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At least 163 records · Page 9

Combustion kinetics and sensitivity analysis computations

The stiff ordinary differential equation solution methods more commonly used for chemical kinetics problems are examined, and the efficiency and accuracy of several of the methods are compared by applying them to two combustion kinetics problems. The local sensitivity analysis methods developed to date are outlined, and their advantages and difficulties are briefly discussed. Examples are used to make comparisons among the different techniques.

Radhakrishnan, K.↗

Gravitropism in higher plant shoots. V - Changing sensitivity to auxin

The relationship in plants between the sensitivity to auxin and differential growth and bending was investigated experimentally. Decapitated and marked sunflower hypocotyl sections were immersed in buffered auxin solutions of different concentrations (0, 10 to the -8th, or 0.001 molar) and were photographed at 1/2 hr intervals; the negatives were analyzed with a digitizer/computer to evaluate surface-length changes in terms of Michaelis-Menten enzyme kinetics. It was found that bending decreased with increasing concentration of auxin. Increasing the auxin concentration inhibits the elongation growth of lower surfaces but promotes upper-surface growth, indicating that the lower surfaces have a greater Km sensitivity to applied auxin than the upper surfaces. At optimum auxin levels (maximum growth), the growth of bottom surfaces exceeded that of top surfaces, indicating that bottom tissues had a greater Vmax sensitivity.

Salisbury, Frank B.↗

Informing nuclear physics via machine learning methods with differential and integral experiments

Information from differential nuclear-physics experiments and theory is often too uncertain to accurately define nuclear-physics observables such as cross sections or energy spectra. Integral experimental data, representing the applications of these observables, are often more precise but depend simultaneously on too many of them to unambiguously identify issues in the observable with human expert analysis alone. Here, we explore how we can leverage physics knowledge gained from differential experimental data, nuclear theory, integral experiments, and neutron-transport calculations to better understand nuclear-physics observables in the context of the application area represented by integral experiments. We support this task with machine-learning methods to discern trends in a large amount of convoluted data. Differential and integral information was used in an analysis augmented by the random forest and the Shapley additive explanations metric. We chose as an application area one that is represented by criticality measurements and pulsed-sphere neutron-leakage spectra. We show one representative example ( 241 Pu fission observables) where the combination of differential and integral information allowed to resolve issues in data representing these observables. As a starting point, the machine learning (ML) algorithms highlighted several observables as leading potentially to bias in simulating integral experiments. Differential information, paired with sensitivity to integral quantities, allowed us then to pinpoint one specific observable ( 241 Pu fission cross section) as the main driver of bias. The comparison to integral experiments, on the other hand, allowed us to indicate a likely reliable experiment among several discrepant ones for this observables. In other cases (e.g., 239 Pu observables), we were not able to resolve the confounding introduced by integral experiments but instead highlighted the need for targeted new experiments and theory developments to better constrain the nuclear-physics space for the application area represented by integral experiments. We were able to combine information from differential experimental data, nuclear-physics theory, integral experiments, and neutron-transport simulations of the latter experiments with the help of the random forest algorithm and expert judgment. This combination of knowledge allows to improve our description of nuclear-physics observables as applied to a particular application area.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice

The evolution of breast tumors greatly depends on the interaction network among different cell types, including immune cells and cancer cells in the tumor. This study takes advantage of newly collected rich spatio-temporal mouse data to develop a data-driven mathematical model of breast tumors that considers cells’ location and key interactions in the tumor. The results show that cancer cells have a minor presence in the area with the most overall immune cells, and the number of activated immune cells in the tumor is depleted over time when there is no influx of immune cells. Interestingly, in the case of the influx of immune cells, the highest concentrations of both T cells and cancer cells are in the boundary of the tumor, as we use the Robin boundary condition to model the influx of immune cells. In other words, the influx of immune cells causes a dominant outward advection for cancer cells. We also investigate the effect of cells’ diffusion and immune cells’ influx rates in the dynamics of cells in the tumor micro-environment. Sensitivity analyses indicate that cancer cells and adipocytes’ diffusion rates are the most sensitive parameters, followed by influx and diffusion rates of cytotoxic T cells, implying that targeting them is a possible treatment strategy for breast cancer.

60 APPLIED LIFE SCIENCES↗

J/Psi Photoproduction Near Threshold With CLAS12

The structure of the proton is comprised of quarks and a sea of gluons. A mechanism that can extract the characteristics of the hidden-color correlations of the nuclear wavefunction is the production of charm near threshold. Due to the fact that momentum transfer is large near threshold in the production of J/ψ , all three valence quarks must act coherently to ex- change energy for the reaction to occur. Models have been developed to predict the nature of J/ψ photoproduction at these specific energies. These include production mechanisms with the two-gluon and three-gluon exchanges. The transferred momentum dependence of the differential cross sections are sensitive to the gluonic form factors, which describe the distribution of color charge in the proton. The CLAS12 detector is capable of measuring J/ψ photoproduction at the energy range close to the threshold. Work showcased in this dissertation encompasses the preparation of the CLAS12 experiments, including the optimization of tracking reconstruction through the study of the Torus magnetic field. In terms of software, contributions were made to the CLAS12 Event Builder, a key stage of reconstruction where event-by-event information is summarized for efficient data analysis. After the run periods were successfully completed, analysis of the RG-A data commenced and an analysis framework was developed to measure the differential and total cross sections of J/ψ photoproduction in Hall B.

Newton, Joseph↗

A Mathematical Model of Breast Tumor Progression Based on Immune Infiltration

Breast cancer is the most prominent type of cancer among women. Understanding the microenvironment of breast cancer and the interactions between cells and cytokines will lead to better treatment approaches for patients. In this study, we developed a data-driven mathematical model to investigate the dynamics of key cells and cytokines involved in breast cancer development. We used gene expression profiles of tumors to estimate the relative abundance of each immune cell and group patients based on their immune patterns. Dynamical results show the complex interplay between cells and molecules, and sensitivity analysis emphasizes the direct effects of macrophages and adipocytes on cancer cell growth. In addition, we observed the dual effect of IFN-γ on cancer proliferation, either through direct inhibition of cancer cells or by increasing the cytotoxicity of CD8+ T-cells.

60 APPLIED LIFE SCIENCES↗

Sensitivity derivatives for advanced CFD algorithm and viscous modelling parameters via automatic differentiation

The computational technique of automatic differentiation (AD) is applied to a three-dimensional thin-layer Navier-Stokes multigrid flow solver to assess the feasibility and computational impact of obtaining exact sensitivity derivatives typical of those needed for sensitivity analyses. Calculations are performed for an ONERA M6 wing in transonic flow with both the Baldwin-Lomax and Johnson-King turbulence models. The wing lift, drag, and pitching moment coefficients are differentiated with respect to two different groups of input parameters. The first group consists of the second- and fourth-order damping coefficients of the computational algorithm, whereas the second group consists of two parameters in the viscous turbulent flow physics modelling. Results obtained via AD are compared, for both accuracy and computational efficiency with the results obtained with divided differences (DD). The AD results are accurate, extremely simple to obtain, and show significant computational advantage over those obtained by DD for some cases.

Green, Lawrence L.↗

Novel strategies for modal-based structural material identification

Here, we present modal-based methods for model calibration in structural dynamics, and address several key challenges in the solution of gradient-based optimization problems with eigenvalues and eigenvectors, including the solution of singular Helmholtz problems encountered in sensitivity calculations, non-differentiable objective functions caused by mode swapping during optimization, and cases with repeated eigenvalues. Unlike previous literature that relied on direct solution of the eigenvector adjoint equations, we present a parallel iterative domain decomposition strategy (Adjoint Computation via Modal Superposition with Truncation Augmentation) for the solution of the singular Helmholtz problems. For problems with repeated eigenvalues we present a novel Mode Separation via Projection algorithm, and in order to address mode swapping between inverse iterations we present a novel Injective mode ordering metric. We present the implementation of these methods in a massively parallel finite element framework with the ability to use measured modal data to extract unknown structural model parameters from large complex problems. A series of increasingly complex numerical examples are presented that demonstrate the implementation and performance of the methods in a massively parallel finite element framework [7], [5], using gradient-based optimization techniques in the Rapid Optimization Library (ROL) [21].

36 MATERIALS SCIENCE↗

Suppression of voltage-decay in Li 2 MnO 3 cathode via reconstruction of layered-spinel coexisting phases

Voltage decay, i.e., the voltage decrease during electrochemical cycling, has been a decade-long challenge for lithium-ion batteries. This issue not only leads to a substantial loss of energy density, but also raises challenges for the battery management system, hindering the commercial application of high capacity lithium-rich oxide. Here, we show that through a combination of electrochemical conditioning and thermal treatment, Li 2 MnO 3 , the parent compound of lithium-rich oxide, which typically displays severe voltage and capacity decay, could be converted into a new phase that essentially suppresses the voltage decay with improved capacity retention and rate performance. Furthermore, by combining atomic-sensitive nuclear magnetic resonance, differential electrochemical mass spectrometry and synchrotron-based resonant inelastic X-ray scattering, we disclose that treatment triggers the formation of three-coexisting phases, i.e., the lithium-rich layered, spinel and defect spinel phases, which enables improved reversibility of the oxygen redox activity and enhanced manganese redox reactions in the initial cycle. Our findings suggest the key role of the local structure in the voltage decay problem and provide insights for material optimizations towards lithium- and manganese-rich cathodes without the voltage decay.

25 ENERGY STORAGE↗

Insights into pathological mechanisms and interventions revealed by analyzing a mathematical model for cone metabolism

This work analyzes a mathematical model for the metabolic dynamics of a cone photoreceptor, which is the first model to account for energy generation from fatty acids oxidation of shed photoreceptor outer segments (POS). Multiple parameter bifurcation analysis shows that joint variations in external glucose, the efficiency of glucose transporter 1 (GLUT1), lipid utilization for POS renewal, and oxidation of fatty acids affect the cone’s metabolic vitality and its capability to adapt under glucose-deficient conditions. The analysis further reveals that when glucose is scarce, cone viability cannot be sustained by only fueling energy production in the mitochondria, but it also requires supporting anabolic processes to create lipids necessary for cell maintenance and repair. In silico experiments are used to investigate how the duration of glucose deprivation impacts the cell without and with a potential GLUT1 or oxidation of fatty acids intervention as well as a dual intervention. The results show that for prolonged duration of glucose deprivation, the cone metabolic system does not recover with higher oxidation of fatty acids and requires greater effectiveness of GLUT1 to recover. Finally, time-varying global sensitivity analysis (GSA) is applied to assess the sensitivity of the model outputs of interest to changes and uncertainty in the parameters at specific times. The results reveal a critical temporal window where there would be more flexibility for interventions to rescue a cone cell from the detrimental consequences of glucose shortage.

59 BASIC BIOLOGICAL SCIENCES↗

The Simons Observatory: Cryogenic half wave plate rotation mechanism for the small aperture telescopes

We present the requirements, design, and evaluation of the cryogenic continuously rotating half-wave plate (CHWP) for the Simons Observatory (SO). SO is a cosmic microwave background polarization experiment at Parque Astronómico de Atacama in northern Chile that covers a wide range of angular scales using both small (Ø0.42 m) and large (Ø6 m) aperture telescopes. In particular, the small aperture telescopes (SATs) focus on large angular scales for primordial B-mode polarization. To this end, the SATs employ a CHWP to modulate the polarization of the incident light at 8 Hz, suppressing atmospheric 1/f noise and mitigating systematic uncertainties that would otherwise arise due to the differential response of detectors sensitive to orthogonal polarizations. The CHWP consists of a 505 mm diameter achromatic sapphire HWP and a cryogenic rotation mechanism, both of which are cooled down to ~50 K to reduce detector thermal loading. Under normal operation, the HWP is suspended by a superconducting magnetic bearing and rotates with a constant 2 Hz frequency, controlled by an electromagnetic synchronous motor. We find that the number of superconductors and the number of magnets that make up the superconducting magnetic bearing are important design parameters, especially for the rotation mechanism’s vibration performance. The rotation angle is detected through an angular encoder with a noise level of 0.07 μrad √ $\overline{s}$. During a cooldown process, the rotor is held in place by a grip-and-release mechanism that serves as both an alignment device and a thermal path. In this paper, we provide an overview of the SO SAT CHWP: its requirements, hardware design, and laboratory performance.

47 OTHER INSTRUMENTATION↗

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma

Abstract Background Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients. Objectives To determine if artificial intelligence and machine learning might help to stratify patients with cSCC by risk using more than solely clinical and histopathological factors. Methods We retrieved a retrospective cohort of 104 patients whose cSCCs had been excised with clear margins. Clinical and histopathological risk factors were evaluated. Haematoxylin and eosin-stained slides were scanned and analysed by an algorithm based on the stacked predictive sparse decomposition technique. Cellular morphometric biomarkers (CMBs) were identified via machine learning and used to derive a cellular morphometric risk score (CMRS) that classified cSCCs into clusters of differential prognoses. Concordance analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated and compared with results obtained with the Brigham and Women’s Hospital (BWH) staging system. The performance of the combination of the BWH staging system and the CMBs was also analysed. Results There were no differences among the CMRS groups in terms of clinical and histopathological risk factors and T-stage assignment, but there were significant differences in prognosis. Combining the CMRS with BWH staging systems increased distinctiveness and improved prognostic performance. C-indices were 0.91 local recurrence and 0.91 for nodal metastasis when combining the two approaches. The NPV was 94.41% and 96.00%, the PPV was 36.36% and 41.67%, and accuracy reached 86.75% and 89.16%, respectively, with the combined approach. Conclusions CMRS is helpful for cSCC risk stratification beyond classic clinical and histopathological risk features. Combining the information from the CMRS and the BWH staging system offers outstanding prognostic performance for patients with high-risk cSCC.

Pérez-Baena, Manuel J.↗

Investigation of tidal displacements of the earth's surface by laser ranging to GEOS-3

Two different approaches to the problem were investigated: (1) a dynamic method that computed pass-to-pass apparent movements in station height relative to short arcs fitted to several passes of data from the same station, and (2) a quasi-geometric method that reduces the dependence on unmodelled satellite dynamics to a knowledge of only the radial position of the satellite by considering two-station simultaneous ranging at the precise time that the satellite passes through the plane defined by the two stations and the center of the mass of the earth. The dynamic method was applied to 24-hour arcs in an attempt to study the total tidal displacement at Goddard, but it was found to be unsuitable. The quasi-geometry method, on the other hand, is significantly less influenced by these effects because it is sensitive principally to the differential tidal displacements between laser stations. Using this method, a good approximation to the theoretical Love number h sub 2 was obtained from five passes over the GEOS-3 calibration area when a systematic bias of 2.16 meters was allowed in the radial distance to the satellite.

Bower, D. R.↗

Quality assurance procedures for V378A matrix resin

A characterization methodology has been developed on which to base quality assurance procedures for U.S. Polymeric V378A bismaleimide matrix resin. Chemical composition is established by partition reverse phase and size exclusion liquid chromatography. Cure rheology behavior is quantitatively characterized by dynamic viscoelastic analysis using the parallel plate technique. The overall cure process is characterized by differential scanning calorimetry. The sensitivity of the procedures is evaluated by studying the effects of ambient out time on the chemical end behaviorial properties of the resin.

Hamermesh, C. L.↗

Rotational modulation and flares on RS CVn and BY Dra stars. VI - Physical parameters of the chromospheres/transition regions of V 711 Tau (HR 1099), II Peg and AR Lac during October 1981

Ground-based optical and IUE satellite-ultraviolet observations of three RS CVn stars are combined with density sensitive line ratios and differential emission measure curves to describe the physical conditions in their outer atmospheres. Solar-like densities are found to be representative of average conditions on two of the stars, V 711 Tau and AR Lac. The total radiative losses from these two stars are estimated and found to be larger than the sun by at least two orders of magnitude. Consideration of the volume emitting in two of the principal transition region lines suggests a possible relation between the disk 'filling factor' for these two lines and the dynamo-related Rossby number. Only one hemisphere of the star II Peg, the one showing least evidence of starspots, is similar. On the opposite hemisphere the presence of a discrete emitting region is deduced which is almost coincident in phase with the passage of the dominant optical spot group across the visible disk. The dimensions of this region, and an illustrative interpretation in terms of a large emitting magnetic loop, are discussed. It is compared to large active region loops on the sun.

Byrne, P. B.↗

Session on High Speed Civil Transport Design Capability Using MDO and High Performance Computing

Since the inception of CAS in 1992, NASA Langley has been conducting research into applying multidisciplinary optimization (MDO) and high performance computing toward reducing aircraft design cycle time. The focus of this research has been the development of a series of computational frameworks and associated applications that increased in capability, complexity, and performance over time. The culmination of this effort is an automated high-fidelity analysis capability for a high speed civil transport (HSCT) vehicle installed on a network of heterogeneous computers with a computational framework built using Common Object Request Broker Architecture (CORBA) and Java. The main focus of the research in the early years was the development of the Framework for Interdisciplinary Design Optimization (FIDO) and associated HSCT applications. While the FIDO effort was eventually halted, work continued on HSCT applications of ever increasing complexity. The current application, HSCT4.0, employs high fidelity CFD and FEM analysis codes. For each analysis cycle, the vehicle geometry and computational grids are updated using new values for design variables. Processes for aeroelastic trim, loads convergence, displacement transfer, stress and buckling, and performance have been developed. In all, a total of 70 processes are integrated in the analysis framework. Many of the key processes include automatic differentiation capabilities to provide sensitivity information that can be used in optimization. A software engineering process was developed to manage this large project. Defining the interactions among 70 processes turned out to be an enormous, but essential, task. A formal requirements document was prepared that defined data flow among processes and subprocesses. A design document was then developed that translated the requirements into actual software design. A validation program was defined and implemented to ensure that codes integrated into the framework produced the same results as their standalone counterparts. Finally, a Commercial Off the Shelf (COTS) configuration management system was used to organize the software development. A computational environment, CJOPT, based on the Common Object Request Broker Architecture, CORBA, and the Java programming language has been developed as a framework for multidisciplinary analysis and Optimization. The environment exploits the parallelisms inherent in the application and distributes the constituent disciplines on machines best suited to their needs. In CJOpt, a discipline code is "wrapped" as an object. An interface to the object identifies the functionality (services) provided by the discipline, defined in Interface Definition Language (IDL) and implemented using Java. The results of using the HSCT4.0 capability are described. A summary of lessons learned is also presented. The use of some of the processes, codes, and techniques by industry are highlighted. The application of the methodology developed in this research to other aircraft are described. Finally, we show how the experience gained is being applied to entirely new vehicles, such as the Reusable Space Transportation System. Additional information is contained in the original.

Rehder, Joe↗

Flutter Sensitivity to Boundary Layer Thickness, Structural Damping, and Static Pressure Differential for a Shuttle Tile Overlay Repair Concept

This paper examines the aeroelastic stability of an on-orbit installable Space Shuttle patch panel. CFD flutter solutions were obtained for thick and thin boundary layers at a free stream Mach number of 2.0 and several Mach numbers near sonic speed. The effect of structural damping on these flutter solutions was also examined, and the effect of structural nonlinearities associated with in-plane forces in the panel was considered on the worst case linear flutter solution. The results of the study indicated that adequate flutter margins exist for the panel at the Mach numbers examined. The addition of structural damping improved flutter margins as did the inclusion of nonlinear effects associated with a static pressure difference across the panel.

Scott, Robert C.↗

TPSAS-NF1676L-10746-DND

This paper presents the design, development, and field testing of a high sensitivity ground-based Differential Absorption Lidar (DIAL) system that was developed under the NASA Instrument Incubator Program. The investigation presents a significant advancement towards the development of future CO2 profiling capability as it incorporates key elements of technologies needed for a future development of global CO2 measuring systems including: (1) 2-μm laser technologies that have been developed under a number of NASA programs including the Laser Risk Reduction Program (LRRP) (2) A novel high quantum efficiency (QE), high gain (without excess noise factor), and low noise phototransistor, and (3) Direct detection DIAL system using a large collection area receiver that is insensitive to speckle and coherence length effects from atmospheric turbulence that influences heterodyne detection systems. The objective of the project was a system TRL of 4, and the goal was TRL 5. Development and testing of the laser, new detector, and receiver systems during the project, integration into a complete lidar system into a trailer, field testing of system at West Branch, IA and comparison of the lidar CO2 measurements with in situ sensors advanced the system to a TRL of 5. The system demonstrated high vertical resolution CO2 profiling capability within the boundary layer and column measurements to long ranges. This is the first direct detection demonstration of a 2-micron CO2 DIAL high vertical resolution capability from instrument concept to field demonstration.

Syed Ismail↗