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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Validation of a Three-Dimensional Ablation and Thermal Response Simulation Code

The 3dFIAT code simulates pyrolysis, ablation, and shape change of thermal protection materials and systems in three dimensions. The governing equations, which include energy conservation, a three-component decomposition model, and a surface energy balance, are solved with a moving grid system to simulate the shape change due to surface recession. This work is the first part of a code validation study for new capabilities that were added to 3dFIAT. These expanded capabilities include a multi-block moving grid system and an orthotropic thermal conductivity model. This paper focuses on conditions with minimal shape change in which the fluid/solid coupling is not necessary. Two groups of test cases of 3dFIAT analyses of Phenolic Impregnated Carbon Ablator in an arc-jet are presented. In the first group, axisymmetric iso-q shaped models are studied to check the accuracy of three-dimensional multi-block grid system. In the second group, similar models with various through-the-thickness conductivity directions are examined. In this group, the material thermal response is three-dimensional, because of the carbon fiber orientation. Predictions from 3dFIAT are presented and compared with arcjet test data. The 3dFIAT predictions agree very well with thermocouple data for both groups of test cases.

Chen, Yih-Kanq↗
DOE OSTI2017

Experimental Evaluation of Load Rejection Over-Voltage from Grid-Tied Solar Inverters

This paper investigates the impact of load rejection over-voltage (LRO) from commercially available grid-tied photovoltaic (PV) solar inverters. LRO can occur when a local feeder or breaker opens and the power output from a distributed energy resource exceeds the load power. Simplified models of current controlled inverters can over-predict over-voltage magnitudes, thus it is useful to quantify testing. The load rejection event was replicated using a hardware testbed at the National Renewable Energy Laboratory (NREL), and a set of commercially available PV inverters was tested to quantify the impact of LRO for a range of generation-to-load ratios. The magnitude and duration of the over-voltage events are reported in this paper along with a discussion of characteristic inverter output behavior. The results for the inverters under test showed that maximum over-voltage magnitudes were less than 200 percent of nominal voltage, and much lower in many test cases. These research results are important because utilities that interconnect inverter-based DER need to understand their characteristics under abnormal grid conditions.

14 SOLAR ENERGY↗
DOE OSTI2019

TRANSP-based optimization towards tokamak scenario development

An optimization approach that incorporates the predictive transport code TRANSP is proposed for tokamak scenario development. Optimization methods are often employed to develop open-loop control strategies to aid access to high performance tokamak scenarios. Generally, the optimization approaches use control-oriented models, i.e. models that are reduced in complexity and prediction accuracy as compared to physics-oriented transport codes such as TRANSP. In the presented approach, an optimization procedure using the TRANSP code to simulate the tokamak plasma is considered for improved predictive capabilities. As a test case, the neutral beam injection (NBI) power is optimized to develop a control strategy that maximizes the noninductive current fraction during the ramp-up phase for NSTX-U. Simulation studies towards the achievement of noninductive ramp-up in NSTX-U have already been carried out with the TRANSP code. The optimization-based approach presented in this work is used to maximize the noninductive current fraction during ramp-up in NSTX-U, demonstrating that the scenario development task can be automated. An additional test case considers optimization of the current ramp rate in DIII-D for obtaining a stationary plasma characterized by a flat loop voltage profile in the flattop phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2009

SWIFT Code Assessment for Two Similar Transonic Compressors

One goal of the NASA Fundamental Aeronautics Program is the assessment of computational fluid dynamic (CFD) codes used for the design and analysis of many aerospace systems. This paper describes the assessment of the SWIFT turbomachinery analysis code for two similar transonic compressors, NASA rotor 37 and stage 35. The two rotors have identical blade profiles on the front, transonic half of the blade but rotor 37 has more camber aft of the shock. Thus the two rotors have the same shock structure and choking flow but rotor 37 produces a higher pressure ratio. The two compressors and experimental data are described here briefly. Rotor 37 was also used for test cases organized by ASME, IGTI, and AGARD in 1994-1998. Most of the participating codes over predicted pressure and temperature ratios, and failed to predict certain features of the downstream flowfield. Since then the AUSM+ upwind scheme and the k- turbulence model have been added to SWIFT. In this work the new capabilities were assessed for the two compressors. Comparisons were made with overall performance maps and spanwise profiles of several aerodynamic parameters. The results for rotor 37 were in much better agreement with the experimental data than the original blind test case results although there were still some discrepancies. The results for stage 35 were in very good agreement with the data. The results for rotor 37 were very sensitive to turbulence model parameters but the results for stage 35 were not. Comparison of the rotor solutions showed that the main difference between the two rotors was not blade camber as expected, but shock/boundary layer interaction on the casing.

Chima, Rodrick V.↗
DOE OSTI2019

TRANSP-based Optimization Towards Tokamak Scenario Development

An optimization approach that incorporates the predictive transport code TRANSP is proposed for tokamak scenario development. Optimization methods are often employed to develop open-loop control strategies to aid access to high performance tokamak scenarios. In general, the optimization approaches use control-oriented models, i.e. models that are reduced in complexity and prediction accuracy as compared to physics-oriented transport codes such as TRANSP. In the presented approach, an optimization procedure using the TRANSP code to simulate the tokamak plasma is considered for improved predictive capabilities. As a test case, the neutral beam injection (NBI) power is optimized to develop a control strategy that maximizes the non-inductive current fraction during the ramp-up phase for NSTX-U. Simulation studies towards the achievement of non-inductive ramp up in NSTX-U have already been carried out with the TRANSP code. The optimization-based approach proposed in this work is used to maximize the non-inductive current fraction during ramp-up in NSTX-U, demonstrating that the scenario development task can be automated. An additional test case considers optimization of the current ramp rate in DIII-D for obtaining a stationary plasma characterized bya flat loop voltage profile in the flattop phase.

DIII-D↗
NASA NTRSDate not supplied

An Optimization Approach to Support Science Decision Making for Lunar Surface Exploration

Introduction: Scientific exploration is one of the three pillars of NASA’s Moon2Mars architecture, with crew surface extra vehicular activities (EVA) serving a critical enabling function. Development of surface EVA operational planning and execution, specifically integrating science and flight control teams (FCT), is currently being explored through analog scenarios. This integration, exercised, for example, through the Joint EVA and Hu-man Surface Mobility Test Team (JETT), allows for science input on EVA activities in near real-time through a Science Evaluation Room (SER), or Arte-mis science backroom, which integrates with the broader FCT through the Science Officer. The SER works within the FCT to support dynamic EVA planning in response to changes in operational constraints as well as science opportunities and re-prioritization, increasing the mission science return and accelerating the accomplishment of the Moon2Mars science objectives. The SER works within the FCT to provide recommendations to traverse execution in near real-time. One challenge is the requirement to deliver SER inputs to the FCT on operationally relevant timelines. Failure to do so may result in suboptimal execution of science exploration EVAs or even loss of key science objectives. To close this gap, we present a network optimization tool to allow the SER to provide rapid input to the FCT in response to changes in operational constraints or science opportunities. Inputs are predicated on approved science objectives, and clear rationale must be provided to the FCT for any requested change. Accordingly, this tool incorporates the Science Traceability Matrix (STM), SER prioritization scheme, and station characterization and action planning with operational constraints such as duration, traverse speed, and distance to maximize science objectives based on SER priorities, consistent with FCT operational requirements. Method: As a proof of concept, we used an existing linear programing software package used to simulate optimal routes through cellular metabolism. We built a Demonstrative Model with three STM objectives and four stations on a region of the Moon. The objectives were given an arbitrary prioritization and mapped to the stations through four possible crew actions. (Figs. 1 and 2). This station to STM mapping is consistent with the method used by the JETT5 Science Team to develop analog surface EVA science planning. We used a grid system with the landing site at the origin and the four stations placed across the positive x,y quadrant. Actions were assigned to each station and the accomplishment of those actions resulted in a numerical “reward” based on the ability of that action to achieve science objectives. The aggregate reward from each individual STM objective contributes to a global score (Science Yield), weighted by its priority. Operational constraints included a requirement to start and end at the landing site, 5 minutes each for initial station characterization and “clean up,” and variable total EVA time, traverse rate (fixed to 0.5 meters per second in our example), and time to perform each action (10, 5, 7, and 15 min for actions 1, 2, 3, and 4, respectively). Additional constraints and variables will be added in the future (e.g., sample mass, number of stations, traverse route constraints, illumination). Optimization. We converted the connections (arcs) between these stations (nodes) into a mixed integer linear programming optimization problem (arcs = constraints, nodes = variables) with the objective to maximize Science Yield. For any action, the Science Yield is equal to the relevance of that action to an STM objective [3, 2, and 1 point(s) for High, Med., and Low relevance, respectively], multiplied by the STM Objective Priority [3, 2, and 1 point(s) for High, Med., and Low priority, respectively]. This resulted in a model that computes the optimal station and action combination to maximize the Science Yield. These weightings can be adjusted by the SER as desired. Results: We explored three test cases for the Demonstrative Model. First, we set the maximum EVA duration to 120 minutes and computed the optimal route (Fig. 3A). The model suggested per-forming Actions 1 and 2 at Station P01, followed by Actions 1 and 2 at Station P02, and finally Actions 1 and 3 at Station P04 before returning to the Landing Site. Second, we adjusted the STM Objective Priori-ty order and computed the new optimal route (Fig. 3B). Under this situation, the model suggested per-forming all Actions at Station P02 followed by all Actions at Station P03. The previous test cases were relevant to SER planning activities. Next, we explored providing mid-EVA replanning input to the FCT. Scenario: While executing the Route in Fig. 3A the crew finishes at Station P01 and FCT decides that the EVA needs to finish in 45 minutes back at the Landing Site. FCT asks SER to recommend changes to the plan to accommodate this operation-al change. Using the model and incorporating these new constraints (start at Station P01, max. time of 45 min), the model suggested performing Actions 2 and 4 at Station P03 (Fig. 4), requiring 41 minutes to complete and return to the Landing Site. Interestingly, Station 3 was not part of the original route. Using the model, we determined the EVA would need 66 minutes, instead of 45, in order for the original Station P04 to yield a larger Science Yield than Station P03. The parametrization and simulation was per-formed in less than a minute, demonstrating the operational relevance of the approach. Future Efforts: The results from the Demonstrative Model suggest this tool can accelerate SER decision making on operationally relevant timelines. Use in analog activities, such as JETT5 or follow-ons, which have over a dozen stations for a crew to explore and over a dozen actions per station, will provide needed validation of the utility of this tool for planning EVAs, replanning mid-EVA, or planning follow-on EVAs based on previous results. Further integration with FCT execution monitoring tools may provide additional efficiency gains, al-lowing rapid and iterative exploration of operation-al and science decision space by the FCT and SER.

Science Operations↗
DOE OSTI2023

Convolutional Neural Network–Aided Temperature Field Reconstruction: An Innovative Method for Advanced Reactor Monitoring

In this study, the capabilities of a physics-informed convolutional neural network (CNN) for reconstructing the temperature field from a limited set of measurements taken at the boundaries of internal flows are demonstrated. Such an approach enables the development of less invasive monitoring methods for real-time plant diagnostics. As a test case, a Molten Salt Fast Reactor (MSFR) design was selected. This circulating fuel reactor has received interest from both scientific and industrial communities due to its intrinsic safety and sustainability. Molten salt flows in such reactors, however, can present highly localized temperature peaks that can induce significant thermal stresses onto the vessel walls. At these local maxima, the salt temperature may exceed a thousand kelvins, which makes a direct measurement challenging or even unfeasible. The proposed CNN algorithm allows one to detect indirectly such discontinuities through an accurate, albeit indirect, temperature measurement method during reactor operation. The datasets employed to train and test the machine learning models in the present work were generated with Nek5000, a computational fluid dynamics (CFD) code developed at Argonne National Laboratory. The CNN algorithm is trained with CFD results that span a set of MSFR operational power and flow ranges. Here, to demonstrate the efficacy of the algorithm, predictions are made for test cases contained within the training range but for which the CFD data were not used when training. Results demonstrate that the proposed technique properly characterizes temperature peaks and distributions within the domain for a broad range of scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2004

DSMC Simulations of Hypersonic Flows and Comparison With Experiments

This paper presents computational results obtained with the direct simulation Monte Carlo (DSMC) method for several biconic test cases in which shock interactions and flow separation-reattachment are key features of the flow. Recent ground-based experiments have been performed for several biconic configurations, and surface heating rate and pressure measurements have been proposed for code validation studies. The present focus is to expand on the current validating activities for a relatively new DSMC code called DS2V that Bird (second author) has developed. Comparisons with experiments and other computations help clarify the agreement currently being achieved between computations and experiments and to identify the range of measurement variability of the proposed validation data when benchmarked with respect to the current computations. For the test cases with significant vibrational nonequilibrium, the effect of the vibrational energy surface accommodation on heating and other quantities is demonstrated.

Moss, James N.↗
DOE OSTI2020

Development of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an Integrated Energy System (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. A new RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization (HERON) has been developed for optimizing the production variables of the IES given the demand profile. Currently, only the limits that affect the production variables and their corresponding time rates of change are considered (explicit constraints). However, other variables are additionally subject to constraints, but the associated limits are not accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response effects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. The Reference Governor (RG) algorithm is traditionally used for enforcing state and control constraints by modifying the set-point trajectories supplied to the feedback regulators. In our application, the RG is coupled within an iterative loop with the HERON-power dispatcher to generate optimal trajectories that ensure the operational constraints are met. A data-driven procedure to derive a representation of the dynamics of the controlled system was developed. First, the variables that represented the state of the system are selected (PCA-based approach), and then state-space representation matrices are derived from the collected measurements (DMDc algorithm). A preliminary version of the developed workflow based on Linear Time Invariant matrices was assessed by adopting a two-unit test case. More sophisticated versions of this workflow foreseeing the on-line derivation of system matrices will be deployed in FY 2021. Finally, a “plug-and-play” library of controllers and state observers was developed in Dymola. Some aspects of the current configuration of the IES unit components, e.g., the encapsulation of the control schemes into dedicated blocks, are consistent with the “plug-and-play” philosophy. Other features, e.g., the system buses collecting the input and the output variables, are not. For this reason, once listed and described the limits of the current configuration, necessary modifications to the plant model interface are presented. As a test-case, the interfaces of the SES model in the RAVEN-based HYBRID framework were reworked accordingly, and two different control schemes were applied to the same plant model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Reduced Order Modeling for Prediction and Control of Large-Scale Systems.

This report describes work performed from June 2012 through May 2014 as a part of a Sandia Early Career Laboratory Directed Research and Development (LDRD) project led by the first author. The objective of the project is to investigate methods for building stable and efficient proper orthogonal decomposition (POD)/Galerkin reduced order models (ROMs): models derived from a sequence of high-fidelity simulations but having a much lower computational cost. Since they are, by construction, small and fast, ROMs can enable real-time simulations of complex systems for onthe- spot analysis, control and decision-making in the presence of uncertainty. Of particular interest to Sandia is the use of ROMs for the quantification of the compressible captive-carry environment, simulated for the design and qualification of nuclear weapons systems. It is an unfortunate reality that many ROM techniques are computationally intractable or lack an a priori stability guarantee for compressible flows. For this reason, this LDRD project focuses on the development of techniques for building provably stable projection-based ROMs. Model reduction approaches based on continuous as well as discrete projection are considered. In the first part of this report, an approach for building energy-stable Galerkin ROMs for linear hyperbolic or incompletely parabolic systems of partial differential equations (PDEs) using continuous projection is developed. The key idea is to apply a transformation induced by the Lyapunov function for the system, and to build the ROM in the transformed variables. It is shown that, for many PDE systems including the linearized compressible Euler and linearized compressible Navier-Stokes equations, the desired transformation is induced by a special inner product, termed the “symmetry inner product”. Attention is then turned to nonlinear conservation laws. A new transformation and corresponding energy-based inner product for the full nonlinear compressible Navier-Stokes equations is derived, and it is demonstrated that if a Galerkin ROM is constructed in this inner product, the ROM system energy will be bounded in a way that is consistent with the behavior of the exact solution to these PDEs, i.e., the ROM will be energy-stable. The viability of the linear as well as nonlinear continuous projection model reduction approaches developed as a part of this project is evaluated on several test cases, including the cavity configuration of interest in the targeted application area. In the second part of this report, some POD/Galerkin approaches for building stable ROMs using discrete projection are explored. It is shown that, for generic linear time-invariant (LTI) systems, a discrete counterpart of the continuous symmetry inner product is a weighted L2 inner product obtained by solving a Lyapunov equation. This inner product was first proposed by Rowley et al., and is termed herein the “Lyapunov inner product“. Comparisons between the symmetry inner product and the Lyapunov inner product are made, and the performance of ROMs constructed using these inner products is evaluated on several benchmark test cases. Also in the second part of this report, a new ROM stabilization approach, termed “ROM stabilization via optimization-based eigenvalue reassignment“, is developed for generic LTI systems. At the heart of this method is a constrained nonlinear least-squares optimization problem that is formulated and solved numerically to ensure accuracy of the stabilized ROM. Numerical studies reveal that the optimization problem is computationally inexpensive to solve, and that the new stabilization approach delivers ROMs that are stable as well as accurate. Summaries of “lessons learned“ and perspectives for future work motivated by this LDRD project are provided at the end of each of the two main chapters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Poster - 53: Improving inter-linac DMLC IMRT dose precision by fine tuning of MLC leaf calibration

Purpose: To develop a method to improve the inter-linac precision of DMLC IMRT dosimetry. Methods: The distance between opposing MLC leaf banks (“gap size”) can be finely tuned on Varian linacs. The dosimetric effect due to small deviations from the nominal gap size (“gap error”) was studied by introducing known errors for several DMLC sliding gap sizes, and for clinical plans based on the TG119 test cases. The plans were delivered on a single Varian linac and the relationship between gap error and the corresponding change in dose was measured. The plans were also delivered on eight Varian 2100 series linacs (at two institutions) in order to quantify the inter-linac variation in dose before and after fine tuning the MLC calibration. Results: The measured dose differences for each field agreed well with the predictions of LoSasso et al. Using the default MLC calibration, the variation in the physical MLC gap size was determined to be less than 0.4 mm between all linacs studied. The dose difference between the linacs with the largest and smallest physical gap was up to 5.4% (spinal cord region of the head and neck TG119 test case). This difference was reduced to 2.5% after fine tuning the MLC gap calibration. Conclusions: The inter-linac dose precision for DMLC IMRT on Varian linacs can be improved using a simple modification of the MLC calibration procedure that involves fine adjustment of the nominal gap size.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Explicit integration with GPU acceleration for large kinetic networks

We demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. This orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2013

Summary of Data from the Fifth AIAA CFD Drag Prediction Workshop

Results from the Fifth AIAA CFD Drag Prediction Workshop (DPW-V) are presented. As with past workshops, numerical calculations are performed using industry-relevant geometry, methodology, and test cases. This workshop focused on force/moment predictions for the NASA Common Research Model wing-body configuration, including a grid refinement study and an optional buffet study. The grid refinement study used a common grid sequence derived from a multiblock topology structured grid. Six levels of refinement were created resulting in grids ranging from 0.64x10(exp 6) to 138x10(exp 6) hexahedra - a much larger range than is typically seen. The grids were then transformed into structured overset and hexahedral, prismatic, tetrahedral, and hybrid unstructured formats all using the same basic cloud of points. This unique collection of grids was designed to isolate the effects of grid type and solution algorithm by using identical point distributions. This study showed reduced scatter and standard deviation from previous workshops. The second test case studied buffet onset at M=0.85 using the Medium grid (5.1x106 nodes) from the above described sequence. The prescribed alpha sweep used finely spaced intervals through the zone where wing separation was expected to begin. Some solutions exhibited a large side of body separation bubble that was not observed in the wind tunnel results. An optional third case used three sets of geometry, grids, and conditions from the Turbulence Model Resource website prepared by the Turbulence Model Benchmarking Working Group. These simple cases were intended to help identify potential differences in turbulence model implementation. Although a few outliers and issues affecting consistency were identified, the majority of participants produced consistent results.

Levy, David W.↗
DOE OSTI2024

Data‐driven variational method for discrepancy modeling: Dynamics with small‐strain nonlinear elasticity and viscoelasticity

Abstract The effective inclusion of a priori knowledge when embedding known data in physics‐based models of dynamical systems can ensure that the reconstructed model respects physical principles, while simultaneously improving the accuracy of the solution in the previously unseen regions of state space. This paper presents a physics‐constrained data‐driven discrepancy modeling method that variationally embeds known data in the modeling framework. The hierarchical structure of the method yields fine scale variational equations that facilitate the derivation of residuals which are comprised of the first‐principles theory and sensor‐based data from the dynamical system. The embedding of the sensor data via residual terms leads to discrepancy‐informed closure models that yield a method which is driven not only by boundary and initial conditions, but also by measurements that are taken at only a few observation points in the target system. Specifically, the data‐embedding term serves as residual‐based least‐squares loss function, thus retaining variational consistency. Another important relation arises from the interpretation of the stabilization tensor as a kernel function, thereby incorporating a priori knowledge of the problem and adding computational intelligence to the modeling framework. Numerical test cases show that when known data is taken into account, the data driven variational (DDV) method can correctly predict the system response in the presence of several types of discrepancies. Specifically, the damped solution and correct energy time histories are recovered by including known data in the undamped situation. Morlet wavelet analyses reveal that the surrogate problem with embedded data recovers the fundamental frequency band of the target system. The enhanced stability and accuracy of the DDV method is manifested via reconstructed displacement and velocity fields that yield time histories of strain and kinetic energies which match the target systems. The proposed DDV method also serves as a procedure for restoring eigenvalues and eigenvectors of a deficient dynamical system when known data is taken into account, as shown in the numerical test cases presented here.

Masud, Arif↗
DOE OSTI2020

Performance Evaluation of a Two-Dimensional Flood Model on Heterogeneous High-Performance Computing Architectures

This paper describes the implementation of a two-dimensional hydrodynamic flood model with two different numerical schemes on heterogeneous high-performance computing architectures. Both schemes were able to solve the nonlinear hyperbolic shallow water equations using an explicit upwind first-order approach on finite differences and finite volumes, respectively, and were conducted using MPI and CUDA. Four different test cases were simulated on the Summit supercomputer at Oak Ridge National Laboratory. Both numerical schemes scaled up to 128 nodes (768 GPUs) with a maximum 98.2x speedup of over 1 GPU. The lowest run time for the 10 day Hurricane Harvey event simulation at 5 meter resolution (272 million grid cells) was 50 minutes. GPUDirect communication proved to be more convenient than the standard communication strategy. Both strong and weak scaling are shown.

Sharif, Md Bulbul↗
NASA NTRS2014

Turbulence Modeling Verification and Validation

Computational fluid dynamics (CFD) software that solves the Reynolds-averaged Navier-Stokes (RANS) equations has been in routine use for more than a quarter of a century. It is currently employed not only for basic research in fluid dynamics, but also for the analysis and design processes in many industries worldwide, including aerospace, automotive, power generation, chemical manufacturing, polymer processing, and petroleum exploration. A key feature of RANS CFD is the turbulence model. Because the RANS equations are unclosed, a model is necessary to describe the effects of the turbulence on the mean flow, through the Reynolds stress terms. The turbulence model is one of the largest sources of uncertainty in RANS CFD, and most models are known to be flawed in one way or another. Alternative methods such as direct numerical simulations (DNS) and large eddy simulations (LES) rely less on modeling and hence include more physics than RANS. In DNS all turbulent scales are resolved, and in LES the large scales are resolved and the effects of the smallest turbulence scales are modeled. However, both DNS and LES are too expensive for most routine industrial usage on today's computers. Hybrid RANS-LES, which blends RANS near walls with LES away from walls, helps to moderate the cost while still retaining some of the scale-resolving capability of LES, but for some applications it can still be too expensive. Even considering its associated uncertainties, RANS turbulence modeling has proved to be very useful for a wide variety of applications. For example, in the aerospace field, many RANS models are considered to be reliable for computing attached flows. However, existing turbulence models are known to be inaccurate for many flows involving separation. Research has been ongoing for decades in an attempt to improve turbulence models for separated and other nonequilibrium flows. When developing or improving turbulence models, both verification and validation are important steps in the process. Verification insures that the CFD code is solving the equations as intended (no errors in the implementation). This is typically done either through the method of manufactured solutions (MMS) or through careful step-by-step comparisons with other verified codes. After the verification step is concluded, validation is performed to document the ability of the turbulence model to represent different types of flow physics. Validation can involve a large number of test case comparisons with experiments, theory, or DNS. Organized workshops have proved to be valuable resources for the turbulence modeling community in its pursuit of turbulence modeling verification and validation. Workshop contributors using different CFD codes run the same cases, often according to strict guidelines, and compare results. Through these comparisons, it is often possible to (1) identify codes that have likely implementation errors, and (2) gain insight into the capabilities and shortcomings of different turbulence models to predict the flow physics associated with particular types of flows. These are valuable lessons because they help bring consistency to CFD codes by encouraging the correction of faulty programming and facilitating the adoption of better models. They also sometimes point to specific areas needed for improvement in the models. In this paper, several recent workshops are summarized primarily from the point of view of turbulence modeling verification and validation. Furthermore, the NASA Langley Turbulence Modeling Resource website is described. The purpose of this site is to provide a central location where RANS turbulence models are documented, and test cases, grids, and data are provided. The goal of this paper is to provide an abbreviated survey of turbulence modeling verification and validation efforts, summarize some of the outcomes, and give some ideas for future endeavors in this area.

Rumsey, Christopher L.↗
DOE OSTI2019

A Comparison of GoldSim, RESRAD-Onsite, and NORMALYSA Modeling Tools at Radioactive Waste Sites - 19480

Radioactive waste disposal and associated decision making is a challenging problem around the world. A strong performance assessment model plays a crucial role in making good management and remediation decisions and in optimizing the performance of a site. The International Atomic Energy Agency (IAEA) MODARIA II Working Group 1 (WG1) is comparing the performance of various modeling platforms used at Naturally Occurring Radioactive Material (NORM) and legacy waste sites to support risk-informed decision making. Neptune and Company, Inc. (Neptune) has developed probabilistic performance assessment models using the GoldSim system modeling software at a variety of radioactive waste sites. This paper presents a comparison between GoldSim and two other tools used to evaluate radiation exposure and their associated risks: the NORM And Legacy Site Assessment (NORMALYSA) tool used to assess risk at the Zapadnoe mill tailings site, and the residual radioactivity (RESRAD-Onsite) computer program used to calculate Authorized Limits at the Los Alamos National Laboratory (LANL). The International Atomic Energy Agency (IAEA) supported development of NORMALYSA based off of Ecolego 6.0, in which the user connects several universal modules, representing various environmental transport and exposure pathways, and enters in site-specific data. Further work with NORMALYSA has continued under the MODARIA II WG 1. A radionuclide transport and dose calculation model of the Zapadnoe uranium mill tailings site at the Pridneprovsky Chemical Plant in the Ukraine has been configured by MODARIA II WG1 to test the capabilities of NORMALYSA. Under this test case, contaminant transport and effective dose calculations were performed for two exposure scenarios. The onsite worker is exposed via external ground irradiation and radon and radioactive dust inhalation. The offsite resident defines a residence established 300 years after institutional control has ended, 800 meters downstream from the site with exposure pathways including: ingestion of garden vegetables irrigated by contaminated ground water, ingestion of fish from the Konoplyanka River and agricultural activities in the contaminated garden. GoldSim modeling software is a dynamic probabilistic modeling platform that evaluates uncertainty in a robust and transparent manner. Although GoldSim provides contaminant and radionuclide transport modules to facilitate integrated modeling of radionuclide migration in the environment, these features are not embedded in an existing modeling framework, except as created by the user. Neptune developed a GoldSim model for the two exposure scenarios of the Zapadnoe test case. Neptune's Generic PA Model was used as a starting point for the Zapadnoe site. Input parameters for the GoldSim model include site-specific parameters from the MODARIA Working Group as well as parameters from the Generic PA Model and other PA models created by Neptune. For the other comparison, Version 7.0 of RESRAD-Onsite, developed by Argonne National Laboratory for the U.S. Department of Energy (DOE), was used to calculate Authorized Limits for LANL. Authorized Limits are concentrations of radionuclides in soil that support the evaluation process to clear land for release under different uses. The RESRAD-Onsite computer code was used to calculate Authorized Limits because this program was specifically designed to derive radionuclide soil guidelines corresponding to a specific dose criterion. The scope of the RESRAD dose or risk evaluation is constrained to the transport and exposure pathways that have been included in the computer code. To assist in illustrating the capability of GoldSim modeling software, a GoldSim model was created to replicate the calculation of LANL's Authorized Limits for soil. The main exposure pathways in this model are inhalation of dust and gas, plant ingestion, soil ingestion, and external ground irradiation. All of the processes and outputs of RESRAD-Onsite and NORMALYSA can be created in a GoldSim model, but the value of GoldSim lies in its flexibility for application to any of a wide variety of environmental modeling problems. GoldSim allows development of site-specific inventory, transport mechanisms and risk assessment scenarios. If all potentially complete release, transport, and exposure pathways are addressed in an existing dose and risk assessment computer code, and if the code's capabilities fulfill the project modeling objectives, then expending resources to create a GoldSim model may not be necessary. Site optimization and good decision making about site management are often best when supported with the flexibility of GoldSim as a modeling tool. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Proline: Mother Nature;s cryoprotectant applied to protein crystallography

L-Proline is one of Mother Nature's cryoprotectants. Plants and yeast accumulate proline under freeze-induced stress and the use of proline in the cryopreservation of biological samples is well established. Here, it is shown that L-proline is also a useful cryoprotectant for protein crystallography. Proline was used to prepare crystals of lysozyme, xylose isomerase, histidine acid phosphatase and 1-pyrroline-5-carboxylate dehydrogenase for low-temperature data collection. The crystallization solutions in these test cases included the commonly used precipitants ammonium sulfate, sodium chloride and polyethylene glycol and spanned the pH range 4.6-8.5. Thus, proline is compatible with typical protein-crystallization formulations. The proline concentration needed for cryoprotection of these crystals is in the range 2.0-3.0 M. Complete data sets were collected from the proline-protected crystals. Proline performed as well as traditional cryoprotectants based on the diffraction resolution and data-quality statistics. The structures were refined to assess the binding of proline to these proteins. As observed with traditional cryoprotectants such as glycerol and ethylene glycol, the electron-density maps clearly showed the presence of proline molecules bound to the protein. In two cases, histidine acid phosphatase and 1-pyrroline-5-carboxylate dehydrogenase, proline binds in the active site. It is concluded that L-proline is an effective cryoprotectant for protein crystallography.

59 BASIC BIOLOGICAL SCIENCES↗