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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Application of a vectorized particle simulation in high-speed near-continuum flow

An efficient particle simulation technique, developed for use on vector architecture based supercomputers for studying hypersonic rarefied gas flows is employed to simulate the complex wake generated by Mach six flow over a 10 deg half-angle wedge for freestream Reynolds numbers of 1780 and 3560. Data obtained are compared against higher Reynolds number experimental results. Simulations utilized as many as 10 to the 5th computational cells and 10 to the 7th simulated particles having power-law interaction potentials. A code performance of 1.8-2.4 microsec of Cray-2 CPU time to process a single particle per timestep is achieved. Diffuse adiabatic and isothermal wedge surface models are used in this investigation. Although the wedge geometry is two-dimensional, the simulation incorporates a width-wise direction, resulting in a three-dimensional computation.

Woronowicz, Michael S.↗
NASA NTRS2024

Large Interferometer For Exoplanets (LIFE) XIII. The value of Combining Thermal Emission and Reflected Light for the Characterization of Earth Twins

Context. Following the recommendations to NASA (in the Astro2020 Decadal survey) and ESA (through the Voyage2050 process), the search for life on exoplanets will be a priority in the next decades. Two concepts for direct imaging space missions are being developed for this purpose: the Habitable Worlds Observatory (HWO) and the Large Interferometer for Exoplanets (LIFE). These two concepts operate in different spectral regimes: HWO is focused on reflected light spectra in the ultraviolet, visible, and near-infrared (UV/VIS/NIR), while LIFE will operate in the mid-infrared (MIR) to capture the thermal emission of temperate exoplanets. Aims. In this study, we aim to assess the potential of HWO and LIFE to characterize a cloud-free Earth twin orbiting a Sun-like star at a distance of 10 pc, both as separate missions and in synergy with each other. We aim to quantify the increase in information that can be gathered by joint atmospheric retrievals on a habitable planet. Methods. We performed Bayesian retrievals on simulated data obtained by an HWO-like mission and a LIFE-like one separately, then jointly. We considered the baseline spectral resolutions currently assumed for these concepts and used two increasingly complex noise simulations, obtained using state-of-the-art noise simulators. Results. An HWO-like concept would allow one to strongly constrain H 2 O, O 2 , and O 3 in the atmosphere of a cloud-free Earth twin, while the atmospheric temperature profile is not well constrained (with an average uncertainty ≈100 K). LIFE-like observations would strongly constrain CO 2 , H 2 O, and O 3 and provide stronger constraints on the thermal atmospheric structure and surface temperature (down to ≈10 K uncertainty). For all the investigated scenarios, both missions would provide an upper limit on CH 4 . A joint retrieval on HWO and LIFE data would accurately define the atmospheric thermal profile and planetary parameters. It would decisively constrain CO 2 , H 2 O, O 2 , and O 3 and find weak constraints on CO and CH 4 . The significance of the detection is in all cases greater than or equal to the single-instrument retrievals. Conclusions. Both missions provide specific information that is relevant for the characterization of a terrestrial habitable exoplanet, but the scientific yield can be maximized by considering synergistic studies of UV/VIS/NIR+MIR observations. The use of HWO and LIFE together will provide stronger constraints on biosignatures and life indicators, with the potential to be transformative for the search for life in the Universe.

E Alei↗
NASA NTRS2013

Sample Analysis at Mars Instrument Simulator

The Sample Analysis at Mars Instrument Simulator (SAMSIM) is a numerical model dedicated to plan and validate operations of the Sample Analysis at Mars (SAM) instrument on the surface of Mars. The SAM instrument suite, currently operating on the Mars Science Laboratory (MSL), is an analytical laboratory designed to investigate the chemical and isotopic composition of the atmosphere and volatiles extracted from solid samples. SAMSIM was developed using Matlab and Simulink libraries of MathWorks Inc. to provide MSL mission planners with accurate predictions of the instrument electrical, thermal, mechanical, and fluid responses to scripted commands. This tool is a first example of a multi-purpose, full-scale numerical modeling of a flight instrument with the purpose of supplementing or even eliminating entirely the need for a hardware engineer model during instrument development and operation. SAMSIM simulates the complex interactions that occur between the instrument Command and Data Handling unit (C&DH) and all subsystems during the execution of experiment sequences. A typical SAM experiment takes many hours to complete and involves hundreds of components. During the simulation, the electrical, mechanical, thermal, and gas dynamics states of each hardware component are accurately modeled and propagated within the simulation environment at faster than real time. This allows the simulation, in just a few minutes, of experiment sequences that takes many hours to execute on the real instrument. The SAMSIM model is divided into five distinct but interacting modules: software, mechanical, thermal, gas flow, and electrical modules. The software module simulates the instrument C&DH by executing a customized version of the instrument flight software in a Matlab environment. The inputs and outputs to this synthetic C&DH are mapped to virtual sensors and command lines that mimic in their structure and connectivity the layout of the instrument harnesses. This module executes, and thus validates, complex command scripts prior to their up-linking to the SAM instrument. As an output, this module generates synthetic data and message logs at a rate that is similar to the actual instrument.

Benna, Mehdi↗
NASA NTRSDate not supplied

Enabling Simulation Interoperability between International Standards in the Space Domain

Today, the design and development of space systems are conducted cooperatively by historical space agencies in this area such as NASA, ESA, Roscosmos, and JAXA together with their industrial partners. The space system lifecycle is characterized by high costs, uncertain conditions, and dangerous scenarios. To mitigate these issues, space agencies rely heavily on Modelling and Simulation as a key technology to support the analysis, design, and operation of space systems. To support large-scale distributed simulations, the scientific community has developed several standards to support the reuse and interoperability of simulation models such as IEEE 1516 High-Level Architecture (HLA), Real-time Platform Reference Federation Object Model (RPR FOM), Simulation Model Portability (SMP), and the novel Space Reference Federation Object Model (SpaceFOM). While the SpaceFOM standard has been specifically conceptualized for handling space systems, the other ones are more general-purpose and can be used to design and simulate generic complex systems. As a consequence, there is a lake of rules and guidelines to enable interoperability among these standards. The paper presents solutions and experiences for enabling interoperability and transferability of HLA, RPR FOM, and SMP simulation models with SpaceFOM.

Simulation↗
NASA NTRS2000

On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal Response

This paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.

Jen, Chian-Li↗
NASA NTRS2014

Designing Liquid Rocket Engine Injectors for Performance, Stability, and Cost

NASA is using computational fluid dynamics (CFD) simulations to lower the cost and increase the performance and stability of fuel injector designs for next-generation liquid rocket engines (LREs). The Loci-STREAM CFD code is used to simulate the complex combustion processes inside the LRE. These analyses enable efficient evaluation of the performance and stability characteristics of injector design concepts, while decreasing reliance on the costly test-fail-fix cycle of traditional design approaches. These injector simulations were recently employed as a key part of the design process for an Advanced Booster concept for NASA's heavy-lift Space Launch System (SLS).

Westra, Douglas G.↗
NASA NTRSDate not supplied

Material Property Estimation in Thin Battery Components Using Guided Wave Measurement, Experimental Dispersion Curve Extraction and Finite Element Modeling

At NASA, we are investigating nondestructive evaluation (NDE) and structural health monitoring (SHM) techniques to detect precursors of thermal runaway failure in lithium metal based lithium ion batteries (LIB). The approach is centered on computational simulation models to guide inspection and aid in interpretation of results. Since lithium metal LIBs have combinations of solid and fluid-filled porous materials, obtaining accurate material properties is both challenging and critical for successful simulation of battery inspection. To this end, we investigated a multi-verification approach for material characterization of thin battery components. First, a laser Doppler vibrometer (LDV) was used to measure guided wave fields in thin (microns-thick) battery components subject to broadband excitation. The time-space wavefield data was converted to frequency-wave number data to extract guided wave dispersion curves. A data visualization and post processing graphics user interface (GUI) was developed at NASA to aid the data exploration and analysis. Due to the thinness of the samples, low frequency-thickness-product plate wave approximations allowed for the calculation of closed-form solutions for material elastic property estimation. These approximations were then verified by calculating the Lamb wave solutions using the previously obtained material properties. Finally, the estimated elastic material properties were implemented in a COMSOL simulation model, and dispersion curves were extracted from simulation results. The dispersion curves and derived material properties were then compared to the analysis results from the experimental data. These comparisons informed on the accuracy of the measured material properties and helped demonstrate the accuracy of the finite element analysis (FEA) computational models. This assessment will prove vital when we start simulating more complex multi-layer components and poroelastic media. This paper gives a brief background of the problem space, outlines the workflow for data analysis and verification, shows results from the workflow, and gives an overview of future plans for simulation of lithium metal LIB inspection.

Peter Juarez↗
NASA NTRSDate not supplied

Computational Fluid Dynamics Simulation of the Swordfish Oxygen/Methane Rotating Detonation Rocket Engine

Rotating Detonation Rocket Engines (RDREs) provide several theoretical performance benefits over traditional deflagration combustion rocket engines. RDREs can potentially generate higher specific impulse (ISP) for a given propellant combination enabling significant consumable mass savings for a spaceflight vehicle. Conversely, RDREs are a relatively new technology with a shallower analytical modeling base compared to traditional combustion engine architectures. In this work, we utilize time-accurate, Computational Fluid Dynamics (CFD) modeling to simulate the complex fluid environment inside an RDRE combustion chamber and propellant manifolds. The selected engine of study is the Swordfish RDRE which was developed and tested and at the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC). CFD simulations were conducted using the as-tested Swordfish geometry and conditions to facilitate comparison between the analytical predictions and experimental results.

Brian R. Richardson↗
NASA NTRS2000

The Numerical Propulsion System Simulation: An Overview

Advances in computational technology and in physics-based modeling are making large-scale, detailed simulations of complex systems possible within the design environment. For example, the integration of computing, communications, and aerodynamics has reduced the time required to analyze major propulsion system components from days and weeks to minutes and hours. This breakthrough has enabled the detailed simulation of major propulsion system components to become a routine part of designing systems, providing the designer with critical information about the components early in the design process. This paper describes the development of the numerical propulsion system simulation (NPSS), a modular and extensible framework for the integration of multicomponent and multidisciplinary analysis tools using geographically distributed resources such as computing platforms, data bases, and people. The analysis is currently focused on large-scale modeling of complete aircraft engines. This will provide the product developer with a "virtual wind tunnel" that will reduce the number of hardware builds and tests required during the development of advanced aerospace propulsion systems.

Lytle, John K.↗
NASA NTRS1999

The Numerical Propulsion System Simulation: A Multidisciplinary Design System for Aerospace Vehicles

Advances in computational technology and in physics-based modeling are making large scale, detailed simulations of complex systems possible within the design environment. For example, the integration of computing, communications, and aerodynamics has reduced the time required to analyze ma or propulsion system components from days and weeks to minutes and hours. This breakthrough has enabled the detailed simulation of major propulsion system components to become a routine part of design process and to provide the designer with critical information about the components early in the design process. This paper describes the development of the Numerical Propulsion System Simulation (NPSS), a multidisciplinary system of analysis tools that is focussed on extending the simulation capability from components to the full system. This will provide the product developer with a "virtual wind tunnel" that will reduce the number of hardware builds and tests required during the development of advanced aerospace propulsion systems.

Lytle, John K.↗
NASA NTRS2022

What Is Unusual About the Third Largest Geomagnetic Storm of Solar Cycle 24?

We report on the solar and interplanetary (IP) causes of the third largest geomagnetic storm (26 August 2018) in solar cycle 24. The underlying coronal mass ejection (CME) originating from a quiescent filament region becomes a 440 km/s magnetic cloud (MC) at 1 au after ∼5 days. The prolonged CME acceleration (for ∼24 hr) coincides with the time profiles of the post-eruption arcade intensity and reconnected flux. Chen et al. (2019, https://doi.org/10.3847/1538-4357/ab3f36) obtain a lower speed since they assumed that the CME does not accelerate after ∼12 hr. The presence of multiple coronal holes near the filament channel and the high-speed wind from them seem to have the combined effect of producing complex rotation in the corona and IP medium resulting in a high-inclination MC. The Dst time profile in the main phase steepens significantly (rapid increase in storm intensity) coincident with the density increase (prominence material) in the second half of the MC. Simulations using the Comprehensive Inner Magnetosphere-Ionosphere model show that a higher ring current energy results from larger dynamic pressure (density) in MCs. Furthermore, the Dst index is highly correlated with the main-phase time integral of the ring current injection that includes density, consistent with the simulations. A complex temporal structure develops in the storm main phase if the underlying MC has a complex density structure during intervals of southward IP magnetic field. We conclude that the high intensity of the storm results from the prolonged CME acceleration, complex rotation of the CME flux rope, and the high density in the 1-au MC.

N. Gopalswamy↗
NASA NTRS1983

Data flow methods for dynamic system simulation - A CSSL-IV microcomputer network interface

A major problem in employing networks of microcomputers for the real-time simulation of complex systems is to allocate computational tasks to the various microcomputers in such a way that idle time and time lost in interprocess communication is minimized. The research reported in this paper is directed to the development of a software interface between a higher-level simulation language and a network of microcomputers. A CSSL-IV source program is translated to a data flow graph. This graph is then analyzed automatically so as to allocate computing tasks to the various processors.

Makoui, A.↗
NASA NTRS1982

Digital system for structural dynamics simulation

State-of-the-art digital hardware and software for the simulation of complex structural dynamic interactions, such as those which occur in rotating structures (engine systems). System were incorporated in a designed to use an array of processors in which the computation for each physical subelement or functional subsystem would be assigned to a single specific processor in the simulator. These node processors are microprogrammed bit-slice microcomputers which function autonomously and can communicate with each other and a central control minicomputer over parallel digital lines. Inter-processor nearest neighbor communications busses pass the constants which represent physical constraints and boundary conditions. The node processors are connected to the six nearest neighbor node processors to simulate the actual physical interface of real substructures. Computer generated finite element mesh and force models can be developed with the aid of the central control minicomputer. The control computer also oversees the animation of a graphics display system, disk-based mass storage along with the individual processing elements.

Krauter, A. I.↗
NASA NTRS1989

Advances in fluid dynamics

Various papers on advances in fluid dynamics are presented. Individual topics addressed include: nonunique solutions of the Euler equations; numerical solution of the biharmonic equation using a spectral multigrid method; finite-volume shape and placement for efficiency, accuracy, and physics; NND schemes and their application to numerical simulation of complex plume flow problems; symbolic analysis and computational algorithm construction; and velocity and mass flux distribution measurements of spherical glass beads in air flow in a 90-deg vertical-to-horizontal bend. Also discussed are: hyperbolic solution adaptive mesh generation; progress and future directions in CFD; numerical simulation of shock focusing; microbubble formation and splitting in a turbulent boundary layer for turbulence reduction; numerical study of spherical Taylor-Couette flow, trajectories of vortex lines beneath a free surface or above a plane; and a mathematical model for response of the coronary circulation to high sustained gravitational force fields.

Ballhaus, W. F., Jr.↗
NASA NTRS2022

Predicting Unreinforced Fabric Mechanical Behavior with Recurrent Neural Networks

Unreinforced woven fabrics are widely employed in various high-performance applications, including parachute deployment systems, airbags, and ballistic armor. The analysis of such materials is inherently complex due to the multiscale structure of these materials, and the dependence of macroscale behavior on changes that occur at lower scales. Previously, NASA’s Multiscale Analysis Tool (NASMAT) showed its capability in predicting unreinforced fabric behavior at the macroscale by capturing finite rotations that occur at the mesoscale. Though effective, the tool can face high computational cost for large, complex problems, motivating the need for the development of a surrogate model that can capture the same behavior. A recurrent neural network (RNN) was developed and trained on virtual NASMAT data to mimic the physics-based solutions while improving the computational runtime. The architecture of the RNN to best simulate the fabric behavior was carefully crafted based on heuristic knowledge of predicting physics-based temporal data, manual hyperparameter case studies, and Hyperband optimization.. The resultant model was able to predict a variety of stress-strain curves for fabrics with different mesoscale geometries, and was further validated by comparing to experimental data for the K706 style Kevlar plain-weave fabric, demonstrating the ability of the model to effectively capture the geometric changes in the fabric without explicitly calculating them, as is done in NASMAT. Furthermore, the tool showed its ability to improve on the runtime by a factor of 10 for fabric solutions compared to the multiscale tool, which would further enable the simulation of complex loading scenarios on unreinforced fabrics.

Fabric↗
NASA NTRSDate not supplied

Combining Data with Physical Knowledge for Uncertainty Quantification in Certification and Reliability Analysis

Unifying empirical data with predictive models can enable engineering cost-savings through certification by analysis and reliability-based design. Both concepts require rigorous uncertainty quantification (UQ) and robust understanding and treatment of relevant physics. Combining sampling-based UQ algorithms with high-fidelity simulations creates a computational bottleneck that is often alleviated through the use of machine learning (ML). ML can be used to create computationally efficient surrogates for simulations of complex or high-dimensional physical interactions (e.g., multi-phase interactions associated with melt pools in laser powder bed fusion or spatially-dependent material properties in functionally graded materials). However, negative side effects of ML may include a lack of interpretability and negative correlation between event rarity and simulation accuracy due to a lack of training data. As such, it is important to infuse ML algorithms with physics-based guardrails to provide confidence in their predictions. This talk will provide a brief review of recent NASA research at this intersection of physics-based simulation, ML, and UQ with a focus on certification and reliability analysis.

uncertainty quantification↗
NASA NTRS2023

Applicability of the Nasa Galactic Cosmic Ray Simulator for Mice, Rats, and Minipigs

Space radiation poses multiple health risks to astronauts including cancer, cardiovascular disease, and damage to the central nervous system. Radiation from galactic cosmic rays (GCR) is the main source of these risks for missions beyond low Earth orbit to the moon and beyond. A galactic cosmic ray simulator (GCRsim) was developed at the NASA Space Radiation Laboratory to better understand and mitigate these risks by simulating the complex mixed field of the GCR environment at a ground-based facility. The GCRsim delivers a radiation field to cell and animal models in a laboratory setting that is comparable to the shielded radiation environment within internal organs of astronauts in deep space missions. Previous verification studies using Monte Carlo simulations with mouse (Digimouse) and rat (Digirat) digital phantoms showed that the GCRsim yields acceptable dose homogeneity within the internal organs of these animals. Spectral characteristics of the intended space radiation environment are also accurately reproduced at radiosensitive sites in both phantoms. In this work, similar Monte Carlo simulations were performed in a minipig model (Digipig) to show the applicability and limitations of the current GCRsim for larger animal model systems. The results showed dose homogeneity in internal organs of the three animal models with GCRsim irradiation. While slightly lower average doses were seen in the minipig compared to the external beam dose, the individual voxel doses in slices of the phantoms were found to be within 6%–8% of the average voxel dose, establishing that the GCRsim can still provide a relatively homogeneous irradiation within larger animals. Furthermore, simulated dose and fluence spectral results across the relevant linear energy transfer (LET) range agreed well with the reference field in the most relevant regions of the spectra, further verifying that the GCRsim beam represents the reference field in larger animals.

Galactic cosmic rays↗
NASA NTRS2004

Advanced Integration Matrix Education Outreach

The Advanced Integration Matrix (AIM) will design a ground-based test facility for developing revolutionary integrated systems for joint human-robotic missions in order to study and solve systems-level integration issues for exploration missions beyond Low Earth Orbit (LEO). This paper describes development plans for educational outreach activities related to technological and operational integration scenarios similar to the challenges that will be encountered through this project. The education outreach activities will provide hands-on, interactive exercises to allow students of all levels to experience design and operational challenges similar to what NASA deals with everyday in performing the integration of complex missions. These experiences will relate to and impact students everyday lives by demonstrating how their interests in science and engineering can develop into future careers, and reinforcing the concepts of teamwork and conflict resolution. Allowing students to experience and contribute to real-world development, research, and scientific studies of ground-based simulations for complex exploration missions will stimulate interest in the space program, and bring NASA's challenges to the student level. By enhancing existing educational programs and developing innovative activities and presentations, AIM will support NASA s endeavor to "inspire the next generation of explorers.. .as only NASA can."

Paul Heather L.↗