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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 343 records · Page 19

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DOE OSTI2022

A particle resolved simulation approach for studying shock interactions with moving, colliding solid particles

This work applies a new combination of techniques for the fully resolved simulation of compressible, gas–particle multiphase flows. Here, the adaptive wavelet collocation method is used to dynamically, and efficiently, adapt the computational grid to localized flow features and the particles. A characteristic-based volume penalization method that imposes arbitrary Dirichlet, Neumann, or Robin-type immersed boundary conditions, is used to enforce the no-slip condition at particle surfaces. A hard-sphere collision model is applied to capture the particle–particle collisions. Proof of concept test cases are presented, showcasing the dynamic grid adaptation and fully resolved two-way coupling between the phases that is possible with this approach. Results for a shock-driven single cylinder under viscous and inviscid conditions are presented along with a demonstration of a shock interacting with a cloud of randomly distributed cylinders and spheres.

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DOE OSTI2020

Connected Vehicle-Based Traffic Signal Coordination

This study presents a connected vehicles (CVs)-based traffic signal optimization framework for a coordinated arterial corridor. The signal optimization and coordination problem are first formulated in a centralized scheme as a mixed-integer nonlinear program (MINLP). The optimal phase durations and offsets are solved together by minimizing fuel consumption and travel time considering an individual vehicle’s trajectories. Due to the complexity of the model, we decompose the problem into two levels: an intersection level to optimize phase durations using dynamic programming (DP), and a corridor level to optimize the offsets of all intersections. In order to solve the two-level model, a prediction-based solution technique is developed. The proposed models are tested using traffic simulation under various scenarios. Compared with the traditional actuated signal timing and coordination plan, the signal timing plans generated by solving the MINLP and the two-level model can reasonably improve the signal control performance. When considering varies vehicle types under high demand levels, the proposed two-level model reduced the total system cost by 3.8% comparing to baseline actuated plan. MINLP reduced the system cost by 5.9%. It also suggested that coordination scheme was beneficial to corridors with relatively high demand levels. For intersections with major and minor street, coordination conducted for major street had little impacts on the vehicles at the minor street.

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DOE OSTI2021

Characterization of mechanical discontinuities based on data-driven classification of compressional-wave travel times

Wave propagation and diffusive transport phenomena are influenced by the mechanical discontinuities in material. Here this study shows that certain bulk properties of the network of low-velocity mechanical discontinuities (e.g. air-filled cracks) in a material can be characterized by processing compressional-wave travel times using traditional data-driven classification techniques. To that end, we perform three tasks in chronological order: (1) use the discrete fracture network (DFN) method to create two-dimensional (2D) numerical models of crack-bearing material embedded with various types of low-velocity mechanical discontinuities, (2) use the fast marching method (FMM) to simulate the propagation of the wave/diffusion front from a single source through the 2D crack-bearing material to multiple receivers placed on the boundary of the material, and (3) train 9 data-driven classifiers to characterize the crack-bearing materials (i.e. bulk properties of the network of mechanical discontinuities in the crack-bearing material) by learning from the simulations of travel times detected by multiple receivers placed around the crack-bearing material. The classifiers identified the orientation, spatial distribution, and dispersion of the low-velocity mechanical discontinuities. Voting classifier performs the best among the 9 classifiers. For the characterization of bulk dispersion and distribution of discontinuities, the sensors located on the adjacent boundaries are more important; whereas for the characterization of bulk orientation of discontinuities, the sensors located on the opposite side are more important.

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NASA NTRS1982

Experiments on identification and control of inflow disturbances in contracting streams

Vorticity from all surfaces and isolated objects in the vicinity of the fan intake, including the outside surfaces of the fan housing, were identified as the major sources for disturbances leading to blade passing frequency noise. The previously proposed mechanism based on atmospheric turbulence is refuted. Flow visualization and hot wire techniques were used in three different facilities to document the evolution of various types of disturbances, including the details of the mean flow and turbulence characteristics. The results suggest that special attention must be devoted to the design of the inlet and that geometric modeling may not lead to adequate simulation of the in flight characteristics. While honeycomb type flow manipulators appear to be effective in reducing some of the disturbances, higher pressure drop devices that generate adequate turbulence, for mixing of isolated nonuniformities, may be necessary to suppress the remaining disturbances. The results are also applicable to the design of inlets of open return wind tunnels and similar flow facilities.

Lee, A. H.↗

DOE OSTI2024

Advanced Cross Section Library Generation using Reduced Order Models

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

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DOE OSTI2024

Comparison of excess free energy at an interface according to the applied interpolation scheme for elasticity: A phase-field method

Phase-field modeling is an effective simulation technique for modeling microstructure evolution of elastically anisotropic systems. To introduce the elastic energy contribution in a phase field model, an interpolation scheme is used to define the mechanical properties within the phases and across the continuous interface. Several existing interpolation schemes introduce a potential excess elastic energy at the interface, which undesirable effect on microstructure evolution needs to be evaluated. In this study, we focused on three interpolation schemes including Khachaturyan’ scheme (KHS), Voigt–Taylor’s scheme (VTS), and Steinbach–Apel’s scheme (SAS). Comparisons of these schemes’ performances were performed in three configuration types using the MOOSE (Multiphysics Object-Oriented Simulation Environment) framework: bi-crystal, isotropic particle-matrix and anisotropic particle-matrix. The contribution of excess elastic energy on the interface energy as a function of interface width and the computational time to steady-state were evaluated in these three configurations. SAS introduces the lowest excess elastic energy contribution and the VTS has the biggest contribution amongst the considered schemes. Moreover, when modeling precipitation in an anisotropic elastic material, the SAS approach seems to predict more physical convex shapes during growth, making it preferable to KHS and VTS. Finally, as currently implemented, SAS requires the largest computational time and KHS requires the smallest time to reach steady-state amongst the considered schemes.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Utilizing biochars to stabilize mercury in contaminated floodplain sediment: Implications on mercury remediation

Major weather events contribute to the mobility and remobilization of legacy mercury (Hg) contamination and sequestration within sediments. Remediation using biochar as a soil amendment is a useful technique to immobilize and decrease Hg toxicity. This study explored whether biochar application is effective at stabilizing labile mercury (LaHg) from floodplain sediment. Controlled mesocosms simulating contamination events and flooding conditions were conducted. Floodplain sediment, which experiences annual periodic flooding, was collected. Sediment was spiked with inorganic Hg, applied with different types of biochar, and experienced simulated flooding events. Four types of biochar, pure rice husk (RH), pure peanut hull (PH), sulfur-modified rice husk (SMRH), and sulfur-modified peanut hull (SMPH), were applied at 10 and 40 g/kg rates (i.e., RH 10, RH 40; PH 10, PH 40, SMRH 10, SMRH 40, SMPH 10, SMPH 40). Total Hg, methylmercury, and LaHg concentrations were analyzed by coupling with redox potential measurements. Results indicate that SMRH 10, PH 10, PH 40, SMPH 10, and SMPH 40 successfully remediate Hg by stabilizing and reducing LaHg species from floodplain sediment. However, a high Hg methylation potential was observed with unsulfated and sulfated peanut hulls (PH 10, PH 40, SMPH 10, and SMPH 40), as they tend to create a reducing microenvironment that favors sulfate reduction reactions. Additionally, sulfur-modified biochar tends to promote Hg methylation potential at high application rates (i.e., 40 g/kg). We thus recommend using SMRH at a relatively low application rate (SMRH 10) for the remediation of Hg from floodplain sediment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗

NASA NTRS1975

STOL aircraft transient ground effects. Part 2: Experimental techniques feasibility study

Procedures for simulating transient effects associated with STOL aircraft landings and takeoffs were examined and a basis was developed for selection of an experimental approach based on consideration of simulation requirements, experimental techniques, facilities, and costs. The results are generally applicable to STOL aircraft employing any of the following powered lift systems: externally blown flap, upper surface blown flap, augmentor wing, or internally ducted jet flap. Scaling relationships were developed to apply the simulation requirements to model test situations. Procedures for the derivation of aerodynamic forces from the measured data were discussed. Various means of expressing the aerodynamic data in forms convenient for use in performance or stability and control applications were described. Five different experimental techniques were presented that depend on two different types of experimental facilities, wind tunnels and test tracks, and involving different types of model motion, and factors pertinent to selection were summarized.

Crowder, J. P.↗

NASA NTRS1994

Ways to Increase Launch Velocities of 2-Stage Gas Guns

The amount of space debris is rapidly increasing and the debris is distributed over a wide variety of orbits. Satellites, manned space vehicles and space stations will have to pay increasing attention to the dangers of impacts with space debris. Various armoring techniques (i.e., double or triple layer armor) will have to tested extensively to determine the most effective armor per unit weight. Intersecting near-earth orbits can lead to impact velocities up to 15 km/sec. Conventional two-stage light gas guns can launch intact, controlled-shape projectiles with a density of 1.2 gm/cc and length- to-diameter ratios of 0.5-1.0 at velocities up to 8-9 km/sec. Higher velocities (10-11 km/sec) can be obtained' for very light projectiles. The higher launch velocities tend to be very severe on the high pressure coupling and barrel of the gun and lead to short component lifetimes. Clearly, the ability to raise the launch velocity of a gun (for reasonably massive projectile shapes) from 8-9 km/sec to 11-13 km/sec (or higher), without reduction of component lifetimes, would have significant benefits. This would allow much better simulation of the higher velocity debris impacts as well as better simulation of high speed re-entry into planetary atmospheres. Several techniques for increasing the launcher muzzle velocity above 8-9 km/sec have been studied using CFD simulations and appear to offer the potential for significant gains. The first technique is to use multiple compressions, instead of a single compression, in the pump tube of the light gas gun. In a sense, this is a kind of pre-heating of the gas in the pump tube; other types of pre-heating have yielded disappointing results in the past. The dynamics of the multiple compression pump tube is very different, however, from the earlier techniques, where the pump tube was typically heated ohmically before the gun 2 cycle was started. In this paper, we present CFD calculations that show that significant increases in muzzle velocity can be obtained with multiple compressions in the pump tube. With a conventional two-stage gun, an important limitation to obtaining higher velocities is friction and heat transfer to the barrel, which typically has a length- to- diameter ratio of 200-400. These viscous losses greatly reduce the effectiveness of the regions of the barrel far removed from the second stage breech. We have studied computationally the effect of adding an additional breech (or breeches) along the barrel to reduce these viscous losses. Velocity increases from 6.5 to 7.2 km/sec have been obtained using the main breech and one additional breech. In these results, both breeches were operated with hydrogen, heated electrothermally. We have also studied a gun geometry where the main breech is operated in the conventional manner, using piston compression. The additional breech is operated either with electrothermal heating or heating by using a high explosive charge in a novel geometry. The latter option provides very effective compression, heating and acceleration of the hydrogen working gas and is fully reusable. Calculations are presented which show that very substantial increases in muzzle velocity can be obtained this way, without overstressing the projectile or the 'gun. The third technique studied is to add a section of ram accelerator tube after the barrel to further accelerate the projectile. The ram accelerator used here is not the conventional premixed gas ram accelerator, but a new technique using high explosive as the energy source and pure hydrogen as the working gas in a geometry which can be made fully reusable. Preliminary results with this new rain accelerator geometry were presented and showed that stable ram accelerator drive can be established. Herein, detailed calculations axe presented which show that substantial velocity increases can be obtained using this ram accelerator technique in tandem with a conventional light gas gun.

Bogdanoff, David W.↗

NASA NTRS2013

Development of a Prototype Algal Reactor for Removing CO2 from Cabin Air

Controlling carbon dioxide in spacecraft cabin air may be accomplished using algal photobioreactors (PBRs). The purpose of this project was to evaluate the use of a commercial microcontroller, the Arduino Mega 2560, for measuring key phot~ioreactor variables: dissolved oxygen, pH, temperature, light, and carbon dioxide. The Arduino platform is an opensource physical computing platform composed of a compact microcontroller board and a C++/C computer language (Arduino 1.0.5). The functionality of the Arduino platform can be expanded by the use of numerous add-ons or 'shields'. The Arduino Mega 2560 was equipped with the following shields: datalogger, BNC shield for reading pH sensor, a Mega Moto shield for controlling CO2 addition, as well as multiple sensors. The dissolved oxygen (DO) probe was calibrated using a nitrogen bubbling technique and the pH probe was calibrated via an Omega pH simulator. The PBR was constructed using a 2 L beaker, a 66 L box for addition of CO2, a micro porous membrane, a diaphragm pump, four 25 watt light bulbs, a MasterFiex speed controller, and a fan. The algae (wild type Synechocystis PCC6803) was grown in an aerated flask until the algae was dense enough to used in the main reactor. After the algae was grown, it was transferred to the 2 L beaker where CO2 consumption and O2 production was measured using the microcontroller sensor suite. The data was recorded via the datalogger and transferred to a computer for analysis.

Patel, Vrajen↗

NASA NTRS2018

A Performance-Based Comparison of Deep-Space Navigation using Optical-Communication and Conventional Navigation Techniques: Small Body Missions

Optical communications may be used in future NASA deep-space missions, resulting in much higher data transfer rates. Those optical communication links could also be used for navigation purposes. The performance of deep-space navigation for an asteroid flyby mission using ground-based optical tracking and conventional navigation techniques was investigated in this work. We present the results of variety of asteroid flyby scenarios including low phase and high phase approach angle flybys, one slow flyby in a Trojan tour mission, and also one slow flyby in a Psyche mission. In this task, four different types of observables were simulated, namely ground-based radiometric, spacecraft on-board optical, ground-based optical tracking of spacecraft (astrometry and 2-way range magnitude), and ground-based asteroid astrometry. Different combinations of these four types of observables were compared with currently in-practice ground-based radiometric/on-board optical measurements. The results showed that the ground-based optical tracking is promising and could be a potential candidate for future deep-space navigation. Precise astrometry is not possible for active comets.

McCandless, Sara Elizabeth↗

NASA NTRS2018

A Performance-Based Comparison of Deep-Space Navigation using Optical-Communication and Conventional Navigation Techniques: Small Body Missions

McCandless, Sarah Elizabeth↗

NASA NTRS2004

Electrochemical Impedance Spectroscopy of Alloys in a Simulated Space Shuttle Launch Environment

Type 304L stainless steel (304L SS) tubing is currently used in various supply lines that service the Orbiter at NASA's John F. Kennedy Space Center Launch Pads in Florida (USA). The atmosphere at the Space Shuffle launch site is very corrosive due to a combination of factors, such as the proximity of the Atlantic Ocean and the concentrated hydrochloric acid produced by the fuel combustion reaction in the solid rocket boosters. The acidic chloride environment is aggressive to most metals and causes severe pitting in many of the common stainless steel alloys such as 304L SS. Stainless steel tubing is susceptible to pitting corrosion that can cause cracking and rupture of both high-pressure gas and fluid systems. Outages in the systems where failures occur can impact the normal operation of the shuttle and launch schedules. The use of a more corrosion resistant tubing alloy for launch pad applications would greatly reduce the probability of failure, improve safety, lessen maintenance costs, and reduce downtime. A study which included ten alloys was undertaken to find a more corrosion resistant material to replace the existing 304L SS tubing. The study included atmospheric exposure at NASA's John F. Kennedy Space Center outdoor corrosion test site near the launch pads and electrochemical measurements in the laboratory which included DC techniques and electrochemical impedance spectroscopy (EIS). This paper presents the results from EIS measurements on three of the alloys: AL6XN (UN N08367), 254SMO (UNS S32l54), and 304L SS (UNS S30403). Type 304L SS was included in the study as a control. The alloys were tested in three electrolyte solutions which consisted of neutral 3.55% NaC1, 3.55% NaCl in O.1N HC1, and 3.55% NaCl in 1.ON HC1. The solutions were chosen to simulate environments that were expected to be less, similar, and more aggressive, respectively, than those present at the Space Shuttle launch pads. The results from the EIS measurements were analyzed to evaluate the corrosion susceptibility of the alloys and to predict the long-term corrosion performance of the subject materials. The results from the EIS measurements for the three alloys indicated that the higher-alloyed 254SMO and AL6XN exhibited a significantly improved resistance to corrosion than the 304L SS as the concentration of hydrochloric acid in the 3.55% NaC1 solution was increased. The polarization resistance values obtained from the EIS measurements were consistent with those from linear polarization measurements, and were indicative of the actual long-term corrosion performance of the alloys during a two-year atmospheric exposure study.

Calle, L. M.↗

DOE OSTI2023

Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification

Multi-fidelity Monte Carlo methods leverage low-fidelity and surrogate models for variance reduction to make tractable uncertainty quantification even when numerically simulating the physical systems of interest with high-fidelity models is computationally expensive. This work proposes a context-aware multi-fidelity Monte Carlo method that optimally balances the costs of training low-fidelity models with the costs of Monte Carlo sampling. It generalizes the previously developed context-aware bi-fidelity Monte Carlo method to hierarchies of multiple models and to more general types of low-fidelity models. When training low-fidelity models, the proposed approach takes into account the context in which the learned low-fidelity models will be used, namely for variance reduction in Monte Carlo estimation, which allows it to find optimal trade-offs between training and sampling to minimize upper bounds of the mean-squared errors of the estimators for given computational budgets. This is in stark contrast to traditional surrogate modeling and model reduction techniques that construct low-fidelity models with the primary goal of approximating well the high-fidelity model outputs and typically ignore the context in which the learned models will be used in upstream tasks. Further, the proposed context-aware multi-fidelity Monte Carlo method applies to hierarchies of a wide range of types of low-fidelity models such as sparse-grid and deep-network models. Numerical experiments with the gyrokinetic simulation code Gene show speedups of up to two orders of magnitude compared to standard estimators when quantifying uncertainties in small-scale fluctuations in confined plasma in fusion reactors. This corresponds to a runtime reduction from 72 days to four hours on one node of the Lonestar6 supercomputer at the Texas Advanced Computing Center.

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NASA NTRS2003

Efficient Development of High Fidelity Structured Volume Grids for Hypersonic Flow Simulations

A new technique for the control of grid line spacing and intersection angles of a structured volume grid, using elliptic partial differential equations (PDEs) is presented. Existing structured grid generation algorithms make use of source term hybridization to provide control of grid lines, imposing orthogonality implicitly at the boundary and explicitly on the interior of the domain. A bridging function between the two types of grid line control is typically used to blend the different orthogonality formulations. It is shown that utilizing such a bridging function with source term hybridization can result in the excessive use of computational resources and diminishes robustness. A new approach, Anisotropic Lagrange Based Trans-Finite Interpolation (ALBTFI), is offered as a replacement to source term hybridization. The ALBTFI technique captures the essence of the desired grid controls while improving the convergence rate of the elliptic PDEs when compared with source term hybridization. Grid generation on a blunt cone and a Shuttle Orbiter is used to demonstrate and assess the ALBTFI technique, which is shown to be as much as 50% faster, more robust, and produces higher quality grids than source term hybridization.

Alter, Stephen J.↗

NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modeling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) specialists within the Nondestructive Evaluation Sciences branch at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗

DOE OSTI2020

Tailored Graphene Micropatterns by Wafer-Scale Direct Transfer for Flexible Chemical Sensor Platform

2D materials, such as graphene, exhibit great potential as functional materials for numerous novel applications due to their excellent properties. The grafting of conventional micropatterning techniques on new types of electronic devices is required to fully utilize the unique nature of graphene. However, the conventional lithography and polymer-supported transfer methods often induce the contamination and damage of the graphene surface due to polymer residues and harsh wet-transfer conditions. In this work, a novel strategy to obtain micropatterned graphene on polymer substrates using a direct curing process is demonstrated. Employing this method, entirely flexible, transparent, well-defined self-activated graphene sensor arrays, capable of gas discrimination without external heating, are fabricated on 4 in. wafer-scale substrates. Finite element method simulations show the potential of this patterning technique to maximize the performance of the sensor devices when the active channels of the 2D material are suspended and nanoscaled. This study contributes considerably to the development of flexible functional electronic devices based on 2D materials.

2D materials, Graphene, Microscale patterning, Che↗