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At least 1,621 records · Page 90

Direct simulation of three-dimensional flow about the AFE vehicle at high altitudes

Three-dimensional hypersonic rarefied flow about the Aeroassist Flight Experiment (AFE) vehicle was studied using the direct simulation Monte Carlo (DSMC) technique. Results are presented for the transitional flow regime encountered between 120 and 200 km altitudes with a reentry velocity of 9.92 km/s. In the simulations, a five-species reacting real-gas model that accounts for internal energies (rotational and vibrational) is used. The results indicate that the transitional effects are significant even at an altitude of 200 km and influence the overall vehicle aerodynamics. For the cases considered, the aerodynamic coefficients, surface pressures, convective heating, and flow field structure variations with rarefaction effects are presented.

Celenligil, M. Cevdet↗

Direct simulation of three-dimensional flow about the AFE vehicle at high altitudes

Three-dimensional hypersonic rarefied flow about the Aeroassist Flight Experiment (AFE) vehicle was studied using the direct simulation Monte Carlo (DSMC) technique. Results are presented for the transitional flow regime encountered between 120 and 200 km altitudes with a reentry velocity of 9.92 km/s. In the simulations, a five-species reacting real-gas model that accounts for internal energies (rotational and vibrational) is used. The results indicate that the transitional effects are significant even at an altitude of 200 km and influence the overall vehicle aerodynamics. For the cases considered, the aerodynamic coefficients, surface pressures, convective heating, and flow field structure variations with rarefaction effects are presented.

Celenligil, M. Cevdet↗

A Robust Machine Learning Schema for Developing, Maintaining, and Disseminating Machine Learning Models

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of ML models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based modeling of material behavior at various length scales and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using ML techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus, effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train ML models and the defining model parameters and architectures within the Granta MI Platform. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in the prediction of material behavior, while following outlined best practices for effective data management. An effective schema for ML data and models can help prevent the recreation of virtual/real training data and surrogate models, help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Brandon L. Hearley↗

Reaction heterogeneity in practical high-energy lithium–sulfur pouch cells

The lithium–sulfur (Li–S) battery is a promising next-generation energy storage technology because of its high theoretical energy and low cost. Extensive research efforts have been made on new materials and advanced characterization techniques for mechanistic studies. However, it is uncertain how discoveries made on the material level apply to realistic batteries due to limited analysis and characterization of real high-energy cells, such as pouch cells. Evaluation of pouch cells (>1 A h) (instead of coin cells) that are scalable to practical cells provides a critical understanding of current limitations which enables the proposal of strategies and solutions for further performance improvement. Herein, we design and fabricate pouch cells over 300 W h kg -1 , compare the cell parameters required for high-energy pouch cells, and investigate the reaction processes and their correlation to cell cycling behavior and failure mechanisms. Spatially resolved characterization techniques and fluid-flow simulation reveal the impacts of the liquid electrolyte diffusion within the pouch cells. We found that catastrophic failure of high-energy Li–S pouch cells results from uneven sulfur/polysulfide reactions and electrolyte depletion for the first tens of cycles, rather than sulfur dissolution as commonly reported in the literature. The uneven reaction stems from limited electrolyte diffusion through the porous channels into the central part of thick cathodes during cycling, which is amplified both across the sulfur electrodes and within the same electrode plane. A combination of strategies is suggested to increase sulfur utilization, improve nanoarchitectures for electrolyte diffusion and reduce consumption of the electrolytes and additives.

25 ENERGY STORAGE↗

Coaxial injector response to axial instability under simulated cold-flow

The frequency dependence of the admittances and response factors of various gaseous rocket injector configurations subject to axial instabilities under cold-flow conditions, have been measured using the modified impedance-tube technique. The tested configurations simulate the flows in a gaseous-fuel injector, gaseous-oxidizer injector and a coaxial injector with both fuel and oxidizer elements. Comparison of the measured response data with corresponding data predicted by the Feiler and Heidmann model indicates good agreement between the two sets of data.

Janardan, B. A.↗

Wake Vortex Tracking Using a 35 GHz Pulsed Doppler Radar

A 35 GHz, pulsed-Doppler radar system has been designed and assembled for wake vortex detection and tracking in low visibility conditions. Aircraft wake vortices continue to be an important factor in determining safe following distances or spacings for aircraft in the terminal area. Currently, under instrument meteorological conditions (IMC), aircraft adhere to conservative, fixed following-distance guidelines based primarily on aircraft weight classifications. When ambient conditions are such that vortices will either drift or dissipate, leaving the flight corridor clear, the prescribed spacings are unnecessarily long and result in decreased airport throughput. There is a potential for significant airport efficiency improvement, if a system can be employed to aid regulators and pilots in setting safe and efficient following distances based on airport conditions. The National Aeronautics and Space Administration (NASA), the Federal Aviation Agency, and Volpe National Transportation Systems Center have promoted and worked to develop systems that would increase airport capacity and provide for safe reductions in aircraft separation. The NASA Aircraft Vortex Spacing System (AVOSS), a wake vortex spacing system that can provide dynamic adjustment of spacings based on real-time airport weather conditions, has demonstrated that Lidar systems can be successfully used to detect and track vortices in clear air conditions. To fill the need for detection capability in low-visibility conditions, a 35 GHz, pulsed-Doppler radar system is being investigated for use as a complimentary, low-visibility sensor for wake vortices. The radar sensor provides spatial and temporal information similar to that provided by Lidar, but under weather conditions that a Lidar cannot penetrate. Currently, we are analyzing the radar design based upon the data and experience gained during the wake vortex Lidar deployment with AVOSS at Dallas/Fort Worth International Airport. As part of this study, two numerical models were utilized in system simulations. The results of this study improve our understanding of the method of detection, resolution requirements for range and azimuth, pulse compression, and performance prediction. Simulations applying pulse compression techniques show that detection is good in heavy fog to greater than 2000 m. Both compressed and uncompressed short pulses show the vortex structure. To explore operational challenges, siting and scanning strategies were also analyzed. Simulation results indicate that excellent wake vortex detection, tracking and classification is possible in drizzle (+15 dBZ) and heavy fog (- 13 dBZ) using short pulse techniques (<99ns) at ranges on the order of 900 m, with a modest power of 500 W output. At 1600 m, detection can be expected at reflectivities as low as -13 dBZ (heavy fog). The radar system, as designed and built, has the potential to support field studies of a wake vortex spacing system in low-visibility conditions ranging from heavy fog to rain, when sited within 2000m of the flight path.

Neece, Robert T.↗

Strength-conductivity synergy via lean alloy design: A study on novel solid stir extrusion of an Al-2Cu-0.1 Nb-0.15Zr (~wt.%) alloy

Aluminum alloys find wide applications in power and transmission cables, and electrical conductors due to their advantageous properties of high electrical conductivity, and lower cost per unit. However, the lower tensile strength compared to copper poses a challenge for the mechanical stability of aluminum-based cables. In this study, we addressed this issue by adopting a process-based alloy design approach, creating a lean alloy with a dilute composition of Al-2Cu-0.1 Nb-0.15Zr (~wt.%). Here, the alloy was processed using a friction stir based novel SolidStir® (SSE) technique, followed by low-temperature aging. The resulting aluminum wire exhibited improved strength (240 MPa) while simultaneously enhancing electrical conductivity (64%IACS). The study employed computational simulations (Thermocalc) and experimental techniques (differential scanning calorimetry and transmission electron microscopy) to thoroughly investigate the microstructure. Microstructural examinations revealed that the precipitation kinetics in SSE and SSE+aged conditions played a significant role in enhancing strength and electrical conductivity. These findings demonstrate the successful achievement of high strength and high electrical conductivity in aluminum wire through a lean alloy design approach.

36 MATERIALS SCIENCE↗

Development and application of hybrid AIMD/cDFT simulations for atomic-to-mesoscale chemistry

Many important chemical processes involve reactivity and dynamics in complex solutions. Gaining a fundamental understanding of these reaction mechanisms is a challenging goal that requires advanced computational and experimental approaches. However, important techniques such as molecular simulation have limitations in terms of scales of time, length, and system complexity. Furthermore, among the currently available solvation models, there are very few designed to describe the interaction between the molecular scale and the mesoscale. To help address this challenge, here, we establish a novel hybrid approach that couples first-principles plane-wave density functional theory with classical density functional theory (cDFT). In this approach, a region of interest described by ab initio molecular dynamics (AIMD) interacts with the surrounding medium described using cDFT to arrive at a self-consistent ground state. cDFT is a robust but efficient mesoscopic approach to accurate thermodynamics of bulk electrolyte solutions over a wide concentration range (up to 2M concentrations). Benchmarking against commonly used continuum models of solvation, such as SMD, as well as experiments, demonstrates that our hybrid AIMD–cDFT method is able to produce reasonable solvation energies for a variety of molecules and ions. With this model, we also examined the solvent effects on a prototype S N 2 reaction of the nucleophilic attack of a chloride ion on methyl chloride in the solution. The resulting reaction pathway profile and the solution phase barrier agree well with experiment, showing that our AIMD/cDFT hybrid approach can provide insight into the specific role of the solvent on the reaction coordinate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flat-Histogram Monte Carlo as an Efficient Tool To Evaluate Adsorption Processes Involving Rigid and Deformable Molecules

Monte Carlo simulations are the foundational technique for predicting thermodynamic properties of open systems where the process of interest involves the exchange of particles. Thus, they have been used extensively to computationally evaluate the adsorption properties of nanoporous materials and are critical for the in silico identification of promising materials for a variety of gas storage and chemical separation applications. In this work we demonstrate that a well-known biasing technique, known as “flat-histogram” sampling, can be combined with temperature extrapolation of the free energy landscape to efficiently provide significantly more useful thermodynamic information than standard open ensemble MC simulations. Namely, we can accurately compute the isosteric heat of adsorption and number of particles adsorbed for various adsorbates over an extremely wide range of temperatures and pressures from a set of simulations at just one temperature. We extend this derivation of the temperature extrapolation to adsorbates with intramolecular degrees of freedom when Rosenbluth sampling is employed. Consequently, the working capacity and isosteric heat can be computed for any given combined temperature/pressure swing adsorption process for a large range of operating conditions with both rigid and deformable adsorbates. Finally, continuous thermodynamic properties can be computed with this technique at very moderate computational cost, thereby providing a strong case for its application to the in silico identification of promising nanoporous adsorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sandia's Current Energy Conversion module for Flexible-Mesh Delft3D flow solver v. 1.0

The DOE has funded Sandia National Labs (SNL) to develop an open-source modeling tool to guide the design and layout of marine hydrokinetic (MHK) arrays to maximize power production while minimizing environmental effects. This modeling framework simulates flows through and around a MHK arrays while quantifying environmental responses. As an augmented version of the Dutch company, Deltares’s, environmental hydrodynamics code, Delft3D, SNL-Delft3D-CEC-FM includes a new module that simulates energy conversion (momentum withdrawal) by MHK current energy conversion devices with commensurate changes in the turbulent kinetic energy and its dissipation rate. SNL-Delft3D-CEC-FM modified the Delft3D flexible mesh flow solver, DFlowFM. The Following is a description of Deltares’s open-source code Delft3D from which Delft3D-CEC is built upon. “Delft3D is a world leading 3D modeling suite to investigate hydrodynamics, sediment transport and morphology and water quality for fluvial, estuarine and coastal environments. As per 1 January 2011, the Delft3D flow (FLOW), morphology (MOR) and waves (WAVE) modules are available in open source. The software is used and has proven his capabilities on many places around the world, like the Netherlands, USA, Hong Kong, Singapore, Australia, Venice, etc. The software is continuously improved and developed with innovating advanced modelling techniques as consequence of the research work of our institute and to stay world leading. The FLOW module is the heart of Delft3D and is a multi-dimensional (2D or 3D) hydrodynamic (and transport) simulation program which calculates non-steady flow and transport phenomena resulting from tidal and meteorological forcing on a curvilinear, boundary fitted grid or spherical coordinates. In 3D simulations, the vertical grid is defined following the so-called sigma coordinate approach or Z-layer approach. The MOR module computes sediment transport (both suspended and bed total load) and morphological changes for an arbitrary number of cohesive and non-cohesive fractions. Both currents and waves act as driving forces and a wide variety of transport formulae have been incorporated. For the suspended load this module connects to the 2D or 3D advection-diffusion solver of the FLOW module; density effects may be taken into account. An essential feature of the MOR module is the dynamic feedback with the FLOW and WAVE modules, which allow the flows and waves to adjust themselves to the local bathymetry and allows for simulations on any time scale from days (storm impact) to centuries (system dynamics). It can keep track of the bed composition to build up a stratigraphic record. The MOR module may be extended to include extensive features to simulate dredging and dumping scenarios. For over 30 years Deltares has been in the forefront of these types of combined morphological simulation techniques.”

Chartand, Chris↗

Confidence Intervals from Realizations of Simulated Nuclear Data

Various statistical techniques are discussed that can be used to assign a level of confidence in the prediction of models that depend on input data with known uncertainties and correlations. The particular techniques reviewed in this paper are: 1) random realizations of the input data using Monte-Carlo methods, 2) the construction of confidence intervals to assess the reliability of model predictions, and 3) resampling techniques to impose statistical constraints on the input data based on additional information. These techniques are illustrated with a calculation of the keff value, based on the 235 U(n, f) and 239 Pu (n, f) cross sections.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA/ESA CV-990 Spacelab Simulation (ASSESS 2)

Cost effective techniques for addressing management and operational activities on Spacelab were identified and analyzed during a ten day NASA-ESA cooperative mission with payload and flight responsibilities handled by the organization assigned for early Spacelabs. Topics discussed include: (1) management concepts and interface relationships; (2) experiment selection; (3) hardware development; (4) payload integration and checkout; (5) selection and training of mission specialists and payload specialists; (6) mission control center/payload operations control center interactions with ground and flight problems; (7) real time interaction during flight between principal investigators and the mission specialist/payload specialist flight crew; and (8) retrieval of scientific data and its analysis.

Source record↗

Quasi-complementary codes - A new technique for MST radar sounding

The binary phase complementary code set has been used in stratospheric radar sounding. The quasi-complementary code technique presented here has nearly complementary properties and offers significant reduction of side lobes caused by imperfections in the radar transmitter. The new technique and its application are described; a simulation of the performance of the two techniques when certain imperfections are present in the transmitter is presented. The results are compared with the actual performance of the Arecibo 430-MHz radar transmitter.

Sulzer, M. P.↗

Progress in hypersonic combustion technology with computation and experiment

Design of successful airbreathing engines for operation at near-orbital speeds presents significant challenges in all the disciplines involved, including propulsion. This paper presents a discussion of the important physics of hypersonic combustion and an assessment of the state of the art of ground simulations with pulse facilities and with computational techniques. Recent examples of experimental and computational simulations are presented and discussed. The need for continued application of these tools to establish the credibility and fidelity of engineering design methods for practical hypersonic combustors is emphasized along with the critical need for improved diagnostic methods for hypervelocity reacting flows.

Anderson, Griffin Y.↗

Variational approaches to CFD: Applications to potential Euler and Navier-Stokes equations

Flow simulations based on variational techniques are discussed. Variational techniques are applied for the problem formulation, for the construction of discrete schemes, and for the solution procedures. Inviscid transonic flows, as well as viscous incompressible and compressible flows, are analyzed by several methods. Variational techniques to solve the discrete systems of equations are well known. The most popular one is the conjugate gradient method. Extensions to nonsymmetric and nonpositive definite systems were under investigation for the last two decades. Variational techniques were used for convergence acceleration of iterative procedures. Some of these ideas based on recent work are examined. The lectures are organized in three parts including numerical simulation of inviscid as well as viscous incompressible and compressible flows.

Hafez, M.↗

Validating an Air Traffic Management Concept of Operation Using Statistical Modeling

Validating a concept of operation for a complex, safety-critical system (like the National Airspace System) is challenging because of the high dimensionality of the controllable parameters and the infinite number of states of the system. In this paper, we use statistical modeling techniques to explore the behavior of a conflict detection and resolution algorithm designed for the terminal airspace. These techniques predict the robustness of the system simulation to both nominal and off-nominal behaviors within the overall airspace. They also can be used to evaluate the output of the simulation against recorded airspace data. Additionally, the techniques carry with them a mathematical value of the worth of each prediction-a statistical uncertainty for any robustness estimate. Uncertainty Quantification (UQ) is the process of quantitative characterization and ultimately a reduction of uncertainties in complex systems. UQ is important for understanding the influence of uncertainties on the behavior of a system and therefore is valuable for design, analysis, and verification and validation. In this paper, we apply advanced statistical modeling methodologies and techniques on an advanced air traffic management system, namely the Terminal Tactical Separation Assured Flight Environment (T-TSAFE). We show initial results for a parameter analysis and safety boundary (envelope) detection in the high-dimensional parameter space. For our boundary analysis, we developed a new sequential approach based upon the design of computer experiments, allowing us to incorporate knowledge from domain experts into our modeling and to determine the most likely boundary shapes and its parameters. We carried out the analysis on system parameters and describe an initial approach that will allow us to include time-series inputs, such as the radar track data, into the analysis

Statistical emulation↗