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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

On learning what to learn: Heterogeneous observations of dynamics and establishing possibly causal relations among them

Abstract Before we attempt to (approximately) learn a function between two sets of observables of a physical process, we must first decide what the inputs and outputs of the desired function are going to be. Here we demonstrate two distinct, data-driven ways of first deciding “the right quantities” to relate through such a function, and then proceeding to learn it. This is accomplished by first processing simultaneous heterogeneous data streams (ensembles of time series) from observations of a physical system: records of multiple observation processes of the system. We determine (i) what subsets of observables are common between the observation processes (and therefore observable from each other, relatable through a function); and (ii) what information is unrelated to these common observables, therefore particular to each observation process, and not contributing to the desired function. Any data-driven technique can subsequently be used to learn the input–output relation—from k-nearest neighbors and Geometric Harmonics to Gaussian Processes and Neural Networks. Two particular “twists” of the approach are discussed. The first has to do with the identifiability of particular quantities of interest from the measurements. We now construct mappings from a single set of observations from one process to entire level sets of measurements of the second process, consistent with this single set. The second attempts to relate our framework to a form of causality: if one of the observation processes measures “now,” while the second observation process measures “in the future,” the function to be learned among what is common across observation processes constitutes a dynamical model for the system evolution.

Sroczynski, David W.↗
NASA NTRS1991

Unstructured grid generation using the distance function

A new class of methods for obtaining level sets to generate unstructured grids is presented. The consecutive grid levels are computed using the distance functions, which corresponds to solving the Hamilton-Jacobi equations representing the equations of motion of fronts propagating with curvature-dependent speed. The relationship between the distance function and the governing equations will be discussed as well as its application to generating grids. Multi-ply connected domains and complex geometries are handled naturally, with a straightforward generalization to several space dimensions. The grid points for the unstructured grid are obtained simultaneously with the grid levels. The search involved in checking for overlapping triangles is minimized by triangulating the entire domain one level at a time.

Bihari, Barna L.↗
NASA NTRS1974

Exospheric temperature and composition from satellite beacon measurements

Routine measurements of the slab thickness of the ionosphere, from 1965 to 1971, are used to infer the changes in neutral temperature and ion composition at a mean latitude of 40 S. Values of neutral temperature at solar maximum are 5 to 10% above Northern Hemisphere backscatter results. The diurnal and seasonal changes agree closely with satellite drag and backscatter measurements, except that the maximum temperature occurs after sunset in winter. Winter night-time values of the O(+)/H(+) transition height were 500 km in 1965-1966, 800 km in 1968-1969, and 700 km in 1971. Changes in the transition height lag about six months behind the changes in solar flux. Diurnal variations have a minimum just before sunrise and a maximum 1 to 3 hr after noon. On winter nights the transition height descends to the level set by chemical equilibrium. On summer nights the transition height is always above this level, giving a continual production of H(+) which serves as an additional source for maintaining the night-time ionosphere in the winter hemisphere.

Titheridge, J. E.↗
NASA NTRS1994

Oscillator strengths of selected resonance transitions in neutral sulfur

Mean lives and branching ratios for the 4s (3)S(sup 0 sub 1) and 4s(double prime) (3)P(sup 0 sub 1, 2) levels of neutral sulfur were determined at the Toledo Heavy Ion Accelerator using beam-foil spectroscopic techniques. The mean lives obtained for the 4s (3)S(sup 0 sub 1) 4s(double prime) (3)P(sup 0 sub 1), and (3)P(sup 0 sub 2) levels, 1.875 +/- 0.094 ns, 2.034 +/- 0.102 ns, and 2.146 +/- 0.129 ns, respectively, represent the most accurate results available to date. Oscillator strengths for the transitions 3p(sup 4)(3)P(sub 2, 1, 0)-4s (3)S(sup 0 sub 1) and 3p(sup 4)(3)P(sub 2, 1, 0)-4s(double prime) (3)P(sup 0 sub 1, 2) were derived from these mean lives together with the measured branching ratios. For comparison with published results which present only multiplet f-values, such f-values were computed from the measured individual line oscillator strengths. The value obtained for the 3p(sup 4)(3)P-4s(sup 3)S(sup 0) multiplet at 1814 A is 0.088 +/- 0.005, in good agreement with the mean of previous experimental measurements and theoretical calculations. With the mean life for the 4s(double prime) 3P(sup 0 sub 0) level set equal to the mean of our determination for the other two 4s(double prime) (3)P(sup 0) levels (a valid assumption for LS coupling conditions, and consistent with the observed equality of the mean lives within the accuracy of our measurement), an oscillator strength for the 1299 A multiplet of 0.121 +/- 0.004 was found. Both results are in good agreement with recent large-scale theoretical calculations that incorporate the effects of configuration interaction.

Beideck, D. J.↗
DOE OSTI2017

Two-Level Convergence Theory for Multigrid Reduction in Time (MGRIT)

Here we develop a two-grid convergence theory for the parallel-in-time scheme known as multigrid reduction in time (MGRIT), as it is implemented in the open-source package [XBraid: Parallel Multigrid in Time, http://llnl.gov/casc/xbraid]. MGRIT is a scalable and multilevel approach to parallel-in-time simulations that nonintrusively uses existing time-stepping schemes, and in a specific two-level setting it is equivalent to the widely known parareal algorithm. The goal of this paper is twofold. First, we present a two-level MGRIT convergence analysis for linear problems where the spatial discretization matrix can be diagonalized, and then apply this analysis to our two basic model problems, the heat equation and the advection equation. One important assumption is that the coarse and fine time-grid propagators can be diagaonalized by the same set of eigenvectors, which is often the case when the same spatial discretization operator is used on the coarse and fine time grids. In many cases, the MGRIT algorithm is guaranteed to converge, and we demonstrate numerically that the theoretically predicted convergence rates are sharp in practice for our model problems. Second, we explore how the convergence of MGRIT compares to the stability of the chosen time-stepping scheme. In particular, we demonstrate that a stable time-stepping scheme does not necessarily imply convergence of MGRIT, although MGRIT with FCF-relaxation always converges for the diffusion dominated problems considered here.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Convergent ab initio analysis of the multi-channel HOBr + H reaction

High-level potential energy surfaces for three reactions of hypobromous acid with atomic hydrogen were computed at the CCSDTQ/CBS//CCSDT(Q)/complete basis set level of theory. Focal point analysis was utilized to extrapolate energies and gradients for energetics and optimizations, respectively. The H attack at Br and subsequent Br–O cleavage were found to proceed barrierlessly. The slightly submerged transition state lies −0.2 kcal mol−1 lower in energy than the reactants and produces OH and HBr. The two other studied reaction paths are the radical substitution to produce H2O and Br with a 4.0 kcal mol−1 barrier and the abstraction at hydrogen to produce BrO and H2 with an 11.2 kcal mol−1 barrier. The final product energies lie −37.2, −67.9, and −7.3 kcal mol−1 lower in energy than reactants, HOBr + H, for the sets of products OH + HBr, H2O + Br, and H2 + BrO, respectively. Additive corrections computed for the final energetics, particularly the zero-point vibrational energies and spin–orbit corrections, significantly impacted the final stationary point energies, with corrections up to 6.2 kcal mol−1.

Chemistry↗
DOE OSTI2021

Automatic Differentiation in MetaPhysicL and Its Applications in MOOSE

Efficient solution via Newton’s method of nonlinear systems of equations requires an accurate representation of the Jacobian, corresponding to the derivatives of the component residual equations with respect to the degrees of freedom. In practice these systems of equations often arise from spatial discretization of partial differential equations used to model physical phenomena. These equations may involve domain motion or material equations that are complex functions of the systems’ degrees of freedom. Computing the Jacobian by hand in these situations is arduous and prone to error. Finite difference approximations of the Jacobian or its action are prone to truncation error, especially in multiphysics settings. Symbolic differentiation packages may be used, but often result in an excessive number of terms in realistic model scenarios. An alternative to symbolic and numerical differentiation is automatic differentiation (AD), which propagates derivatives with every elementary operation of a computer program, corresponding to continual application of the chain rule. Automatic differentiation offers the guarantee of an exact Jacobian at a relatively small overhead cost. In this work, we outline the adoption of AD in the Multiphysics Object Oriented Simulation Environment (MOOSE) via the MetaPhysicL package. We describe the application of MOOSE’s AD capability to several sets of physics that were previously infeasible to model via hand-coded or Jacobian-free simulation techniques, including arbitrary Lagrangian-Eulerian and level-set simulations of laser melt pools, phase-field simulations with free energies provided through neural networks, and metallic nuclear fuel simulations that require inner Newton loop calculation of nonlinear material properties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Omega-Limit Sets and Input-To-State Stability in Power Grids with Switching Equilibria

This paper studies a power transmission system with both conventional generators (CGs) and distributed energy assets (DEAs) providing frequency control. We consider an operating condition with demand aggregating two dynamic components: one that switches between different values on a finite set, and one that varies smoothly over time. Such dynamic operating conditions may result from protection scheme activations, external cyber-attacks, or due to the integration of dynamic loads, such as data centers. Mathematically, the dynamics of the resulting system are captured by a system that switches between a finite number of vector fields - or modes -, with each mode having a distinct equilibrium point induced by the demand aggregation. To analyze the stability properties of the resulting switching system, we leverage tools from hybrid dynamic inclusions and the concept of ..omega.. -limit sets from sets. Specifically, we characterize a compact set that is semi-globally practically asymptotically stable under the assumption that the switching frequency and load variation rate are sufficiently slow. For arbitrarily fast variations of the load, we use a level-set argument with multiple Lyapunov functions to establish input-to-state stability of a larger set and with respect to the rate of change of the loads. The theoretical results are illustrated via numerical simulations on the IEEE 39-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2006

Space and Ground Trades for Human Exploration and Wearable Computing

Human exploration of the Moon and Mars will present unique trade study challenges as ground system elements shift to planetary bodies and perhaps eventually to the bodies of human explorers in the form of wearable computing technologies. This presentation will highlight some of the key space and ground trade issues that will face the Exploration Initiative as NASA begins designing systems for the sustained human exploration of the Moon and Mars, with an emphasis on wearable computing. We will present some preliminary test results and scenarios that demonstrate how wearable computing might affect the trade space noted below. We will first present some background on wearable computing and its utility to NASA's Exploration Initiative. Next, we will discuss three broad architectural themes, some key ground and space trade issues within those themes and how they relate to wearable computing. Lastly, we will present some preliminary test results and suggest guidance for proceeding in the assessment and creation of a value-added role for wearable computing in the Exploration Initiative. The three broad ground-space architectural trade themes we will discuss are: 1. Functional Shift and Distribution: To what extent, if any, should traditional ground system functionality be shifted to, and distributed among, the Earth, Moon/Mars, and the human. explorer? 2. Situational Awareness and Autonomy: How much situational awareness (e.g. environmental conditions, biometrics, etc.) and autonomy is required and desired, and where should these capabilities reside? 3. Functional Redundancy: What functions (e.g. command, control, analysis) should exist simultaneously on Earth, the Moon/Mars, and the human explorer? These three themes can serve as the axes of a three-dimensional trade space, within which architectural solutions reside. We will show how wearable computers can fit into this trade space and what the possible implications could be for the rest of the ground and space architecture(s). We intend this to be an example of explorer-centric thinking in a fully integrated explorer paradigm, where integrated explorer refers to a human explorer having instant access to all relevant data, knowledge of the environment, science models, health and safety-related events, and other tools and information via wearable computing technologies. The trade study approach will include involvement from the relevant stakeholders (Constellation Systems, CCCI, EVA Project Office, Astronaut office, Mission Operations, Space Life Sciences, etc.) to develop operations concepts (and/or operations scenarios) from which a basic high-level set of requirements could be extracted. This set of requirements could serve as a foundation (along with stakeholder buy-in) that would help define the trade space and assist in identifying candidate technologies for further study and evolution to higher-level technology readiness levels.

Lupisella, Mark↗
DOE OSTI2018

Crickets{sup TM} and Curies: Lessons Learned from the Steel Industry - 18221

The global nuclear power industry, and to a lesser extent, the decommissioning and demolition of old nuclear weapons plants, obviously present challenges to those in the radioactive waste management field. Some if not many of these challenges have already been dealt with, and resolved, in the steel industry, including its recycling component. This paper presents proven state-of-the-art radiation detection systems used in steel and related recycling facilities, emphasizing current, reliable and flexible technologies for characterization, volume reduction, and remote handling of recyclable solid wastes contaminated and, just as important, not contaminated, with a wide range of radioactive isotopes. It will also cover features of remotely operated waste handling equipment effective in reducing or eliminating exposure of workers engaged in decontamination and demolition work on active and/or inactive nuclear installations. The industry group identified above has a long-standing policy regarding any radioactivity in potentially recyclable as well as waste materials it receives: if it is detected, it is rejected. The US Steel Manufacturers Association (SMA) put it this way in one of their Public Policy Statements: 'SMA members have not, and will not, accept scrap that is known to be radioactively contaminated' (emphasis included in the original) (1). This policy, adopted around the globe, obviously has major implications for decommissioning and demolition projects. To put it bluntly, if rad-contaminated metal, concrete, or other materials are sent to a facility for possible recycling, reuse or even disposal, they may well be rejected. If so, the materials will be returned to the generator--at the generator's cost-and a new solution will have to be found. This also results in additional costs for the generator. Facilities in the steel making and metal recycling industries have access to, and routinely count on, a wide range of proven detection technologies and techniques for monitoring incoming shipments and sorting the materials in them. The approaches range from using sensitive handheld instruments for pinpointing and isolating small devices such as isotope-containing gauges and radium dials all the way up to technologies effective for large volumes and weights of contaminated construction and demolition material. In this latter realm, the most suitable, robust, and field-proven system for decommissioning and demolition work is a radiation detection system fitted to a grappling and/or magnetic device, known as the Crickets{sup TM} technology, which automatically scans bulk material with no added effort or time in material handling operations. Highly versatile, a Crickets{sup TM} system can be put to work on any material-handling system, including grapples handling volumes ranging from 1 up to 18 cubic yards, while detecting radioactivity in real-time over a very wide dose range, from nSv to Sv levels. Other field-proven real-time measuring radiation detection devices can be fixed to conveyor belts with traverse speeds up 3 meters/second, also measuring in real time and over the same dose range, allowing both recyclable and waste materials with a pre-set level of radioactivity to be diverted off the belt. Finally, there are highly sensitive radiation portal installations for detecting radiation from materials being transported by vehicles, including those with roll-offs, dump trailers, and other containers, again in real-time and for the same dose ranges. For vehicles, the speed must be carefully controlled-the vehicles need to travel from 5 to 10 km/h through the scanning zone to ensure that maximum detection capability is maintained. When radiation detection systems at recycling and steel making facilities detect radioactive material in an incoming shipment, these facilities have a zero tolerance for accepting the cargo. Therefore, it is imperative that material from a demolition operation that is slated to be sent for recycling or other reuse be checked at the point of demolition at similar detection levels to avoid possible rejection later of a shipment because of its radioactivity. In addition to measuring overall radiation levels (for example, total gamma), when necessary, combinations of different radiation detection media can be used to detect the presence and intensities of specific isotopes such as U-235, Cs-137, Co-60, Am-241, etc., again in real-time and over a similar dose range. These detection technologies can be fixed or transportable. More important for the rad-waste management profession, this overall systems approach can be tailored and adapted during use on-site in any dismantling, demolition or remediation project, to allow materials to be thoroughly scanned before being released to the recycling stream for reuse, or to appropriate long-term storage and disposal facilities. Potentially recyclable materials with contamination such as steel beams and rebar will set off alarms at recycling facilities, resulting in unnecessary added expenses to the generator, primarily due to increased transportation costs, time delays and additional rad-waste handling and disposal charges. Additionally, there are situations where relatively lightly contaminated materials, once identified and appropriately characterized, can be reused in new construction applications, such as concrete from demolition being used in the base layer for roads or recycled steel used for repair or construction of bridges. In other cases, specific smaller volumes can be sent to specialized rad-waste disposal sites. These radiation detection systems can also be custom tailored to ensure proper handling and disposition of contaminated materials destined for reuse in specific applications where, for example, acceptable levels of radioactivity in NORM or TENORM can be reused or safely disposed of. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1992

Consumables and wastes estimations for the First Lunar Outpost

The First Lunar Outpost mission is a design reference mission for the first human return to the moon. This paper describes a set of consumables and waste material estimations made on the basis of the First Lunar Outpost mission scenario developed by the NASA Exploration Programs Office. The study includes the definition of a functional interface framework and a top-level set of consumables and waste materials to be evaluated, the compilation of mass flow information from mission developers supplemented with information from the literature, and the analysis of the resulting mass flow information to gain insight about the possibility of material flow integration between the moon outpost elements. The results of the study of the details of the piloted mission and the habitat are used to identify areas where integration of consumables and wastes across different mission elements could provide possible launch mass savings.

Theis, Ronald L. A.↗
DOE OSTI2016

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy

Purpose: For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Methods: Considering the complex H&N structures and ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28% ± 1.46%) and margin error (0.49 ± 0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. Conclusions: The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-207A-07: Prediction of High Dimensional State Subject to Respiratory Motion: A Manifold Learning Approach

Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction reliability in such low dimensional manifold. The fixed-point iterative approach turns out to work well practically for the pre-image recovery. Our approach is particularly suitable to facilitate managing respiratory motion in image-guide radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-H-CAMPUS-JeP2-03: Machine-Learning-Based Delineation Framework of GTV Regions of Solid and Ground Glass Opacity Lung Tumors at Datasets of Planning CT and PET/CT Images

Purpose: In radiation treatment planning, delineation of gross tumor volume (GTV) is very important, because the GTVs affect the accuracies of radiation therapy procedure. To assist radiation oncologists in the delineation of GTV regions while treatment planning for lung cancer, we have proposed a machine-learning-based delineation framework of GTV regions of solid and ground glass opacity (GGO) lung tumors following by optimum contour selection (OCS) method. Methods: Our basic idea was to feed voxel-based image features around GTV contours determined by radiation oncologists into a machine learning classifier in the training step, after which the classifier produced the degree of GTV for each voxel in the testing step. Ten data sets of planning CT and PET/CT images were selected for this study. The support vector machine (SVM), which learned voxel-based features which include voxel value and magnitudes of image gradient vector that obtained from each voxel in the planning CT and PET/CT images, extracted initial GTV regions. The final GTV regions were determined using the OCS method that was able to select a global optimum object contour based on multiple active delineations with a level set method around the GTV. To evaluate the results of proposed framework for ten cases (solid:6, GGO:4), we used the three-dimensional Dice similarity coefficient (DSC), which denoted the degree of region similarity between the GTVs delineated by radiation oncologists and the proposed framework. Results: The proposed method achieved an average three-dimensional DSC of 0.81 for ten lung cancer patients, while a standardized uptake value-based method segmented GTV regions with the DSC of 0.43. The average DSCs for solid and GGO were 0.84 and 0.76, respectively, obtained by the proposed framework. Conclusion: The proposed framework with the support vector machine may be useful for assisting radiation oncologists in delineating solid and GGO lung tumors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

On the parameter combinations that matter and on those that do not: data-driven studies of parameter (non)identifiability

Abstract We present a data-driven approach to characterizing nonidentifiability of a model’s parameters and illustrate it through dynamic as well as steady kinetic models. By employing Diffusion Maps and their extensions, we discover the minimal combinations of parameters required to characterize the output behavior of a chemical system: a set of effective parameters for the model. Furthermore, we introduce and use a Conformal Autoencoder Neural Network technique, as well as a kernel-based Jointly Smooth Function technique, to disentangle the redundant parameter combinations that do not affect the output behavior from the ones that do. We discuss the interpretability of our data-driven effective parameters, and demonstrate the utility of the approach both for behavior prediction and parameter estimation. In the latter task, it becomes important to describe level sets in parameter space that are consistent with a particular output behavior. We validate our approach on a model of multisite phosphorylation, where a reduced set of effective parameters (nonlinear combinations of the physical ones) has previously been established analytically.

Evangelou, Nikolaos↗
DOE OSTI2021

A coupled discontinuous Galerkin-Finite Volume framework for solving gas dynamics over embedded geometries

Herein, we present a computational framework for solving the equations of inviscid gas dynamics using structured grids with embedded geometries. The novelty of the proposed approach is the use of high-order discontinuous Galerkin (dG) schemes and a shock-capturing Finite Volume (FV) scheme coupled via an hp adaptive mesh refinement (hp-AMR) strategy that offers high-order accurate resolution of the embedded geometries. The hp-AMR strategy is based on a multi-level block-structured domain partition in which each level is represented by block-structured Cartesian grids and the embedded geometry is represented implicitly by a level set function. The intersection of the embedded geometry with the grids produces the implicitly-defined mesh that consists of a collection of regular rectangular cells plus a relatively small number of irregular curved elements in the vicinity of the embedded boundaries. High-order quadrature rules for implicitly-defined domains enable high-order accuracy resolution of the curved elements with a cell-merging strategy to address the small-cell problem. The hp-AMR algorithm treats the system with a second-order finite volume scheme at the finest level to dynamically track the evolution of solution discontinuities while using dG schemes at coarser levels to provide high-order accuracy in smooth regions of the flow. On the dG levels, the methodology supports different orders of basis functions on different levels. The space-discretized governing equations are then advanced explicitly in time using high-order Runge-Kutta algorithms. Numerical tests are presented for two-dimensional and three-dimensional problems involving an ideal gas. The results are compared with both analytical solutions and experimental observations and demonstrate that the framework provides high-order accuracy for smooth flows and accurately captures solution discontinuities.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

CDC Bioreactor Configuration Method for Volume Level Control with Controlled Inlet and Outlet Flow

Environmental Control Life Support Systems and other microbiological biofilm studies often utilize small scale bioreactors. Among these options are the popular BioSurface CDC bioreactors, currently being utilized by Marshall Space Flight Center groups researching the impact of biofilms on life support systems. After a recent experimental regime, it was determined additional equipment could be added to augment the capabilities of the bioreactors. Previous research configurations such as ASTM E3161 – 18 relied on an outlet stream gravity draining from a side drain port located above sampling coupons. This limited applications to experimental conditions with a controlled inlet and uncontrolled outlet flow. With the introduction of a small single pole single throw (SPST) reed float switch, a peristaltic pump connected to the outlet drain and a chassis controller, the bioreactor is able to maintain a set level. The modification allows additional variables to be tested, including highly adjustable fill and flush cycles, bioreactor volume, draining and filling control. Once the configuration modifications were implemented through the installation of the new equipment, data was collected to ensure the stability of the level measurements. As the level control switch is a float switch, consideration was taken into account for effects of internal stirring speed, along with effects of inlet and outlet flow rate. Data presented in this study will illustrate the stability and effectiveness of the configuration changes in equipment made to the bioreactor. These configuration changes are proving an effective control method to conduct biofilm mitigation techniques for ECLSS hardware research. The controlled level capabilities allow for a constant drip feed flow rate into the bioreactors, a key aspect of the biofilm mitigation testing.

CDC Bioreactor↗