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At least 505 records · Page 28

Development of a Scalable Risk-informed Predictive Maintenance Cloud-based Strategy at Nuclear Power Plants

The fact that light-water reactor operation and maintenance costs are prohibitively expensive and contribute to the premature decommissioning of nuclear power plants is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology, as its low cost, computing and storage adaptability, and ability to host applications across numerous virtual infrastructures potentially make it a cost-effective alternative to onsite storage and diagnostics. In this paper, a technological assessment is carried out on a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. This cloud-based monitoring system would enable maintenance and diagnostic analysts and other authorized plant users to remotely monitor equipment functionality, thus enabling early fault detection and effective predictive maintenance practices. To provide data processing and storage, sensor device networking, and database management, the Microsoft Azure cloud platform is utilized as part of the proposed cloud architecture; however, this analysis could be extended to other cloud computing service providers as well. The focus of this paper is on application of cloud resources for enabling predictive maintenance, identification of technological hurdles associated with moving to a cloud-computing-based architecture, and potential benefits from moving to a centralized cloud system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Incremental Threshold Scheme Enabled IoT Group Key Management

Cyber landscape evolves rapidly. Internet of Things (IoT) and Edge Computing (EC) have rapidly become an integral part of the modern computing infrastructure. It is expected that there will be more than 50 billion active and connected IoT devices by 2025 [1]. Pervasive IoT/EC creates unprecedented opportunities bridging the gap between previously segregated cyber and physical spaces. However, this progress also brings along new security challenges. IoT devices typically have limited computation, communication, and storage resources. This leads to security architecture designs such as using symmetric keys for group communication. While secure and efficient in stable network settings, symmetric key solutions are ill-adapted for IoT's highly dynamic device mobility behavior and frequent group membership turnover. Whenever IoT members leave a group, the known symmetric keys cannot be made forgotten, posing a serious vulnerability. This leads to frequent re-groupings that require expensive re-authentication, key regeneration, and key redistribution in order to maintain IoT/EC security. We present a novel symmetric key management framework that integrate an Incremental Threshold Scheme (ITS) cryptographical function into communication protocol's key rotation mechanism to allow for secure and efficient symmetric key communication group member node revocation. This ITS-enabled key management framework alleviates the need of frequent and expensive re-grouping and re-keying needed by today's large and dynamic IoT/EC operations. We further applied this ITS-enabled key management framework to a distributed IoT/EC-integrated publish and subscribe framework for applicability validation.

Li, Mingyan↗

Aerothermal Analysis of the Rocket Lab Venus Probe Heatshield

This document provides an overview of the aerothermodynamic analyses performed by the Aerothermodynamics Branch at NASA Langley Research Center for the Rocket Lab Venus Probe (RLVP). In addition to defining the baseline heating environment to the heatshield, this document pursues the experimental validation of key physical models at RLVP-relevant conditions. This experimental validation analysis, which captures the model form uncertainty, is used as one of two primary components of the margin assessment, where the other component is the parametric uncertainty. These model form (experimental) and parametric uncertainty components are used to construct a spatial and time varying margin for the heating to the RLVP heatshield. The margin is evaluated as the sum of the parametric and model form uncertainty components. The model form uncertainty is defined as the difference between the RLVP-relevant measurements and their simulations, using the upper limit uncertainty bounds for both the measurements and simulations in the comparisons. The differences in the dominant physics in the stagnation region and flank lead to the separate RLVP-relevant measurements for assessing the model form uncertainty in these two regions. These regions are addressed as follows: Stagnation Region Heating Environment: For the high-temperature stagnation-region, both the radiative heating and impact of blowing on convective heating are significant, while the impacts of turbulence and roughness are negligible. Coupled radiation and ablation LAURA/HARA solutions with ray-tracing provide the radiative heating over the entire vehicle, including the contributions from the Venus atmosphere and ablation species. Non-ablating LAURA simulations provide the convective heating. During the material-response computation typically used for TPS sizing, this non-ablating convective heating is corrected for the impact of ablation using the blowing correction. Coupled ablation LAURA simulations that capture finite-rate sur-face processes show that this blowing correction may be non-conservative over most of the heatshield. This non-conservatism is due to hydrogen recombination in the finite-rate surface model, which tends to increase the coupled ablation convective heating to near the non-ablating values, therefore making any reduction in the non-ablating value through the blowing correction non-conservative. This non-conservatism due to H catalysis is captured in the parametric component of the margin. The best available ground-test measurements that capture the impact of blowing on stagnation region convective heating, at RLVP-relevant conditions, indicate that the current blowing reduction model is non-conservative by up to 20% at RLVP-relevant blowing rates (the coupled blowing simulations were also non-conservative). Because of the relatively low velocity of the ground tests and the non-Venus atmospheric chemistry, these measurements do not capture the chemistry and therefore do not inform the uncertainty due to H catalysis. However, they do capture the fluid mechanics of blowing. The non-conservatism of the blowing correction implied by these measurements is covered by the model form component of the margin, which leads to total margin values over 50%. For the radiative heating, the shock-tube informed bias approach suggests a model form uncertainty of roughly 20%, while the parametric uncertainty analysis suggests values over 100%. The combined stagnation-point radiation margin of over 100% leads to peak margined radiative heating values of over300 W/cm2, which remains small relative to the peak margined convective heating of nearly 2000 W/cm2. Based on this analysis, at the stagnation point, the peak margined heat rate is 2203 W/cm2 and the margined total heat load is 31.5 kJ/cm2 for the current nominal trajectory. Flank Heating Environment: The forebody flank (and near-shoulder) heating environment is dominated by the impact of turbulence, roughness augmentation, and ablation on the convective heating. An extensive collection of ground test measurements with RLVP-relevant turbulence and roughness is studied to show that the maximum difference between the simulated and measured convective heating is 5%. However, with the exception of the Holden measurements from the 1980s, these measurements do not include roughness elements extending into the supersonic region of the boundary layer, which is likely to occur for RLVP (due to the 45 degree sphere-cone geometry). The interaction between the supersonic flow and roughness could cause convective heating augmentation fundamentally different than for locally subsonic flow. Although these Holden measurements are consistent with the other measurements considered, another path was pursued to assure that the rough-ness height extending into supersonic flow does not fundamentally change the roughness augmentation. This additional path was a computational effort to resolve the roughness elements in the CFD grid, so that the interaction be-tween the roughness elements and locally supersonic flow may be simulated in detail. This roughness-resolved CFD simulation is feasible because of the RLVP forebody TPS’s patterned roughness, which may be approximated analytically, and because of the axisymmetric nominal flow field, which allows a narrow surface region to be simulated and therefore make the computational expense feasible. These grid-resolved roughness simulations, which are performed at actual RLVP flight conditions, result in heating augmentation values that are below the design approach for roughness augmentation. This provides evidence that the design approach for RLVP roughness augmentation is sufficient. Based on this analysis, at this flank or near-shoulder location, the peak margined total heat rate is 2088 W/cm2and the margined total heat load is 26.0 kJ/cm2for the current nominal trajectory. Heat flux, shear, pressure and heat transfer coefficient at the RLVP stagnation point and near shoulder location are evaluated for the entire trajectory, and curved fit to a functional form of F=AρB∞UC∞. These simplified relationships for the nominal and margined aerothermal environments are referred to as aerothermal indicators, and presented at the end of this document.

Christopher O Johnston↗

Active- and transfer-learning applied to microscale-macroscale coupling to simulate viscoelastic flows

Active- and transfer-learning are applied to microscale dynamics of polymer flows for the multiscale discovery of effective constitutive approximations required in viscoelastic flow simulation. The result is macroscopic rheology directly connected to a microstructural model. Micro and macroscale simulations are adaptively coupled by means of Gaussian process regression (GPR) to run the expensive microscale computations only as necessary. This multiscale method is demonstrated with flows of a polymer solution as a model system. At the microscale level dissipative particle dynamics (DPD) is employed to model the fluid as a suspension of bead-spring micro-structures subjected to steady shear flow. The results yield the non-Newtonian viscosity and the first normal stress difference at strain rates as training data used in a GPR model. DPD parameters are calibrated with respect to experimental data for a real polymer solution. Compliance with these data requires adjustment of the DPD model's cutoff radius, which then becomes a function of the second invariant of the strain rate tensor. The FENE-P model is chosen for the macroscale description using the spectral element method (SEM) to simulate channel flow and flow past a circular cylinder. The DPD results at the lowest possible shear strain rate yield an estimate of the zero-shear rate viscosity, which allows the initiation of the macroscale flow by SEM as a Newtonian fluid. The resulting strain-rate field is surveyed to determine additional shear strain rate sampling points for the DPD system. This new information allows an initial fitting of parameters of the constitutive equation followed by new SEM simulations at the macroscale. Additionally, guided by active-learning GPR to select new sampling points, this process continues until convergence is achieved. The effectiveness of this new simulation paradigm for viscoelastic flows is tested with different macroscale operating conditions. The effective closure learned in the channel simulation is then transferred directly to the flow past a circular cylinder at low Reynolds number, where the results show that only two additional DPD simulations are required to achieve a satisfactory constitutive model. With an increase of the Reynolds number, the active-learning scheme automatically detects the inaccuracy of the learned constitutive model, and initiates additional DPD simulations for the extra data needed to once again close the microscale-macroscale coupled system. This new paradigm of active- and transfer-learning for multiscale modeling is readily applicable to other microscale-macroscale coupled simulations of complex fluids and other materials. Furthermore, the coupling between microscale and macroscale solvers can be seamlessly implemented with our open source multiscale universal interface (MUI) library.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Structural mode coupling in perovskite oxides using hypothesis-driven active learning

Abstract Finding the ground-state structure with minimum energy is paramount to designing any material. In ABO 3 -type perovskite oxides with Pnma symmetry, the lowest energy phase is driven by an inherent trilinear coupling between the two primary order parameters such as rotation and tilt with antiferroelectric displacement of the A-site cations as established via hybrid improper ferroelectric mechanism. Conventionally, finding the relevant mode coupling driving phase transition requires performing first-principles calculations which is computationally time-consuming as well as expensive. It involves following an intuitive iterative hit and trial method of (a) adding two or multiple mode vectors, followed by (b) evaluating which combination would lead to the ground-state energy. In this study, we show how a hypothesis-driven active learning framework can identify suitable mode couplings within the Landau free energy expansion with minimal information on amplitudes of modes for a series of double perovskite oxides with A-site layered, columnar and rocksalt ordering. This scheme is expected to be applicable universally for understanding atomistic mechanisms derived from various structural mode couplings behind functionalities, for e.g. polarization, magnetization and metal–insulator transitions.

36 MATERIALS SCIENCE↗

Architecture independent environment for developing engineering software on MIMD computers

Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management.

Valimohamed, Karim A.↗

Advanced microfabrication technologies for microspacecraft

Advanced microfabrication technologies offer the prospect of reducing the weight and size of spacecraft through the use of lighter and stronger materials in conjunction with new mechanical/structural design concepts and design optimization methods. At the same time, electronic components have been scaled down while increasing functional utility. A two-fold benefit is derived for space applications through the use of less expensive components and the lower launch costs associated with lighter components. GE-CRD is actively pursuing research in these key technologies for a wide range of applications including satellites. These key technologies will be reviewed and an update on GE progress will be given. The need to reduce weight and lower cost, while maintaining product quality and reliability are primary drivers in the design of satellites, in general, and microsatellites in particular. For the structural subsystem, these requirements pose a complex design problem unless new mechanical design concepts and computer-aided design optimization methods are employed. Several new concepts, such as battery packs doubling as panel reinforcements and fuel tanks as integral structural members, need to utilized. In addition, new viscoelastic material damping concepts for spacecraft components provide for lighter weight/lower cost designs, while satisfying the structural dynamics requirements. High density interconnect (HDI) technology permits the use of bare IC's on a ceramic substrate with 90 percent active area utilization. A copper/polyimide multilayer structure is the backbone of the technology, which has demonstrated a size/weight reduction of greater than 10x compared to printed circuit board with performance up to the GHz level. HDI modules have exceptional mechanical robustness as evidenced by survival of 180 kg rapid acceleration tests. Microelectromechanical systems (MEMS) are redefining sensors and actuators by miniaturization through micromachining techniques. Sharing many fabrication steps with HDI, we have developed a new technique for surface micromachining of copper/polyimide structures using computer-aided laser patterning.

Ghezzo, M.↗

Accurate predictions from small boxes: variance suppression via the Zel'dovich approximation

Simulations have become an indispensable tool for accurate modelling of observables measured in galaxy surveys, but can be expensive if very large dynamic range in scale is required. We describe how to combine Lagrangian perturbation theory models with N-body simulations to reduce the effects of finite computational volume in the prediction of ensemble average properties in the simulations within the context of control variates. In particular we use the fact that Zel'dovich displacements, computed during initial condition generation for any simulation, correlate strongly with the final density field. Since all the correlators of biased tracers can be computed with arbitrary precision for these displacements, pairing the Zel'dovich `simulation' with the N-body realization allows hundredfold reductions in sample variance for power spectrum or correlation function estimation. Additionally, Zel'dovich control variates can accurately extend matter or tracer field emulators to larger scales than previously possible, as well as improving measurements of statistics in simulations which are inherently limited to small volumes, such as hydrodynamical simulations of galaxy formation and reionization.

79 ASTRONOMY AND ASTROPHYSICS↗

A deep neural network regressor for phase constitution estimation in the high entropy alloy system Al-Co-Cr-Fe-Mn-Nb-Ni

High Entropy Alloys (HEAs) are composed of more than one principal element and constitute a major paradigm in metals research. The HEA space is vast and an exhaustive exploration is improbable. Therefore, a thorough estimation of the phases present in the HEA is of paramount importance for alloy design. Machine Learning presents a feasible and non-expensive method for predicting possible new HEAs on-the-fly. A deep neural network (DNN) model for the elemental system of: Mn, Ni, Fe, Al, Cr, Nb, and Co is developed using a dataset generated by high-throughput computational thermodynamic calculations using Thermo-Calc. The features list used for the neural network is developed based on literature and freely available databases. A feature significance analysis matches the reported HEAs phase constitution trends on elemental properties and further expands it by providing so far-overlooked features. The final regressor has a coefficient of determination ( r 2 ) greater than 0.96 for identifying the most recurrent phases and the functionality is tested by running optimization tasks that simulate those required in alloy design. The DNN developed constitutes an example of an emulator that can be used in fast, real-time materials discovery/design tasks.

36 MATERIALS SCIENCE↗

Bichromatic Wave Selection for Validation of the Difference-Frequency Transfer Function for the OC6 Validation Campaign: Preprint

The focus of the Offshore Code Comparison Collaboration, Continuation, with Correlation and unCertainity (OC6) project, which operates under the International Energy Agency (IEA) Wind Task 30, is to refine the accuracy of engineering tools used to design offshore wind turbines. In support of this work, a new validation campaign is being developed that seeks to better understand the nonlinear wave loading that excites floating wind systems at their low-frequency, rigid-body modes in surge and pitch. The validation data will be used in a three-way validation between simplified engineering tools and higher-fidelity tools, such as computational fluid dynamics (CFD). Irregular wave spectrums, which are traditionally used to examine the nonlinear wave interaction with offshore structures, are too computationally expensive to be simulated in CFD tools, and so bichromatic wave cases will be used instead. This paper reviews the process used to choose the bichromatic wave pairs to be used in the campaign to validate the second-order difference-frequency quadratic and potential loads at the surge and pitch natural frequencies of a floating semisubmersible.

17 WIND ENERGY↗

Forced and Unforced Variability of Twentieth Century North American Droughts and Pluvials

Research on the forcing of drought and pluvial events over North America is dominated by general circulation model experiments that often have operational limitations (e.g., computational expense, ability to simulate relevant processes, etc). We use a statistically based modeling approach to investigate sea surface temperature (SST) forcing of the twentieth century pluvial (1905-1917) and drought (1932-1939, 1948-1957, 1998-2002) events. A principal component (PC) analysis of Palmer Drought Severity Index (PDSI) from the North American Drought Atlas separates the drought variability into five leading modes accounting for 62% of the underlying variance. Over the full period spanning these events (1900-2005), the first three PCs significantly correlate with SSTs in the equatorial Pacific (PC 1), North Pacific (PC 2), and North Atlantic (PC 3), with spatial patterns (as defined by the empirical orthogonal functions) consistent with our understanding of North American drought responses to SST forcing. We use a large ensemble statistical modeling approach to determine how successfully we can reproduce these drought/pluvial events using these three modes of variability. Using Pacific forcing only (PCs 1-2), we are able to reproduce the 1948-1957 drought and 1905-1917 pluvial above a 95% random noise threshold in over 90% of the ensemble members; the addition of Atlantic forcing (PCs 1-2-3) provides only marginal improvement. For the 1998-2002 drought, Pacific forcing reproduces the drought above noise in over 65% of the ensemble members, with the addition of Atlantic forcing increasing the number passing to over 80%. The severity of the drought, however, is underestimated in the ensemble median, suggesting this drought intensity can only be achieved through internal variability or other processes. Pacific only forcing does a poor job of reproducing the 1932-1939 drought pattern in the ensemble median, and less than one third of ensemble members exceed the noise threshold (28%). Inclusion of Atlantic forcing improves the ensemble median drought pattern and nearly doubles the number of ensemble members passing the noise threshold (52%). Even with the inclusion of Atlantic forcing, the intensity of the simulated 1932-1939 drought is muted, and the drought itself extends too far into the southwest and southern Great Plains. To an even greater extent than the 1998-2002 drought, these results suggest much of the variance in the 1932-1939 drought is dependent on processes other than SST forcing. This study highlights the importance of internal noise and non SST processes for hydroclimatic variability over North America, complementing existing research using general circulation models.

Cook, Benjamin I.↗

Gas-phase ion-molecule interactions in a collision reaction cell with triple quadrupole-inductively coupled plasma mass spectrometry: Investigations with N 2 O as the reaction gas

Nitrous oxide (N 2 O) was used as a reaction gas to investigate the gas phase ion-molecule interactions using the Agilent 8900 QQQ-ICP-MS. A multi-element standard containing 45 elements with masses ranging from 9 to 208 u was measured in the presence and absence of N 2 O. The main product ion species observed were oxides and nitrides. Comparison of the N 2 O reaction results with similar measurements conducted with O 2 revealed that N 2 O was more effective at forming oxides in general: the elements Cd and Pb were shown to produce oxides with N 2 O where the reaction did not occur with O 2 . Nitrous oxide was also shown to produce a significant amount of nitride species in a few cases. The general reactivity was shown to be consistent with density functional theory (DFT)-predicted reaction enthalpies, such that all predicted exothermic reactions produced product ions at levels at least 1% of the unreacted ion. Our results show that reaction enthalpy is a reasonable predictor of reactivity with N2O on the timescales of the interactions in non-thermal ICP-MS/MS systems. Our work demonstrates the utility of two relatively new platforms (commercial elemental ICP-MS/MS and EMSL Arrows interface to the NWChem program suite), which allows for the study of a large number of elements within a short period. While DFT with the basis sets utilized here is not the most accurate computational method, it is also not computationally expensive and is shown to be suitable for predicting gas phase reactivity in the QQQ-ICP-MS for the majority of ions studied. Here, the ease and rapidity of data collection and DFT calculations has the potential to be very impactful for the identification of targeted reaction chemistries to be leveraged for analytical method development, such as for the inline separation of isobaric interferences from analytes of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Capturing anharmonicity in a lattice thermal conductivity model for high-throughput predictions

High-throughput, low-cost, and accurate predictions of thermal properties of new materials would be beneficial in fields ranging from thermal barrier coatings and thermoelectrics to integrated circuits. To date, computational efforts for predicting lattice thermal conductivity (κ L ) have been hampered by the complexity associated with computing multiple phonon interactions. In this work, we develop and validate a semiempirical model for κ L by fitting density functional theory calculations to experimental data. Experimental values for κ L come from new measurements on SrIn 2 O 4 , Ba 2 SnO 4 , Cu 2 ZnSiTe 4 , MoTe 2 , Ba 3 In 2 O 6 , Cu 3 TaTe 4 , SnO, and InI as well as 55 compounds from across the published literature. Here, to capture the anharmonicity in phonon interactions, we incorporate a structural parameter that allows the model to predict κ L within a factor of 1.5 of the experimental value across 4 orders of magnitude in κ L values and over a diverse chemical and structural phase space, with accuracy similar to or better than that of computationally more expensive models.

36 MATERIALS SCIENCE↗

Compatibility issues between electrodes and electrolytes in solid-state batteries

Remarkable success has been achieved in the discovery of ceramic alkali superionic conductors as electrolytes in solid-state batteries; however, obtaining a stable interface between these electrolytes and electrodes is difficult. Only limited studies on the compatibility between electrodes and solid electrolytes have been reported, partially because of the need for expensive instrumentation and special cell designs. Without simple yet powerful tools, these compatibility issues cannot be systematically investigated, thus hindering the generalization of design rules for the integration of solid-state battery components. Herein, we present a methodology that combines density functional theory calculations and simple experimental techniques such as X-ray diffraction, simultaneous differential scanning calorimetry and thermal gravimetric analysis, and electrochemistry to efficiently screen the compatibility of numerous electrode/electrolyte pairs. We systemically distinguish between the electrochemical stability of the solid-state conductor, which is relevant wherever the electrolyte contacts an electron pathway, and the electrochemical stability of the electrode/electrolyte interfaces. For the solid electrolyte, we are able to computationally derive an absolute thermodynamic stability voltage window, which is small for Na 3 PS 4 and Na 3 PSe 4 , and a larger voltage window which can be kinetically stabilized. The experimental stability, when measured with reliable techniques, falls between these thermodynamic and kinetic limits. Employing a Na solid-state system as an example, we demonstrate the efficiency of our method by finding the most stable system (NaCrO 2 |Na 3 PS 4 |Na–Sn) within a selected chemical space (more than 20 different combinations of electrodes and electrolytes). Important selection criteria for the cathode, electrolyte, and anode in solid-state batteries are also derived from this study. The current method not only provides an essential guide for integrating all-solid-state battery components but can also significantly accelerate the expansion of the electrolyte/electrode compatibility data.

25 ENERGY STORAGE↗

Transition-state correlations for predicting thermochemistry of adsorbates and surface reactions

Estimating thermochemical properties from linear correlations may provide a pathway to circumvent expensive density functional theory (DFT) calculations for quantities such as pre-exponentials and temperature corrections to DFT energies. Here, in this work, we construct thermochemical scaling relations between C 1 –C 6 n-alkanes in the gas phase and adsorbed alkyl chains extending from several transition metal surfaces, and examine changes in the slope and fit between metals and adsorption sites. We subsequently add –OH, –NH 2 , C$=$O, and C$=$C functional groups to the C 1 –C 6 molecules and demonstrate strong linear correlations for thermochemistry across all species. We broaden the correlations to incorporate transition states of C 1 –C 6 n-alkane dehydrogenation reactions, where thermochemistry for computationally prohibitive transition-state calculations can be quickly assessed. Additionally, we rationalize the linearity of thermochemical correlations based on the composition of the homologous series and theoretical assessments. As an application of the correlations, we estimate pre-exponentials for elementary surface reactions of ethane and propane hydrogenolysis on Ru(0001), which is of relevance to plastic hydrogenolysis. Depending on kinetically important steps, entropic contributions may be necessary to include in certain reaction mechanisms; in contrasting examples, entropies are found to be relatively insignificant for ethane hydrogenolysis but pertinent for propane hydrogenolysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonadiabatic Molecular Dynamics by Multiconfiguration Pair-Density Functional Theory

Herein, we present the first implementation of multiconfiguration pair-density functional theory (MC-PDFT) ab initio molecular dynamics. MC-PDFT is a multireference electronic structure method that in many cases has a similar accuracy (or even better accuracy) the complete active space second-order perturbation theory (CASPT2) at a significantly lower computational cost. In this study, we introduced MC-PDFT analytical gradients into the SHARC molecular dynamics program for ab initio, nonadiabatic molecular dynamics simulations. We verify our implementation by examining the intersystem crossing dynamics of thioformaldehyde, and we observe excellent agreement with recent CASPT2 and experimental findings. Moreover, with MC-PDFT, we could perform dynamics simulations with the 12 electron in 10 orbitals active space that was computationally too expensive for direct dynamics with CASPT2.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Testing Surrogate-Based Optimization with the Fortified Branin-Hoo Extended to Four Dimensions

Some popular functions used to test global optimization algorithms have multiple local optima, all with the same value, making them all global optima. It is easy to make them more challenging by fortifying them via adding a localized bump at the location of one of the optima. In previous work the authors illustrated this for the Branin-Hoo function and the popular differential evolution algorithm, showing that the fortified Branin-Hoo required an order of magnitude more function evaluations. This paper examines the effect of fortifying the Branin-Hoo function on surrogate- based optimization, which usually proceeds by adaptive sampling. Two algorithms are considered. The EGO algorithm, which is based on a Gaussian process (GP) and an algorithm based on radial basis functions (RBF). EGO is found to be more frugal in terms of the number of required function evaluations required to identify the correct basin, but it is expensive to run on a desktop, limiting the number of times the runs could be repeated to establish sound statistics on the number of required function evaluations. The RBF algorithm was cheaper to run, providing more sound statistics on performance. A four-dimensional version of the Branin-Hoo function was introduced in order to assess the effect of dimensionality. Furthermore, it was found that the difference between the ordinary function and the fortified one was much more pronounced for the four-dimensional function compared to the two dimensional one.

97 MATHEMATICS AND COMPUTING↗