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NASA NTRS1993

Induced activation study of LDEF

Analysis of the induced radioactivity of the Long Duration Exposure Facility (LDEF) is continuing with extraction of specific activities for various spacecraft materials. Data and results of activation measurements from eight facilities are being collected for interpretation at Eastern Kentucky University and NASA/Marshall Space Flight Center. The major activation mechanism in LDEF components is the proton flux in the South Atlantic Anomaly (SAA). This flux is highly anisotropic, and could be sampled by taking advantage of the gravity-gradient stabilization of the LDEF. The directionally-dependent activation due to these protons was clearly observed in the data from aluminum experiment tray clamps (reaction product Na-22), steel trunnions (reaction product Mn-54 and others) and is also indicated by the presence of a variety of nuclides in other materials. A secondary production mechanism, thermal neutron capture, was observed in cobalt, indium, and tantalum, which are known to have large capture cross sections. Experiments containing samples of these metals and significant amounts of thermalizing low atomic number (Z) material showed clear evidence of enhanced activation of Co-60, In-114m, and Ta-182. Other mechanisms which activate spacecraft material that are not as easily separable from SAA proton activation, such as galactic proton bombardment and secondary production by fast neutrons, are being investigated by comparison to radiation environmental calculations. Deviations from one-dimensional radiation models indicate that these mechanisms are more important at greater shielding depths. The current status of the induced radioactivity measurements as of mid-year 1992 are reviewed. Specific activities for a number of materials which show SAA effects and thermal neutron capture are presented. The results for consistency by combining data from the participating institutions is also examined.

Harmon, B. A.↗
NASA NTRS2010

Tool for Forecasting Cool-Season Peak Winds Across Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily morning forecast for ground and space launch operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45th Weather Squadron (45 WS) must issue forecast advisories for KSC/CCAFS when they expect peak gusts for >= 25, >= 35, and >= 50 kt thresholds at any level from the surface to 300 ft. In Phase I of this task, the 45 WS tasked the Applied Meteorology Unit (AMU) to develop a cool-season (October - April) tool to help forecast the non-convective peak wind from the surface to 300 ft at KSC/CCAFS. During the warm season, these wind speeds are rarely exceeded except during convective winds or under the influence of tropical cyclones, for which other techniques are already in use. The tool used single and multiple linear regression equations to predict the peak wind from the morning sounding. The forecaster manually entered several observed sounding parameters into a Microsoft Excel graphical user interface (GUI), and then the tool displayed the forecast peak wind speed, average wind speed at the time of the peak wind, the timing of the peak wind and the probability the peak wind will meet or exceed 35, 50 and 60 kt. The 45 WS customers later dropped the requirement for >= 60 kt wind warnings. During Phase II of this task, the AMU expanded the period of record (POR) by six years to increase the number of observations used to create the forecast equations. A large number of possible predictors were evaluated from archived soundings, including inversion depth and strength, low-level wind shear, mixing height, temperature lapse rate and winds from the surface to 3000 ft. Each day in the POR was stratified in a number of ways, such as by low-level wind direction, synoptic weather pattern, precipitation and Bulk Richardson number. The most accurate Phase II equations were then selected for an independent verification. The Phase I and II forecast methods were compared using an independent verification data set. The two methods were compared to climatology, wind warnings and advisories issued by the 45 WS, and North American Mesoscale (NAM) model (MesoNAM) forecast winds. The performance of the Phase I and II methods were similar with respect to mean absolute error. Since the Phase I data were not stratified by precipitation, this method's peak wind forecasts had a large negative bias on days with precipitation and a small positive bias on days with no precipitation. Overall, the climatology methods performed the worst while the MesoNAM performed the best. Since the MesoNAM winds were the most accurate in the comparison, the final version of the tool was based on the MesoNAM winds. The probability the peak wind will meet or exceed the warning thresholds were based on the one standard deviation error bars from the linear regression. For example, the linear regression might forecast the most likely peak speed to be 35 kt and the error bars used to calculate that the probability of >= 25 kt = 76%, the probability of >= 35 kt = 50%, and the probability of >= 50 kt = 19%. The authors have not seen this application of linear regression error bars in any other meteorological applications. Although probability forecast tools should usually be developed with logistic regression, this technique could be easily generalized to any linear regression forecast tool to estimate the probability of exceeding any desired threshold . This could be useful for previously developed linear regression forecast tools or new forecast applications where statistical analysis software to perform logistic regression is not available. The tool was delivered in two formats - a Microsoft Excel GUI and a Tool Command Language/Tool Kit (Tcl/Tk) GUI in the Meteorological Interactive Data Display System (MIDDS). The Microsoft Excel GUI reads a MesoNAM text file containing hourly forecasts from 0 to 84 hours, from one model run (00 or 12 UTC). The GUI then displays e peak wind speed, average wind speed, and the probability the peak wind will meet or exceed the 25-, 35- and 50-kt thresholds. The user can display the Day-1 through Day-3 peak wind forecasts, and separate forecasts are made for precipitation and non-precipitation days. The MIDDS GUI uses data from the NAM and Global Forecast System (GFS), instead of the MesoNAM. It can display Day-1 and Day-2 forecasts using NAM data, and Day-1 through Day-5 forecasts using GFS data. The timing of the peak wind is not displayed, since the independent verification showed that none of the forecast methods performed significantly better than climatology. The forecaster should use the climatological timing of the peak wind (2248 UTC) as a first guess and then adjust it based on the movement of weather features.

Barrett, Joe H., III↗
DOE OSTI2018

Heat capacity of Mg 3 Sb 2 , Mg 3 Bi 2 , and their alloys at high temperature

The thermoelectric figure of merit reported for n-type Mg 3 (Sb,Bi) 2 compounds has made these materials of great engineering significance, increasing the need for accurate evaluations of their thermal conductivity. Thermal conductivity is typically derived from measurements of thermal diffusivity and determination of the specific heat capacity. The uncertainty in this method (often 10% or more) is frequently attributed to measurement of heat capacity such that estimated values are often more accurate. Inconsistencies between reported thermal conductivity of Mg 3 (Sb,Bi) 2 compounds may be attributed to the different values of heat capacity measured or used to calculate thermal conductivity. The high anharmonicity of these materials can lead to significant deviations at high temperatures from the Dulong-Petit heat capacity, which is often a reasonable substitute for measurements at high temperatures. Herein, a physics-based model is used to assess the magnitude of the heat capacity over the entire temperature range up to 800 K. The model agrees in magnitude with experimental low-temperature values and reproduces the linear slope observed in high-temperature data. Owing to the large scatter in experimental values of high-temperature heat capacity, the model is likely more accurate (within ±3%) than a measurement of a new sample even for doped or alloyed materials. It is found that heat capacity for the solid solution series can be simply described (for temperatures: 200K≤T≤800K ) by the polynomial equation: c p [Jg –1 K –1 ]=3NR/M W (1 + 1.3 × 10 –4 T – 4 × 10 3 T –2 ), where 3 NR = 124.71 J mol –1 K –1 , M W is the molecular weight [gmol –1 ] of the formula unit being considered, and T is temperature in K . This heat capacity is recommended to be a standard value for reporting and comparing the thermal conductivity of Mg 3 (Sb,Bi) 2 including doped or alloyed derivatives. Furthermore, a general form of the equation is given which can be used for other material systems

36 MATERIALS SCIENCE↗
DOE OSTI2017

Markov state models from short non-equilibrium simulations—Analysis and correction of estimation bias

To begin, many state-of-the-art methods for the thermodynamic and kinetic characterization of large and complex biomolecular systems by simulation rely on ensemble approaches, where data from large numbers of relatively short trajectories are integrated. In this context, Markov state models (MSMs) are extremely popular because they can be used to compute stationary quantities and long-time kinetics from ensembles of short simulations, provided that these short simulations are in “local equilibrium” within the MSM states. However, over the last 15 years since the inception of MSMs, it has been controversially discussed and not yet been answered how deviations from local equilibrium can be detected, whether these deviations induce a practical bias in MSM estimation, and how to correct for them. In this paper, we address these issues: We systematically analyze the estimation of MSMs from short non-equilibrium simulations, and we provide an expression for the error between unbiased transition probabilities and the expected estimate from many short simulations. We show that the unbiased MSM estimate can be obtained even from relatively short non-equilibrium simulations in the limit of long lag times and good discretization. Further, we exploit observable operator model (OOM) theory to derive an unbiased estimator for the MSM transition matrix that corrects for the effect of starting out of equilibrium, even when short lag times are used. Finally, we show how the OOM framework can be used to estimate the exact eigenvalues or relaxation time scales of the system without estimating an MSM transition matrix, which allows us to practically assess the discretization quality of the MSM. Applications to model systems and molecular dynamics simulation data of alanine dipeptide are included for illustration. The improved MSM estimator is implemented in PyEMMA of version 2.3.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Modeling dark- and light-induced crystal structures and single-crystal optical absorption spectra of ruthenium-based complexes that undergo SO 2 -linkage photoisomerization

A family of coordination complexes of the type [Ru(SO 2 )(NH 3 ) 4 X] m+ Y n – (m, n = 1 or 2) exhibit optical switching capabilities in their single-crystal states. This striking effect is caused by the light-induced formation of SO 2 -linkage photoisomers, which are metastable if kept at suitably cool temperatures. We modeled the dark- and light-induced states of these large crystalline complexes via plane-wave (PW)- and molecular-orbital (MO)-based density functional theory (DFT) and time-dependent DFT in order to calculate their structural and optical properties; the calculated results are compared with experimental data. We show that the PW-DFT-based periodic models replicate the structural properties of these complexes more effectively than the MO-DFT-based molecular-fragment models, observing only small deviations in key bond lengths relative to the experimentally derived crystal structures. The periodic models were also found to more effectively simulate trends seen in experimental optical absorption spectra, with optical absorbance and coverage of the visible region increasing with the formation of the photoinduced geometries. The contribution of the metastable photoisomeric species more heavily focuses on the lower-energy end of the spectra. Spectra generated from the molecular-fragment models are limited by the geometry of the fragment used and the number of excited-state roots considered in those calculations. In general, periodic models outperform the molecular-fragment models owing to their ability to better appreciate the periodic phenomena that are present in these crystalline materials as opposed to MO approaches, which are finite methods. We thus demonstrate that PW-DFT-based periodic models should be considered as a more than viable method for simulating the optical and electronic properties of these single-crystal optical switches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Bose-Einstein condensation phenomenology in systems with repulsive interactions

The role of repulsive interactions in statistical systems of Bose particles is investigated. Three different phenomenological frameworks are considered: A mean-field model, an excluded volume model, and a model with a medium-dependent effective mass. All three models are tuned to yield similar equations of state, with only minor deviations from the ideal Bose gas at small chemical potentials. Our analysis indicates, however, that these models lead to qualitatively different results for the Bose-Einstein condensation phenomenon. We discuss the different aspects of this phenomenon, namely, an onset of the Bose-Einstein condensation, particle number fluctuations, and a behavior of the Bose condensate. The obtained results can be helpful for interpreting the lattice QCD data at small temperature and large isospin chemical potential and the data on multiple pion production in high-energy nuclear collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Introducing a multiscale feature integration network for inpainting with applications to enhanced CMB map reconstruction

We introduce a novel neural network, SkyReconNet, which combines the expanded receptive fields of dilated convolutional layers along with standard convolutions, to capture both the global and local features for reconstructing the missing information in an image. We implement our network to inpaint the masked regions in a full-sky cosmic microwave background (CMB) map. Inpainting CMB maps is a particularly formidable challenge when dealing with extensive and irregular masks, such as galactic masks which can obscure substantial fractions of the sky. The hybrid design of SkyReconNet leverages the strengths of standard and dilated convolutions to accurately predict CMB fluctuations in the masked regions by effectively utilizing the information from surrounding unmasked areas. During training, the network optimizes its weights by minimizing a composite loss function that combines the structural similarity index measure (SSIM) and mean squared error (MSE). SSIM preserves the essential structural features of the CMB, ensuring an accurate and coherent reconstruction of the missing CMB fluctuations, while MSE minimizes the pixelwise deviations, thus enhancing the overall accuracy of the predictions. The predicted CMB maps and their corresponding angular power spectra align closely with the targets, achieving the performance limited only by the fundamental uncertainty of cosmic variance. The network’s generic architecture enables application to other physics-based challenges involving data with missing or defective pixels, systematic artifacts, etc. In conclusion, our results demonstrate its effectiveness in addressing the challenges posed by large irregular masks, offering a significant inpainting tool not only for CMB analyses but also for image-based experiments across disciplines where such data imperfections are prevalent.

Cosmic microwave background↗
DOE OSTI2015

SU-E-I-34: Evaluating Use of AEC to Lower Dose for Lung Cancer Screening CT Protocols

Purpose: The National Lung Screening Trial mandated manual low dose CT technique factors, where up to a doubling of radiation output could be used over a regular to large patient size range. Recent guidance from the AAPM and ACR for lung cancer CT screening recommends radiation output adjustment for patient size either through AEC or a manual technique chart. This study evaluated the use of AEC for output control and dose reduction. Methods: The study was performed on a multidetector helical CT scanner (Aquillion ONE, Toshiba Medical) equipped with iterative reconstruction (ADIR-3D), AEC was adjusted with a standard deviation (SD) image quality noise index. The protocol SD parameter was incrementally increased to reduce patient population dose while image quality was evaluated by radiologist readers scoring the clinical utility of images on a Likert scale. Results: Plots of effective dose vs. body size (water cylinder diameter reported by the scanner) demonstrate monotonic increase in patient dose with increasing patient size. At the initial SD setting of 19 the average CTDIvol for a standard size patient was ∼ 2.0 mGy (1.2 mSv effective dose). This was reduced to ∼1.0 mGy (0.5 mSv) at an SD of 25 with no noticeable reduction in clinical utility of images as demonstrated by Likert scoring. Plots of effective patient diameter and BMI vs body size indicate that these metrics could also be used for manual technique charts. Conclusion: AEC offered consistent and reliable control of radiation output in this study. Dose for a standard size patient was reduced to one-third of the 3 mGy CTDIvol limit required for ACR accreditation of lung cancer CT screening. Gary Arbique: Research Grant, Toshiba America Medical Systems; Cecelia Brewington: Research Grant, Toshiba America Medical Systems; Di Zhang: Employee, Toshiba America Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-577: Comparison of Small Field Dosimetry Measurements in Fields Shaped with Conical Applicators On Two Different Accelerating Systems

Purpose: To investigate small field dosimetry measurements and associated uncertainties when conical applicators are used to shape treatment fields from two different accelerating systems. Methods: Output factor measurements are made in water in beams from the CyberKnife radiosurgery system, which uses conical applicators to shape fields from a (flattening filter-free) 6 MV beam, and in a 6 MV beam from the Elekta Precise linear accelerator (with flattening filter) with BrainLab external conical applicators fitted to shape the field. The measurements use various detectors: (i) an Exradin A16 ion chamber, (ii) two Exradin W1 plastic scintillation detectors, (iii) a Sun Nuclear Edge diode, and (iv) two PTW microDiamond synthetic diamond detectors. Profiles are used for accurate detector positioning and to specify field size (FWHM). Output factor measurements are corrected with detector specific correction factors taken from the literature where available and/or from Monte Carlo simulations using the EGSnrc code system. Results: Differences in measurements of up to 1.7% are observed with a given detector type in the same beam (i.e., intra-detector variability). Corrected results from different detectors in the same beam (inter-detector differences) show deviations up to 3 %. Combining data for all detectors and comparing results from the two accelerators results in a 5.9% maximum difference for the smallest field sizes (FWHM=5.2–5.6 mm), well outside the combined uncertainties (∼1% for the smallest beams) and/or differences among detectors. This suggests that the FWHM of a measured profile is not a good specifier to compare results from different small fields with the same nominal energy. Conclusion: Large differences in results for both intra-detector variability and inter-detector differences suggest potentially high uncertainties in detector-specific correction factors. Differences between the results measured in circular fields from different accelerating systems provide insight into sources of variability in small field dosimetric measurements reported in the literature.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2018

Electrolyzer Exergy Analysis for an Environmental Control and Life Support System

An exergy based analysis of the Environmental Control and Life Support System (ECLSS) aboard the International Space Station (ISS) is conducted to assess its overall performance. Exergy is chosen as a measure of performance because it accounts for both the first and second laws of thermodynamics. The exergy efficiency of a system is first defined as the total exergy destroyed by the system relative to the total exergy input to the system. To determine the ECLSS exergy efficiency, the system is divided into constituent subsystems which in turn are divided into assemblies and components. Based on this system decomposition, exergy balances are derived for each assembly or component. Exergy balances and supporting calculations are implemented in MATLAB® code. The major subsystems of the ECLSS considered in this analysis include the Atmosphere Revitalization Subsystem (ARS), Atmosphere Control and Supply Subsystem (ACS), Temperature and Humidity Control Subsystem (THC), Water Recovery and Management Subsystem (WRM), and Waste Management Subsystem (WM). This paper focuses on the ARS and its constituent assemblies and components. Exergy efficiency of the ARS and its constituent assemblies and components is first presented. The Oxygen Generation Assembly (OGA), an assembly within the ARS, is then highlighted because the exergy destruction by the OGA is a large magnitude contributor to the overall exergy destruction of the ECLSS. The OGA produces oxygen to meet the crew's metabolic demand via water electrolysis in a proton exchange membrane (PEM) electrolyzer. The exergy destruction of the OGA's PEM electrolyzer is a function of the amount of oxygen produced, which determines the necessary current density and voltage drop across the PEM electrolyzer. In addition, oxygen production in the PEM electrolyzer requires deviation from the Nernst potential, presenting trade-offs between the exergy efficiency and critical life support functions. The results of parametric studies of PEM electrolyzer performance are presented with an emphasis on the impacts of polarization and operational conditions on exergy efficiency.

Chow, Raymond↗
DOE OSTI2020

Inexact convex relaxations for AC optimal power flow: Towards AC feasibility

Convex relaxations of AC optimal power flow (AC-OPF) problems have attracted significant interest as in several instances they provably yield the global optimum to the original non-convex problem. If, however, the relaxation is inexact, the obtained solution is not AC-feasible. The quality of the obtained solution is essential for several practical applications of AC-OPF, but detailed analyses are lacking in existing literature. Here, this paper aims to cover this gap. We provide an in-depth investigation of the solution characteristics when convex relaxations are inexact, we assess the most promising AC feasibility recovery methods for large-scale systems, and we propose two new metrics that lead to a better understanding of the quality of the identified solutions. We perform a comprehensive assessment on 96 different test cases, ranging from 14 to 3120 buses, and we show the following: (i) Despite an optimality gap of less than 1%, several test cases still exhibit substantial distances to both AC feasibility and local optimality and the newly proposed metrics characterize these deviations. (ii) Penalization methods fail to recover an AC-feasible solution in 15 out of 45 test cases. (iii) The computational benefits of warm-starting non-convex solvers have significant variation, but a computational speedup exists in over 75% of cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13 C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Competing Pathways for Nucleation of the Double Perovskite Structure in the Epitaxial Synthesis of La 2 MnNiO 6

Over the past decades a confluence of advanced synthesis techniques, data-driven characterization, and rapid increases in computing power has sparked a renaissance in materials engineering. The emerging “materials-by-design” approach, while radically transforming the development of multicomponent systems, has tended to overlook the complex kinetic pathways that define materials synthesis. Although we are able to envision almost limitless materials combinations, we are unable to synthesize all of them in practice, since existing characterization and modeling approaches often fail to capture the inherent complexity of such systems. There is currently a disconnect between highly local structural characterization and macroscale properties measurements, resulting in oversimplified or incomplete structure-property models. Here we describe a multi-technique approach that combines aberration-corrected transmission electron microscopy with emerging oxide atom probe tomography to measure chemical ordering and extended defects in the model complex oxide, La2MnNiO6. We visualize cation ordering, as well as a three-dimensional network of secondary phases, which we describe in terms of ab initio structure calculations. We propose a defect model in which these phases alter their surrounding octahedral environment, severely disrupting cation superexchange. Through this array of experimental and theoretical techniques, we uncover fundamental structure-property relationships and illustrate a new approach to engineer complex, multicomponent systems.

atom probe tomography↗
DOE OSTI2016

WE-FG-207B-08: Dual-Energy CT Iodine Accuracy Across Vendors and Platforms

Purpose: Although a major benefit of dual-energy CT is its quantitative capabilities, it is critical to understand how results vary by scanner manufacturer and/or model before making clinical patient management decisions. Each manufacturer utilizes a specific dual-energy CT approach; cross-calibration may be required for facilities with more than one dual-energy CT scanner type. Methods: A solid dual-energy quality control phantom (Gammex, Inc.; Appleton, WI) representing a large body cross-section containing three Iodine inserts (2mg/ml, 5mg/ml, 15 mg/ml) was scanned on these CT systems: GE HD-750 (80/140kVp), prototype GE Revolution CT with GSI (80/140kVp), Siemens Flash (80/140kVp and 100/140kVp), and Philips IQon (120kVp and 140kVp). Iodine content was measured in units of concentration (mg/ml) from a single 5mm-thick central image. Three to five acquisitions were performed on each scanner platform in order to compute standard deviation. Scan acquisitions were approximately dose-matched (∼25mGy CTDIvol) and image parameters were as consistent as possible (thickness, kernel, no noise reduction applied). Results: Iodine measurement error ranges were −0.24-0.16 mg/ml for the 2mg/ml insert (−12.0 − 8.0%), −0.28–0.26 mg/ml for the 5mg/ml insert (−5.6 − 5.2%), and −1.16−0.99 mg/ml for the 15mg/ml insert (−7.7 − 6.6%). Standard deviations ranged from 0 to 0.19 mg/ml for the repeated acquisitions from each scanner. The average iodine measurement error and standard deviation across all systems and inserts was −0.21 ± 0.48 mg/ml (−1.5 ± 6.48%). The largest absolute measurement error was found in the 15mg/ml iodine insert. Conclusion: There was generally good agreement in Iodine quantification across 3 dual-energy CT manufacturers and 4 scanner models. This was unexpected given the widely different underlying dual-energy CT mechanisms employed. Future work will include additional scanner platforms, independent verification of the Iodine insert standard concentrations (especially the 15 mg/ml insert), and how much measurement variability can be clinically tolerated. This research has been supported by funds from Dr. William Murphy, Jr., the John S. Dunn, Sr. Distinguished Chair in Diagnostic Imaging at MD Anderson Cancer Center.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

maranasgroup/yeastsMFA

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Dinh, Hoang↗
DOE OSTI2023

maranasgroup/k-sacce306

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Dinh, Hoang↗
DOE OSTI2023

Increased power gains from wake steering control using preview wind direction information

Abstract. Yaw controllers typically rely on measurements taken at the wind turbine, resulting in a slow reaction to wind direction changes and subsequent power losses due to misalignments. Delayed yaw action is especially problematic in wake steering operation because it can result in power losses when the yaw misalignment angle deviates from the intended one due to a changing wind direction. This study explores the use of preview wind direction information for wake steering control in a two-turbine setup with a wind speed in the partial load range. For these conditions and a simple yaw controller, results from an engineering model identify an optimum preview time of 90 s. These results are validated by forcing wind direction changes in a large-eddy simulation model. For a set of six simulations with large wind direction changes, the average power gain from wake steering increases from only 0.44 % to 1.32 %. For a second set of six simulations with smaller wind direction changes, the average power gain from wake steering increases from 1.24 % to 1.85 %. Low-frequency fluctuations are shown to have a larger impact on the performance of wake steering and the effectiveness of preview control, in particular, than high-frequency fluctuations. From these results, it is concluded that the benefit of preview wind direction control for wake steering is substantial, making it a topic worth pursuing in future work.

17 WIND ENERGY↗
NASA NTRS1978

Characterization of the non axial thrust generated by large solid propellant rocket motors in three axis stabilized ascent

Nonaxial thrusts produced by solid rocket motors during three-axis stabilized attitude control have been determined from ascent experience on twenty three Burner II, Burner IIA and Block 5D-1 upper stage vehicles. A data base representing four different rocket motor designs (three spherical and one extended spherical) totaling twenty five three-axis stabilized firings is generated. Solid rocket motor time-varying resultant and lateral side force vector magnitudes, directions and total impulses, and roll torque couple magnitudes, directions, and total impulses are tabulated in the appendix. Population means and three sigma deviations are plotted. Existing applicable ground test side force and roll torque magnitudes and total impulses are evaluated and compared to the above experience data base. Within the spherical motor population, the selected AEDC ground test data consistently underestimated experienced motor side forces, roll torques and total impulses. Within the extended spherical motor population, the selected AEDC test data predicted experienced motor side forces, roll torques, and total impulses, with surprising accuracy considering the very small size of the test and experience populations.

Kosmann, W. J.↗