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Parallel Variable Population Multi-Objective Optimizer (pvpmoo) v1.0

This is a parallel variable population multi-objective optimizer with an adaptive unified differential evolution algorithm or a genetic algorithm. It can also be used for single objective optimization. Some features of this code include: 1) The population size varies from generation to generation to save the total # of objective function evaluations. 2) The population is uniformly distributed to a number of parallel processors for simultaneous objective function evaluation. 3) The objective function evaluation can be attained from an external simulation program with control variables in its input file and objectives calculated from its output files. 4) The optimizer includes an adaptive unified differential evolution algorithm and a real value genetic algorithm. The parameters in the unified differential evolution algorithm can be chosen to attain any mutation schemes in the published literature.

Qiang, Ji↗

Bayesian Inversion of Seismic and Electromagnetic Data for Marine Gas Reservoir Characterization Using Multi-chain Markov Chain Monte Carlo Sampling

In this study we developed an efficient Bayesian inversion framework for interpreting marine seismic amplitude versus angle (AVA) and controlled source electromagnetic (CSEM) data for marine reservoir characterization. The framework uses a multi-chain Markov-chain Monte Carlo (MCMC) sampler, which is a hybrid of DiffeRential Evolution Adaptive Metropolis (DREAM) and Adaptive Metropolis (AM) samplers. The inversion framework is tested by estimating reservoir-fluid saturations and porosity based on marine seismic and CSEM data. The multi-chain MCMC is scalable in terms of the number of chains, and is useful for computationally demanding Bayesian model calibration in scientific and engineering problems. As a demonstration, the approach is used to efficiently and accurately estimate the porosity and saturations in a representative layered synthetic reservoir. The results indicate that the seismic AVA and CSEM joint inversion provides better estimation of reservoir saturations than the seismic AVA-only inversion, especially for the parameters in deep layers. The performance of the inversion approach for various levels of noise in observational data was evaluated – reasonable estimates can be obtained with noise levels up to 25%. Sampling efficiency due to the use of multiple chains was also checked and was found to have almost linear scalability.

Ren, Huiying↗

A parallel variable population multi-objective optimizer for accelerator beam dynamics optimization

The simultaneous optimization of multiple objective functions is needed in many particle accelerator applications. In this paper, we present a parallel evolution based multi-objective optimizer that uses a variable population from generation to generation and an external storage to save good solutions. Two heuristic optimization methods, one uses the unified differential evolution and the other uses the real-coded genetic algorithm, are included in the optimizer to generate next generation candidate solutions, and are compared in the test examples. Finally, as an application, we applied this optimizer to the beam dynamics design optimization of a photoinjector and attained the optimal front solutions after 200 generations with the unified differential evolution offspring production scheme.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A genome-wide analysis of the flax (Linum usitatissimum L.) dirigent protein family: from gene identification and evolution to differential regulation

Identification of DIR encoding genes in flax genome. Analysis of phylogeny, gene/protein structures and evolution. Identification of new conserved motifs linked to biochemical functions. Investigation of spatio-temporal gene expression and response to stress. Dirigent proteins (DIRs) were discovered during 8-8' lignan biosynthesis studies, through identification of stereoselective coupling to afford either (+)- or (-)-pinoresinols from E-coniferyl alcohol. DIRs are also involved or potentially involved in terpenoid, allyl/propenyl phenol lignan, pterocarpan and lignin biosynthesis. DIRs have very large multigene families in different vascular plants including flax, with most still of unknown function. DIR studies typically focus on a small subset of genes and identification of biochemical/physiological functions. Herein, a genome-wide analysis and characterization of the predicted flax DIR 44-membered multigene family was performed, this species being a rich natural grain source of 8-8' linked secoisolariciresinol-derived lignan oligomers. All predicted DIR sequences, including their promoters, were analyzed together with their public gene expression datasets. Expression patterns of selected DIRs were examined using qPCR, as well as through clustering analysis of DIR gene expression. These analyses further implicated roles for specific DIRs in (-)-pinoresinol formation in seed-coats, as well as (+)-pinoresinol in vegetative organs and/or specific responses to stress. Phylogeny and gene expression analysis segregated flax DIRs into six distinct clusters with new cluster-specific motifs identified. We propose that these findings can serve as a foundation to further systematically determine functions of DIRs, i.e. other than those already known in lignan biosynthesis in flax and other species. Given the differential expression profiles and inducibility of the flax DIR family, we provisionally propose that some DIR genes of unknown function could be involved in different aspects of secondary cell wall biosynthesis and plant defense.

dirigent protein↗

A hybrid optimization algorithm to explore atomic configurations of TiO 2 nanoparticles

Here in this paper we present a hybrid algorithm comprised of differential evolution, coupled with the Broyden–Fletcher–Goldfarb–Shanno quasi-Newton optimization algorithm, for the purpose of identifying a broad range of (meta)stable Ti n O 2 n nanoparticles, as an example system, described by Buckingham interatomic potential. The potential and its gradient are modified to be piece-wise continuous to enable use of these continuous-domain, unconstrained algorithms, thereby improving compatibility. To measure computational effectiveness a regression on known structures is used. This approach defines effectiveness as the ability of an algorithm to produce a set of structures whose energy distribution follows the regression as the number of Ti n O 2n increases such that the shape of the distribution is consistent with the algorithm’s stated goals. Our calculation demonstrates that the hybrid algorithm finds global minimum configurations more effectively than the differential evolution algorithms, widely employed in the field of materials science. Specifically, the hybrid algorithm is shown to reproduce the global minimum energy structures reported in the literature up to n = 5, and retains good agreement with the regression up to n = 25. For 25 < n < 100, where literature structures are unavailable, the hybrid effectively obtains structures that are in lower energies per TiO 2 unit as the system size increases.

36 MATERIALS SCIENCE↗

Application of Polynomial Chaos Expansion in One-Dimensional Inverse Transport Problems

In the problem of inverse radiation transport, measurements of particle leakages from radioactive source/shield systems are used to infer unknown parameters within the systems. This reconstruction can be accomplished by finding the physical parameters of the unknown system that minimize the difference between calculated detector responses and measured detector responses. The inverse transport solver should also propagate uncertainties from the detector responses to the reconstructed parameter values. Recently, the Differential Evolution Adaptive Metropolis (DREAM) method was shown to be a robust method for uncertainty quantification in inverse problems. The DREAM method uses the differential evolution algorithm to choose efficient steps in a Markov chain Monte Carlo (MCMC) simulation. Although the DREAM method has been shown to be more efficient than traditional MCMC approaches, it still requires thousands of transport computations to accurately quantify uncertainty. For the simple ray-tracing model, it was possible to perform these calculations in a reasonable amount of time (under an hour). However, inverse transport problems that require computationally-intensive transport solvers will need prohibitively long run times when using the DREAM method. A way to overcome the computational burden of the DREAM method is to perform surrogate modeling using the polynomial chaos expansion (PCE) approach. It was recently shown that the PCE method provides both accurate and computationally inexpensive uncertainty quantification in forward radiation source/shield problems. PCE was also recently applied to an inverse problem in nonlinear point reactor kinetics within a standard MCMC approach. PCE was first used with the DREAM method where it was applied to inverse problems in groundwater modeling.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Genome and evolution of the arbuscular mycorrhizal fungus Diversispora epigaea (formerly Glomus versiforme ) and its bacterial endosymbionts

Arbuscular mycorrhizal (AM) fungi form endosymbioses with most plants, and they themselves are hosts for Mollicutes/Mycoplasma-related endobacteria (MRE). Despite their significance, genomic information for AM fungi and their MRE are relatively sparse, which hinders our understanding of their biology and evolution. We assembled the genomes of the AM fungus Diversispora epigaea (formerly Glomus versiforme) and its MRE and performed comparative genomics and evolutionary analyses. The D. epigaea genome showed a pattern of substantial gene duplication and differential evolution of gene families, including glycosyltransferase family 25, whose activities are exclusively lipopolysaccharide biosynthesis. Genes acquired by horizontal transfer from bacteria possibly function in defense against foreign DNA or viruses. The MRE population was diverse, with multiple genomes displaying characteristics of differential evolution and encoding many MRE-specific genes as well as genes of AM fungal origin. Gene family expansion in D. epigaea may enhance adaptation to both external and internal environments, such as expansion of kinases for signal transduction upon external stimuli and expansion of nucleoside salvage pathway genes potentially for competition with MRE, whose genomes lack purine and pyrimidine biosynthetic pathways. Collectively, this metagenome provides high-quality references and begins to reveal the diversity within AM fungi and their MRE.

59 BASIC BIOLOGICAL SCIENCES↗

Application of Markov Chain Monte Carlo Methods for Uncertainty Quantification in Inverse Transport Problems

Determination of the components of a radioactive source/shield system using the system’s radiation signature is of great importance in homeland security, material safeguards, and waste management. Although significant progress has been made toward solving this inverse transport problem in recent years, work remains to be done to quantify the uncertainty in reconstructed results. In this article we apply two Markov chain Monte Carlo (MCMC) approaches, the delayed rejection adaptive metropolis (DRAM) and differential evolution adaptive metropolis (DREAM) methods, to solve inverse problems and quantify uncertainty. The DRAM method uses delayed rejection combined with global adaptation of the proposal covariance matrix. Furthermore, the DREAM method hybridizes MCMC sampling with the differential evolution (DE) algorithm. In numerical test cases, the DRAM and DREAM methods are shown to be superior to a first-order inverse Hessian approach for problems with noisy data and multiple unknown quantities, with DREAM converging to the posterior distribution more quickly than DRAM. The DREAM and DRAM results indicate that a full posterior distribution is required to quantify uncertainty in many inverse transport problems.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this study, a Differential Evolution Adaptive Metropolis (DREAM) algorithm was used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The DREAM is a multi-chain method and uses differential evolution technique for chain movement, allowing it to be efficiently applied to high-dimensional problems, and can reliably estimate heavy-tailed and multimodal distributions that are difficult for single-chain schemes using a Gaussian proposal distribution. The results were evaluated against the popular Adaptive Metropolis (AM) scheme. DREAM indicated that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identified one mode. The calibration of DREAM resulted in a better model fit and predictive performance compared to the AM. DREAM provides means for a good exploration of the posterior distributions of model parameters. Lastly, it reduces the risk of false convergence to a local optimum and potentially improves the predictive performance of the calibrated model.

54 ENVIRONMENTAL SCIENCES↗

Quantitative Analysis of the Morphology of {101} and {001} Faceted Anatase TiO 2 Nanocrystals and Its Implication on Photocatalytic Activity

The atomistic structure and morphology (shape and size) of nanomaterials have strong influences on their physical and chemical properties. However, many characterization techniques focus exclusively on one length-scale regime or another when developing quantitative morphology/structural models. In this article, we demonstrate that powder X-ray diffraction and neutron pair distribution function (PDF) can be used to obtain accurate average morphology and atomistic structure of {001} and {101} faceted anatase TiO 2 nanocrystals based on differential evolution refinements using Debye scattering equation calculations. It is also demonstrated that the morphology polydispersity of TiO 2 nanocrystals can be effectively obtained from the diffraction data via a numerical refinement routine. The morphology refinement results are in good agreement with those from transmission electron microscopy and the modeling of small angle neutron scattering data. This method is successfully used to quantify the facet-specified photocatalytic hydrogen evolution activity of anatase TiO 2 nanocrystals with different {001} to {101} ratios. It is found that the sample with an intermediate amount of both {001} and {101} facets shows the best photocatalytic hydrogen evolution reaction (HER) activity. It is expected that the simultaneous structure and morphology refinement technique can be generally used to study the relationship between morphology and functionality of nanomaterials.

36 MATERIALS SCIENCE↗

SAChES: Scalable Adaptive Chain-Ensemble Sampling.

We present the development of a parallel Markov Chain Monte Carlo (MCMC) method called SAChES, Scalable Adaptive Chain-Ensemble Sampling. This capability is targed to Bayesian calibration of com- putationally expensive simulation models. SAChES involves a hybrid of two methods: Differential Evo- lution Monte Carlo followed by Adaptive Metropolis. Both methods involve parallel chains. Differential evolution allows one to explore high-dimensional parameter spaces using loosely coupled (i.e., largely asynchronous) chains. Loose coupling allows the use of large chain ensembles, with far more chains than the number of parameters to explore. This reduces per-chain sampling burden, enables high-dimensional inversions and the use of computationally expensive forward models. The large number of chains can also ameliorate the impact of silent-errors, which may affect only a few chains. The chain ensemble can also be sampled to provide an initial condition when an aberrant chain is re-spawned. Adaptive Metropolis takes the best points from the differential evolution and efficiently hones in on the poste- rior density. The multitude of chains in SAChES is leveraged to (1) enable efficient exploration of the parameter space; and (2) ensure robustness to silent errors which may be unavoidable in extreme-scale computational platforms of the future. This report outlines SAChES, describes four papers that are the result of the project, and discusses some additional results.

97 MATHEMATICS AND COMPUTING↗

Temperature-dependent mechanical properties and crystal plasticity parameters for additively manufactured Haynes-214 alloy: Experiments and numerical modeling

Our experimental mechanical testing data demonstrated that the additively manufactured (AM) laser powder bed fusion (L-PBF) Haynes-214 alloy exhibits non-linear mechanical properties as the temperature rises from ambient to 870 °C. Crystal plasticity (CP) simulations provide an effective approach to gaining deeper insights into microstructure-property linkages under thermomechanical loading. This method can reduce the need for costly high-temperature mechanical testing while accounting for the effects of crystallographic texture and grain morphology on the mechanical behavior of AM materials. However, calibrating a CP model is time-consuming because individual simulations are computationally expensive and hundreds (or more) of iterations over parameter sets may be required. To address this issue, we have designed a machine learning-differential evolution (ML-DE) CP framework that can accurately interpolate the tensile properties of AM L-PBF Haynes-214 alloy across a wide temperature range from ambient to 870 °C, with minimal reliance on experimental data. The framework uses electron backscatter diffraction (EBSD) measurements to generate statistically equivalent microstructural volume elements to serve as inputs to the CP modeling framework. Stress–strain curves were generated from 1000 CP simulations, which serve as the training data set for the three ML regression algorithms explored: linear, extra-trees, and multi-layer perceptron. These three regression models were independently evaluated to compare their efficiency and identify the most suitable algorithm for the given problem. Results revealed that the extra-trees ML regressor outperforms the other models in both qualitative and quantitative aspects with an R 2 of 0.98. Subsequently, the differential evolution optimization approach is employed to calibrate the ML-based CP material parameters with experimental results obtained at various temperatures. Finally, temperature-dependent CP material parameters are formulated. The effectiveness and efficiency of the designed framework are validated through comparison with experimental results, demonstrating a high degree of agreement. These calibrated parametric constitutive equations enable further use of the CP model to study the deformation behavior of this alloy under a wide range of thermo-mechanical loading conditions.

36 MATERIALS SCIENCE↗

Grainsize evolution and differential comminution in an experimental regolith

The comminution of planetary surfaces by exposure to continuous meteorite bombardment was simulated by impacting the same fragmental gabbro target 200 times. The role of comminution and in situ gardening of planetary regoliths was addressed. Mean grain size continuously decreased with increasing shot number. Initially it decreased linearly with accumulated energy, but at some stage comminution efficiency started to decrease gradually. Point counting techniques, aided by the electron microprobe for mineral identification, were performed on a number of comminution products. Bulk chemical analyses of specific grain size fractions were also carried out. The finest sizes ( 10 microns) display generally the strongest enrichment/depletion factors. Similar, if not exactly identical, trends are reported from lunar soils. It is, therefore, not necessarily correct to explain the chemical characteristics of various grain sizes via different admixtures of materials from distant source terrains. Differential comminution of local source rocks may be the dominating factor.

Horz, F.↗

Chemical differentiation, thermal evolution, and catastrophic overturn on Venus: Predictions and geologic observations

Observations from Magellan show that: (1) the surface of Venus is generally geologically young, (2) there is no evidence for widespread recent crustal spreading or subduction, (3) the crater population permits the hypothesis that the surface is in production, and (4) relatively few impact craters appear to be embayed by volcanic deposits suggesting that the volcanic flux has drastically decreased as a function of time. These observations have led to consideration of hypotheses suggesting that the geological history of Venus may have changed dramatically as a function of time due to general thermal evolution, and/or thermal and chemical evolution of a depleted mantle layer, perhaps punctuated by catastrophic overturn of upper layers or episodic plate tectonics. We have previously examined the geological implications of some of these models, and here we review the predictions associated with two periods of Venus history. Stationary thick lithosphere and depleted mantle layer, and development of regional to global development of regional to global instabilities, and compare these predictions to the geological characteristics of Venus revealed by Magellan.

Head, James W.↗

Re-Os Isotopic Constraints on the Chemical Evolution and Differentiation of the Martian Mantle

The (187)Re-187Os isotopic systematics of SNC meteorites, thought to be from Mars, provide valuable information regarding the chemical processes that affected the Martian mantle, particularly with regard to the relative abundances of highly siderophile elements (HSE). Previously published data (Birck and Allegre 1994, Brandon et al. 2000), and new data obtained since these studies, indicate that the HSE and Os isotopic composition of the Martian mantle was primarily set in its earliest differentiation history. If so, then these meteorites provide key constraints on the processes that lead to variation in HSE observed in not only Mars, but also Earth, the Moon and other rocky bodies in the Solar System. Processes that likely have an effect on the HSE budgets of terrestrial mantles include core formation, magma ocean crystallization, development of juvenile crust, and the addition of a late veneer. Each of these processes will result in different HSE variation and the isotopic composition of mantle materials and mantle derived lavas. Two observations on the SNC data to present provide a framework for which to test the importance of each of these processes. First, the concentrations of Re and Os in SNC meteorites indicate that they are derived from a mantle that has similar concentrations to the Earth's mantle. Such an observation is consistent with a model where a chondritic late veneer replenished the Earth and Martian mantles subsequent to core formation on each planet. Alternative models to explain this observation do exist, but will require additional data to test the limitations of each. Second, Re-Os isotopic results from Brandon et al. (2000) and new data presented here, show that initial yos correlates with variations in the short-lived systems of (182)Hf- (182)W and (142)Sm-142Nd in the SNC meteorites (epsilon(sub W) and epsilon(sub 142Nd)). These systematics require an isolation of mantle reservoirs during the earliest differentiation history of Mars, and subsequent inefficient mixing between these reservoirs. These data show that models for the origin of isotopic variation for SNC meteorites require at least two long-lived mantle reservoirs, and possibly three. The range in the projected present day gamma(sub Os) of these reservoirs is from -5.4+/-2.6, to +4+/-1. The isotopic systematics of these reservoirs may be linked to development of cumulate crystal piles in a Martian magma ocean and variable amounts of late stage intercumulus melt. In this model, fractional crystallization of olivine and possibly other phases with slightly subchondritic Re/Os, from a solidifying magma ocean, resulted in a lower Re/Os ratio early cumulates, and a resultant low gamma(sub Os). Later cumulates or evolved melts crystallized with higher Re/Os ratios to produce the mantle reservoir(s) with consequent higher gamma(sub Os). Crystallization of the Martian magma ocean followed earliest core formation, as indicated by the correlation of epsilon(sub W) with epsilon(sub 142Nd) and initial gamma(sub Os).

Brandon, Alan D.↗

THE GALAXY OPTICAL LUMINOSITY FUNCTION FROM THE AGN AND GALAXY EVOLUTION SURVEY

We present the galaxy optical luminosity function for the redshift range 0.05 < z < 0.75 from the AGN and Galaxy Evolution Survey, a spectroscopic survey of 7.6 deg{sup 2} in the Booetes field of the NOAO Deep Wide-Field Survey. Our statistical sample is composed of 12,473 galaxies with known redshifts down to I = 20.4 (AB). Our results at low redshift are consistent with those from Sloan Digital Sky Survey; at higher redshift, we find strong evidence for evolution in the luminosity function, including differential evolution between blue and red galaxies. We find that the luminosity density evolves as (1 + z){sup (0.54{+-}0.64)} for red galaxies and (1 + z){sup (1.64{+-}0.39)} for blue galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

Advances in global optimization of high brightness beams

High brightness electron beams play an important role in accelerator-based applications such as driving X-ray free electron laser (FEL) radiation.Here in this paper, we report on advances in global beam dynamics optimization of an accelerator design using start-to-end simulations and a new parallel multi-objective differential evolution optimization method. The global optimization results in significant improvement of the final electron beam brightness.

43 PARTICLE ACCELERATORS↗