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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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DOE OSTI2016

Simulation of Rutherford backscattering spectrometry from arbitrary atom structures

Rutherford backscattering spectrometry in a channeling direction (RBS/C) is a powerful tool for analysis of the fraction of atoms displaced from their lattice positions. However, it is in many cases not straightforward to analyze what is the actual defect structure underlying the RBS/C signal. To reveal insights of RBS/C signals from arbitrarily complex defective atomic structures, we develop in this paper a method for simulating the RBS/C spectrum from a set of arbitrary read-in atom coordinates (obtained, e.g., from molecular dynamics simulations). We apply the developed method to simulate the RBS/C signals from Ni crystal structures containing randomly displaced atoms, Frenkel point defects, and extended defects, respectively. The RBS/C simulations show that, even for the same number of atoms in defects, the RBS/C signal is much stronger for the extended defects. Finally, comparison with experimental results shows that the disorder profile obtained from RBS/C signals in ion-irradiated Ni is due to a small fraction of extended defects rather than a large number of individual random atoms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

CHARACTERISTICS OF CYCLE-TO-CYCLE COMBUSTION VARIABILITY AT PARTIAL-BURN LIMITED AND MISFIRE LIMITED SPARK TIMING UNDER HIGHLY DILUTED CONDITIONS

Diluted combustion with exhaust gas recirculation (EGR) has been widely employed to improve the fuel economy of spark ignition engines. The combustion kinetics, however, are affected and the flame propagation speed is decreased. In order to compensate for this adverse effect, the spark timing needs to be recalibrated to achieve maximum brake torque (MBT). At high levels of EGR dilution, the spark timing is constrained by two ignition limits: 1) the partial-bum limit where the spark timing is retarded from MBT and 2) the misfire limit where the spark timing is too advanced. This work uses a probabilistic framework to capture the differences between both ignition limits. In particular, it introduces the concept of a nominal indicated mean effective pressure (IMEP) distribution based on the stochastic properties of the cycle-to-cycle variability (CCV) at nominal stable conditions. By defining a nominal band where fully burned cycles occur with high probability, we introduce a cycle classification method that can be used to 1) determine the level of randomness of misfire and partial-burn events, and 2) measure CCV. The new CCV metric based on the density of the nominal band is compared with the traditional coefficient of variation of IMEP (CoVIMEP). It is shown that the nominal band concept, together with the CoVIMEP, can help to discern between partial-burn limited and misfire limited conditions. Furthermore, the Kullback-Leibler divergence is used to demonstrate that the IMEP distribution is significantly different between nominal and partial-burn/misfire limited conditions. Experiments are carried at various EGR levels and spark timings while recoding in-cylinder pressure at steady state. Although the emphasis of this work is to characterize the differences of both ignition limits from a probabilistic point of view, similarities between partial-burn cycles at either limiting conditions are also discussed.

Maldonado, Bryan↗
DOE OSTI2016

SU-F-I-03: Correction of Intra-Fractional Set-Up Errors and Target Coverage Based On Cone-Beam Computed Tomography for Cervical Cancer Patients

Purpose: The purpose of this study is to investigate the patient set-up error and interfraction target coverage in cervical cancer using image-guided adaptive radiotherapy (IGART) with cone-beam computed tomography (CBCT). Methods: Twenty cervical cancer patients undergoing intensity modulated radiotherapy (IMRT) were randomly selected. All patients were matched to the isocenter using laser with the skin markers. Three dimensional CBCT projections were acquired by the Varian Truebeam treatment system. Set-up errors were evaluated by radiation oncologists, after CBCT correction. The clinical target volume (CTV) was delineated on each CBCT, and the planning target volume (PTV) coverage of each CBCT-CTVs was analyzed. Results: A total of 152 CBCT scans were acquired from twenty cervical cancer patients, the mean set-up errors in the longitudinal, vertical, and lateral direction were 3.57, 2.74 and 2.5mm respectively, without CBCT corrections. After corrections, these were decreased to 1.83, 1.44 and 0.97mm. For the target coverage, CBCT-CTV coverage without CBCT correction was 94% (143/152), and 98% (149/152) with correction. Conclusion: Use of CBCT verfication to measure patient setup errors could be applied to improve the treatment accuracy. In addition, the set-up error corrections significantly improve the CTV coverage for cervical cancer patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-421: Dosimetry Change During Radiotherapy and Dosimetry Difference for Rigid and Deformed Registration in the Mid-Thoracic Esophageal Carcinoma

Purpose: This study aimed to analyze dosimetry changes during radiotherapy for the mid-thoracic esophageal carcinoma, and investigate dosimetry difference between rigid and deformed registration. Methods: Twelve patients with primary middle thoracic esophageal carcinoma were selected randomly. Based on first CT scanning of each patient, plans-o were generated by experience physicists. After 20 fractions treatment, the corresponding plans-re were created with second CT scanning. And then, these two CT images were rigid and deformed registration respectively, and the dose was accumulated plan-o with plan-re. The dosimetry variation of these plans (plan-o: with 30 fractions, plan-rig: the accumulated dose with rigid registration and plan-def: the accumulated dose with deformed registration) were evaluated by paired T-test. Results: The V20 value of total lung were 32.68%, 30.3% and 29.71% for plan-o, plan-rig and plan-def respectively. The mean dose of total lung was 17.19 Gy, 16.67 Gy and 16.51 Gy for plan-o plan-rig and plan-def respectively. There were significant differences between plan-o and plan-rig or plan-def for both V20 and mean dose of total lung (with p= 0.003, p= 0.000 for V20 and p=0.008, p= 0.000 for mean dose respectively). There was no significant difference between plan-rig and plan-def (with p=0.118 for V20 and p=0.384 for mean dose). The max dose of spinal-cord was 41.95 Gy, 41.48 Gy and 41.4 Gy for plan-o, plan-rig and plan-def respectively. There were no significant differences for the max dose of spinal-cord between these plans. Conclusion: The target volume changes and anatomic position displacement of mid-thoracic esophageal carcinoma should not be neglected in clinics. These changes would cause overdose in normal tissue. Therefore, it is necessary to have another CT scanning and re-plan during the mid-thoracic esophageal carcinoma radiotherapy. And the dosimetry difference between rigid and deformed fusions was not found in this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-AB-BRA-03: Atlas-Based Algorithms with Local Registration-Goodness Weighting for MRI-Driven Electron Density Mapping

Purpose: To develop image-analysis algorithms to synthesize CT with accurate electron densities for MR-only radiotherapy of head & neck (H&N) and pelvis anatomies. Methods: CT and 3T-MRI (Philips, mDixon sequence) scans were randomly selected from a pool of H&N (n=11) and pelvis (n=12) anatomies to form an atlas. All MRIs were pre-processed to eliminate scanner and patient-induced intensity inhomogeneities and standardize their intensity histograms. CT and MRI for each patient were then co-registered to construct CT-MRI atlases. For more accurate CT-MR fusion, bone intensities in CT were suppressed to improve the similarity between CT and MRI. For a new patient, all CT-MRI atlases are deformed onto the new patients’ MRI initially. A newly-developed generalized registration error (GRE) metric was then calculated as a measure of local registration accuracy. The synthetic CT value at each point is a 1/GRE-weighted average of CTs from all CT-MR atlases. For evaluation, the mean absolute error (MAE) between the original and synthetic CT (generated in a leave-one-out scheme) was computed. The planning dose from the original and synthetic CT was also compared. Results: For H&N patients, MAE was 67±9, 114±22, and 116±9 HU over the entire-CT, air and bone regions, respectively. For pelvis anatomy, MAE was 47±5 and 146±14 for the entire and bone regions. In comparison with MIRADA medical, an FDA-approved registration tool, we found that our proposed registration strategy reduces MAE by ∼30% and ∼50% over the entire and bone regions, respectively. GRE-weighted strategy further lowers MAE by ∼15% to ∼40%. Our primary dose calculation also showed highly consistent results between the original and synthetic CT. Conclusion: We’ve developed a novel image-analysis technique to synthesize CT for H&N and pelvis anatomies. Our proposed image fusion strategy and GRE metric help generate more accurate synthetic CT using locally more similar atlases (Support: Philips Healthcare). The research is supported by Philips HealthCare.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Sliced-Inverse-Regression--Aided Rotated Compressive Sensing Method for Uncertainty Quantification

Compressive-sensing-based uncertainty quantification methods have become a pow- erful tool for problems with limited data. In this paper, we use the sliced inverse regression (SIR) method to provide an initial guess for the alternating direction method, which is used to enhance sparsity of the Hermite polynomial expansion of stochastic state variables. The sparsity improvement increases both the efficiency and accuracy of the compressive-sensing-based uncertainty quantification method. We demonstrate that the initial guess from SIR is more suitable for the cases when the available data is very limited (Algorithm 4). We also propose another algorithm (Algorithm 5) that performs dimension reduction first with sliced inverse regression, then constructs a Hermite polynomial expansion of the reduced model. This method allows us to approximate the statistics accurately with even less available data. Both methods are non-intrusive and require no a priori information of the sparsity of the system. We demonstrate the effectiveness of these two methods (Algorithms 4 and 5) using problems with up to 500 random dimensions.

Yang, Xiu↗
DOE OSTI2022

A Systematic Review and Meta-Analysis of Tai Chi Training in Cardiorespiratory Fitness of Elderly People

Objectives. The purpose of this study was to investigate the influence of Tai Chi on cardiorespiratory fitness (CRF) in elderly people using meta-analysis. Methods. This study used seven electronic databases and data retrieved from randomized controlled trials (RCTs) investigating the role of Tai Chi on CRF in the elderly. All these 24 RCTs were screened and selected from 7 literature databases. The Stata 11.2 software (StataCorp, USA) was used for the meta-analysis, subgroup analysis, and bias test, while the Cochrane Collaboration’s tool was used for the assessment of the risk of bias (RoB). 4 researchers independently participated in sample selection, data extraction, and RoB assessment. Results. Following the inclusion criteria, 24 eligible studies were included in our analysis. The meta-analysis indicated that Tai Chi practice significantly increased the maximum rate of oxygen consumption (VO2 max) (weighted mean difference (WMD) = 3.76, 95% CI: 1.25 to 6.26, P < 0.1 ), leading to an overall reduction in the heart rate (HR) (WMD = −1.84, 95% CI: −2.04 to −1.63, P ≤ 0.001 ) and an increase in the O2 pulse (WMD = 0.94, 95% CI: 0.60 to 1.28, P ≤ 0.001 ) in individuals who practiced Tai Chi regularly compared with those who did not. The subgroup analysis suggested that overall in those who practiced Tai Chi, males (WMD = 1.48, 95% CI: 0.85 to 2.12, P ≤ 0.001 ) had higher O2 pulse than females (WMD = 0.73, 95% CI: 0.33 to 1.12, P ≤ 0.001 ). The subgroup analysis also showed an increase in the vital capacity (VC) (WMD = 316.05, 95% CI: 239.74 to 392.35, P ≤ 0.001 ) in individuals practicing Tai Chi. When the samples were further stratified by Tai Chi practicing time, the subgroup analysis suggested that individuals practicing Tai Chi over a period of 24 weeks showed no significant difference in VC (WMD = 82.95, 95% CI: -98.34 to 264.23, P = 0.370 ), while those practicing Tai Chi over a period of 48 weeks showed a significant increase (WMD = 416.62, 95% CI: 280.68 to 552.56, P ≤ 0.001 ). Furthermore, the subgroup analysis demonstrated that the increase in VC is significantly correlated with the Tai Chi practicing time (WMD = 344.97, 95% CI: 227.88 to 442.06, P ≤ 0.001 ). Conclusion. Regular Tai Chi practice could improve the CRF in the elderly, as indicated by significant improvement in indicators including VO2max, O2pulse, VC, and HR. However, gender and practice time might influence the overall beneficial outcomes.

Tan, Tianyang↗
DOE OSTI2025

hiposa v0.1.0

Fast construction of hierarchical N-dimensional experimental design. The software allows construction of sampling strategies that are self-avoiding, tunable in resolution in N dimensions. This code is a drop-in replacement for seeding optimization runs often performed using uniform random sampling. The hierarchical approach allows for a rapid, top down method for construction the most effective design that drives towards a global optimum.

Zwart, PetrusH [Lawrence Berkeley National Laborat↗
DOE OSTI2020

Fast Computational Algorithms for Partial Differential Equations and Uncertainty Quantifications

This project concerned the construction, testing and analysis of computational algorithms for solving parameterized and stochastic partial differential equations. The study and understanding of equations of this type is of fundamental importance in numerous engineering and scientific applications. Examples include simulation of plasma dynamics in models of electric propulsion and nuclear fusion, simulation of multiphase flows, such as the flow of water, gas and oil in reservoirs, and structural analysis of the dependence of structures on materials. Parametrization is used in such settings when properties of the models such as viscosity of fluids or electric resistivity of materials are not precisely understood and instead are treated as random variables. The resulting solutions are themselves random, and having such solutions will enable engineers to use probabilistic methods to assess the likelihood of events, for example, whether a pollutant in a liquid will exceed a limit, and to use such analyses to develop ways to ensure positive outcomes. Construction of accurate (high resolution) computational solutions is expensive, requiring significant computer time and computational resources, and there is need to reduce computational cost to make simulation useful and effective. The aim of the project was to construct algorithms to efficiently compute surrogate solutions to parameterized problems to allow for efficient and accurate simulation. The technical approach used focused on two related strategies, based on rank-reduction methods and reduced-order models. These methods construct surrogate solutions of parameter-dependent models by projection or interpolation into low-dimensional approximation spaces. Cost savings are achieved if the low-dimensional spaces can be identified and constructed efficiently and if the resulting low-dimensional algebraic systems can be solved cheaply. Accomplishments include: Theoretical and empirical demonstration of the effectiveness of fast multigrid solution strategies for computing low-rank representations of parameter-dependent solutions to discrete partial differential equations, including the first proof establishing so-called textbook convergence properties for low-rank methods. Development of efficient solution algorithms for solving nonlinear parameter-dependent partial differential equations used in models of fluid dynamics. Developent of efficient algorithms for low-rank representation of solutions of time-dependent simulations of fluid dynamics using multi-dimensional tensor representations of solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Energy Delivery Systems with Verifiable Trustworthiness (Final Report)

Energy Delivery Systems (EDS) must be verified to be free from intrusive and malicious software. One way of verifying this software is to perform device scans to detect malicious code. Because it is possible to have “fileless” malware that exists only in device (volatile) memory, offline scanning and even many forms of online scanning is insufficient for detection. This project (“Verify”) addresses this need by performing direct sampling of memory during device operation to detect unexpected or modified software while not interfering with device operation. The Verify project provides a proof-of-concept of detection by random sampling combined with remote software- and timing-based attestation methods for robust detection of in-memory threats. An external review of Verify was performed by our partner, General Electric (GE), and a summary of their findings is provided.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Analyzing the Validity of Brazilian Testing Using Digital Image Correlation and Numerical Simulation Techniques

Characterizing the mechanical behavior of rocks plays a crucial role to optimize the fracturing process in unconventional reservoirs. However, due to the intrinsic anisotropy and heterogeneity in unconventional resources, fracture process prediction remains the most significant challenge for sustainable and economic hydrocarbon production. During the deformation tracking under compression, deploying conventional methods (strain gauge, extensometer, etc.) is insufficient to measure the deformation since the physical attachment of the device is restricted to the size of the sample, monitoring limited point-wise deformation, producing difficulties in data retrieval, and a tendency to lose track in failure points, etc. Where conventional methods are limited, the application of digital image correlation (DIC) provides detailed and additional information of strain evolution and fracture patterns under loading. DIC is an image-based optical method that records an object with a camera and monitors the random contrast speckle pattern painted on the facing surface of the specimen. To overcome the existing limitations, this paper presents numerical modeling of Brazilian disc tests under quasi-static conditions to understand the full-field deformation behaviors and finally, it is validated by DIC. As the direct tensile test has limitations in sample preparation and test execution, the Brazilian testing principle is commonly used to evaluate indirectly the tensile strength of rocks. The two-dimensional numerical model was built to predict the stress distribution and full-field deformation on Brazilian disc under compression based on the assumptions of a homogenous, isotropic and linear elastic material. The uniaxial compression test was conducted using the DIC technique to determine the elastic properties of Spider Berea sandstone, which were used as inputs for the simulation model. The model was verified by the analytical solution and compared with the digital image correlation. The numerical simulation results showed that the solutions matched reasonably with the analytical solutions where the maximum deviation of stress distribution was obtained as 14.59%. The strain evolution (normal and shear strains) and displacements along the central horizontal and vertical planes were investigated in three distinguishable percentages of peak loads (20%, 40%, and 90%) to understand the deformation behaviors in rock. The simulation results demonstrated that the strain evolution contours consistently matched with DIC generated contours with a reasonable agreement. The changes in displacement along the central horizontal and vertical planes showed that numerical simulation and DIC generated experimental results were repeatable and matched closely. In terms of validation, Brazilian testing to measure the indirect tensile strength of rocks is still an issue of debate. The numerical model of fracture propagation supported by digital image correlation from this study can be used to explain the fracturing process in the homogeneous material and can be extended to non-homogeneous cases by incorporating heterogeneity, which is essential for rock mechanics field applications.

58 GEOSCIENCES↗
DOE OSTI2017

Use of Uncertainty in Modeling DFLAW Treatment at Hanford - 17115

Average or mean is understood by most; standard deviation (SD) is understood by few. Certainty is easy to model; uncertainty is not. The flowsheet simulation, described in this paper, placed uncertainties in the G2 model of the Hanford Tank Waste Treatment and Immobilization Plant's (WTP) Direct Feed Low-Activity Waste (DFLAW) process for performance and sensitivity evaluations. G2 is a dynamic material balance model that starts and proceeds with operating logic until all the feed is processed. Dynamic material balance is achieved by tracking the flows, storage, and change of all materials within the plant as time increments. Processing equipment and limitations of the flowsheet are modeled (e.g., equipment types, piping, volumes, flowrates, efficiencies, and physical and chemical environments that impact separations, phase equilibriums, and chemical reactions). Operating logic represents the rules and strategies of a running plant. The G2 model simulated both certainty and uncertainty scenarios for comparison purposes. For the uncertainty scenarios, process decisions were made using presumed values to simulate various operational measurement errors and process variabilities. Presumed means that the known G2 values are adjusted to replicate measurement errors and variabilities. These include: 1) volume measurement, 2) sample analysis, 3) melter decontamination factor (DF), 4) glass former weighing, and 5) glass former composition variations. The errors were randomly generated in accordance with SD values of measurement devices, laboratory methods, and glass former composition ranges. The G2 model runs give insight on the DFLAW process' controllability and the expected range of glass properties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Hypergraph Random Walks, Laplacians, and Clustering

We propose a flexible framework for clustering hypergraph-structured data based on recently proposed random walks utilizing edge-dependent vertex weights. When incorporating edge-dependent vertex weights (EDVW), a weight is associated with each vertex-hyperedge pair, yielding a weighted incidence matrix of the hypergraph. Such weightings have been utilized in term-document representations of text data sets. We explain how random walks with EDVW serve to construct different hypergraph Laplacian matrices, and then develop a suite of clustering methods that use these incidence matrices and Laplacians for hypergraph clustering. Using 20Newsgroup, U.S. patent, Reuters' Corpus Volume 1, and genetics data sets, we compare the performance of these clustering algorithms experimentally against a variety of existing hypergraph clustering methods. We show that the proposed methods produce higher-quality clusters.

hypergraphs, clustering, laplacian, random walk, M↗
DOE OSTI2016

Autoionization resonances in the photoabsorption spectra of Fe{sup n+} iron ions

The photoabsorption cross sections of a neutral iron atom, as well as positive Fe{sup +} and Fe{sup 2+} ions, are calculated in the relativistic random-phase approximation with exchange in the energy range 20–160 eV. The wavefunctions of the ground and excited states are calculated in the single-configuration Hartree–Fock–Dirac approximation. The resultant photoabsorption spectra are compared with experimental data and with the results of calculations based on the nonrelativistic spin-polarized version of the random-phase approximation with exchange. Series of autoionization resonance peaks, as well as giant autoionization resonance lines corresponding to discrete transitions 3p → 3d, are clearly observed in the photoabsorption cross sections. The conformity of the positions of calculated peaks of giant autoionization resonances with experimental data is substantially improved by taking into account additionally the correlation electron–electron interaction based on the model of the dynamic polarization potential.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Identification and Preservation of Arm Lymphatic System in Axillary Dissection for Breast Cancer to Reduce Arm Lymphedema Events: A Randomized Clinical Trial

Background: Controversy in axillary reverse mapping in axillary lymph node dissection (ALND) possibly results from incomplete recognition of the arm lymphatic system (ALS) and its compromise to oncological safety. The iDEntification and Preservation of ARm lymphaTic system (DEPART) technique facilitates complete identification of ALS; therefore, its use may decrease the occurrence of arm lymphedema. This study aimed to examine the arm lymphedema rate, locoregional recurrence, and feasibility to perform DEPART in ALND. Methods: Patients from February 2013 to October 2017 from two tertiary referral centers were randomly assigned to two groups. In the study group, indocyanine green and methylene blue (MB) were utilized to identify arm sentinel nodes, and 0.1 ml MB was injected into the arm sentinel nodes to reveal the subsequent-echelon nodes and lymphatics. Gross arm lymph nodes were examined by intraoperative partial frozen section and were removed if positive. Arm lymphedema, local recurrence, regional recurrence, and distant metastasis were recorded at different follow-up examinations. Results: Arm sentinel nodes were identified in 573 (83.2%) patients. Subsequent-echelon nodes and lymphatics were visualized in 558 (97.4%) patients. Metastatic arm nodes were identified in 38 (6.8%) patients. The arm lymphedema rate was 3.3% (18/543) in the study group versus 15.3% (99/648) in the control group (p < 0.001) after 37-month median follow-up. Regional recurrence showed no difference between the two groups (1.4% and 1.2%, respectively) (p = 0.392). Conclusions: DEPART can benefit breast cancer patients who undergo ALND, reducing the arm lymphedema rate without adversely affecting the morbidity of regional recurrence.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Prediction of atomization energy using graph kernel and active learning

Data-driven prediction of molecular properties presents unique challenges to the design of machine learning methods concerning data structure/dimensionality, symmetry adaption, and confidence management. In this paper, we present a kernel-based pipeline that can learn and predict the atomization energy of molecules with high accuracy. The framework employs Gaussian process regression to perform predictions based on the similarity between molecules, which is computed using the marginalized graph kernel. To apply the marginalized graph kernel, a spatial adjacency rule is first employed to convert molecules into graphs whose vertices and edges are labeled by elements and interatomic distances, respectively. We then derive formulas for the efficient evaluation of the kernel. Specific functional components for the marginalized graph kernel are proposed, while the effects of the associated hyperparameters on accuracy and predictive confidence are examined. We show that the graph kernel is particularly suitable for predicting extensive properties because its convolutional structure coincides with that of the covariance formula between sums of random variables. Using an active learning procedure, we demonstrate that the proposed method can achieve a mean absolute error of 0.62 ± 0.01 kcal/mol using as few as 2000 training samples on the QM7 dataset.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)

Land surface models (LSMs), which form the land component of earth system models, rely on numerous processes for describing carbon, water and energy budgets, often associated with highly uncertain parameters. Data assimilation (DA) is a useful approach for optimising the most critical parameters in order to improve model accuracy and refine future climate predictions. In this study, we compare two different DA methods for optimising the parameters of seven plant functional types (PFTs) of the ORCHIDEE LSM using daily averaged eddy-covariance observations of net ecosystem exchange and latent heat flux at 78 sites across the globe. We perform a technical investigation of two classes of minimisation methods – local gradient-based (the L-BFGS-B algorithm, limited memory Broyden–Fletcher–Goldfarb–Shanno algorithm with bound constraints) and global random search (the genetic algorithm) – by evaluating their relative performance in terms of the model–data fit and the difference in retrieved parameter values. We examine the performance of each method for two cases: when optimising parameters at each site independently (“single-site” approach) and when simultaneously optimising the model at all sites for a given PFT using a common set of parameters (“multi-site” approach). We find that for the single site case the random search algorithm results in lower values of the cost function (i.e. lower model–data root mean square differences) than the gradient-based method; the difference between the two methods is smaller for the multi-site optimisation due to a smoothing of the cost function shape with a greater number of observations. The spread of the cost function, when performing the same tests with 16 random first-guess parameters, is much larger with the gradient-based method, due to the higher likelihood of being trapped in local minima. When using pseudo-observation tests, the genetic algorithm results in a closer approximation of the true posterior parameter value in the L-BFGS-B algorithm. We demonstrate the advantages and challenges of different DA techniques and provide some advice on using it for the LSM parameter optimisation.

58 GEOSCIENCES↗
DOE OSTI2017

Formation and structural phase transition in Co atomic chains on a Cu(775) surface

The formation of Co atomic chains on a Cu(775) surface is investigated by the kinetic Monte Carlo method. It is found that the length of Co atomic chains formed as a result of self-organization during epitaxial growth is a random quantity and its mean value depends on the parameters of the experiment. The existence of two structural phases in atomic chains is detected using the density functional theory. In the first phase, the separations between an atom and its two nearest neighbors in a chain are 0.230 and 0.280 nm. In the second phase, an atomic chain has identical atomic spacings of 0.255 nm. It is shown that the temperature of the structural phase transition depends on the length of the atomic chain.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗