We then assess the accuracy of the resulting reduced model in estimating fuel consumption under actual drive conditions. Our findings suggest that, when the reference Autonomie model is properly calibrated, the simplified model produced by the reduction pipeline can provide reliable, semi-principled fuel rate estimates suitable for large-scale transportation applications.

42 ENGINEERING↗

Bridging particle and reactor scales in the simulation of biomass fast pyrolysis by coupling particle resolved simulation and coarse grained CFD-DEM

Efficient utilization of biomass is challenging due to the complexity of the feedstock at molecular, particle, and reactor scales. Direct coupling of particle scale model and reactor scale simulation is computationally infeasible. In this work, the results from a particle resolved simulation were used to calibrate the heat transfer and reaction kinetics of particles. A hybrid drag model was used to consider the different fluidization properties of sands and biomass particles. The computation cost was reduced using a coarse-grained Discrete Element Method (DEM). The simulated conversion rate, char yield, tar yield, and pyrolysis gas yield compare well with experiment. The residence time and axial distributions of biomass were also analyzed. This novel multi-scale method provides an efficient and accurate tool for the modeling of biomass pyrolysis reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗