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At least 1,225 records · Page 68

Tricyclononenes and tricyclononadienes as efficient monomers for controlled ROMP: understanding structure–propagation rate relationships and enabling facile post-polymerization modification

Grubbs 3rd-generation (G3) pre-catalyst-initiated ring-opening metathesis polymerization (ROMP) remains an indispensable tool in the polymer chemist's toolbox. Tricyclononenes (TCN) and tricyclononadienes (TCND) represent under-explored classes of monomers for ROMP that have the potential to both advance fundamental knowledge (e.g., structure-polymerization kinetics relationships) and serve as practical tools for the polymer chemist (e.g., post-polymerization functionalization). In this work, a library of TCN and TCND imides, monoesters, and diesters, along with their exo-norbornene counterparts, were synthesized to compare their behaviors in G3-initiated ROMP. Real-time 1 H NMR was used to study their polymerization kinetics; propagation rates ( k p ) were extracted for each monomer. To understand the relationships between monomer structure and ROMP propagation rates, density functional theory methods were used to calculate a variety of electronic and steric parameters for each monomer. While electronic parameters (e.g., HOMO energy levels) correlated positively with the measured k p values, steric parameters generally gave improved correlations, which indicates that monomer size and shape are better predictors for k p than electronic parameters for this data set. Furthermore, the TCND diester—which contains an electron-deficient cyclobutene that is resistant to ROMP—and its polymer p(TCND) are shown to be highly reactive toward DBU-catalyzed conjugate addition reactions with thiols, providing a protecting- and activating-group free strategy for post-polymerization modification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Second-order perturbative corrections to the restricted active space configuration interaction with the hole and particle approach

Second-order corrections to the restricted active space configuration interaction (RASCI) with the hole and particle truncation of the excitation operator are developed. Theoretically, the computational cost of the implemented perturbative approach, abbreviated as RASCI(2), grows like its single reference counterpart in MP2. Two different forms of RASCI(2) have been explored, that is the generalized Davidson-Kapuy and the Epstein-Nesbet partitions of the Hamiltonian. The preliminary results indicate that the use of energy level shift of a few tenths of a Hartree might systematically improve the accuracy of the RASCI(2) energies. The method has been tested in the computation of the ground state energy profiles along the dissociation of the hydrogen fluoride and N{sub 2} molecules, the computation of correlation energy in the G2/97 molecular test set, and in the computation of excitation energies to low-lying states in small organic molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Benchmarking third-order cluster perturbation theory for electronically excited states

In this study, we investigate the reliability of cluster perturbation (CP) theory applied to the calculation of electronically excited states through a comprehensive benchmark. In CP theory, perturbative corrections are added to the properties of a parent excitation space, which converge toward the properties of a target excitation space. For the CPS(D-n) model, perturbative corrections through order n are added to the coupled cluster singles (CCS) excitation energies to target the coupled cluster singles and doubles (CCSD) excitation energies. Through a comparative analysis of excitation energy calculations across a diverse set of molecules and wavefunction methods, we present a comprehensive evaluation of the accuracy of the third-order CPS(D) model, CPS(D-3), in calculating excitation energies. Further, our findings demonstrate that CPS(D-3) is a reliable alternative to established methods, particularly CCSD, while systematically overestimating the excitation energies compared to high-level coupled cluster methods such as CC3. These results highlight the strengths and limitations of CPS(D-3), as well as the promising directions for its future development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observational consequences of the standard model Higgs inflation variants

We consider the possibility to observationally differentiate the Standard Model (SM) Higgs driven inflation with non-minimal coupling to gravity from other variants of SM Higgs inflation based on the scalar field theories with non-canonical kinetic term such as Galileon-like kinetic term and kinetic term with non-minimal derivative coupling to the Einstein tensor. In order to ensure consistent results, we study the SM Higgs inflation variants by using the same method, computing the full dynamics of the background and perturbations of the Higgs field during inflation at quantum level. Assuming that all the SM Higgs inflation variants are consistent theories, we use the MCMC technique to derive constraints on the inflationary parameters and the Higgs boson mass from their fit to WMAP7+SN+BAO data set. We conclude that a combination of the SM Higgs mass measurement by the LHC and accurate determination by the PLANCK satellite of the spectral index of curvature perturbations and tensor-to-scalar ratio will enable to distinguish among these models. We also show that the consistency relations of the SM Higgs inflation variants are distinct enough to differentiate among them.

79 ASTRONOMY AND ASTROPHYSICS↗

Physics-Informed Deep Learning-Based Proof-of-Concept Study of a Novel Elastohydrodynamic Seal for Supercritical CO 2 Turbomachinery

Supercritical carbon dioxide (sCO 2 ) power cycles show promising potential of higher plant efficiencies and power densities for a wide range of power generation applications such as fossil fuel power plants, nuclear power production, solar power, and geothermal power generation. sCO 2 leakage through the turbomachinery has been one of the main concerns in such applications. To offer a potential solution, we propose an elastohydrodynamic (EHD) seal that can work at elevated pressures and temperatures with low leakage and minimal wear. The EHD seal has a very simple, sleeve-like structure, wrapping on the rotor with minimal initial clearance at micron levels. Here, in this work, a proof-of-concept study for the proposed EHD seal was presented by using the simplified Reynolds equation and Lame’s formula for the fluid flow in the clearance and for seal deformation, respectively. The set of nonlinear equations was solved by using both the conventional Prediction–Correction (PC) method and modern Physics-Informed Neural Network (PINN). It was shown that the physics-informed deep learning method provided good computational efficiency in resolving the steep pressure gradient in the clearance with good accuracy. The results showed that the leakage rates increased quadratically with working pressures and reached a steady-state at high-pressure values of 15~20 MPa, where Q = 300 g/s at 20 MPa for an initial seal clearance of 255 μm. This indicates that the EHD seal could be tailored to become a potential solution to minimize the sCO 2 discharge in power plants.

30 DIRECT ENERGY CONVERSION↗

A comprehensive formulation for volumetric modulated arc therapy planning

Purpose: Volumetric modulated arc therapy (VMAT) is a widely employed radiation therapy technique, showing comparable dosimetry to static beam intensity modulated radiation therapy (IMRT) with reduced monitor units and treatment time. However, the current VMAT optimization has various greedy heuristics employed for an empirical solution, which jeopardizes plan consistency and quality. The authors introduce a novel direct aperture optimization method for VMAT to overcome these limitations. Methods: The comprehensive VMAT (comVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term to penalize the difference between the optimized dose and the prescribed dose, as well as an anisotropic total variation term to promote piecewise continuity in the fluence maps, preparing it for direct aperture optimization. A level set function was used to describe the aperture shapes and the difference between aperture shapes at adjacent angles was penalized to control MLC motion range. A proximal-class optimization solver was adopted to solve the large scale optimization problem, and an alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc comVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme case, a lung (LNG) case, and two head and neck cases—one with three PTVs (H&N{sub 3PTV}) and one with foue PTVs (H&N{sub 4PTV})—to test the efficacy. The plans were optimized using an alternating optimization strategy. The plans were compared against the clinical VMAT (clnVMAT) plans utilizing two overlapping coplanar arcs for treatment. Results: The optimization of the comVMAT plans had converged within 600 iterations of the block minimization algorithm. comVMAT plans were able to consistently reduce the dose to all organs-at-risk (OARs) as compared to the clnVMAT plans. On average, comVMAT plans reduced the max and mean OAR dose by 6.59% and 7.45%, respectively, of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N{sub 3PTV} case. PTV coverages measured by D95, D98, and D99 were within 0.25% of the prescription dose. By comprehensively optimizing all beams, the comVMAT optimizer gained the freedom to allow some selected beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel nongreedy VMAT approach simultaneously optimizes all beams in an arc and then directly generates deliverable apertures. The single arc VMAT approach thus fully utilizes the digital Linac’s capability in dose rate and gantry rotation speed modulation. In practice, the new single VMAT algorithm generates plans superior to existing VMAT algorithms utilizing two arcs.

60 APPLIED LIFE SCIENCES↗

Machine Learning of All Mycobacterium tuberculosis H37Rv RNA-seq Data Reveals a Structured Interplay between Metabolism, Stress Response, and Infection

Mycobacterium tuberculosis is one of the most consequential human bacterial pathogens, posing a serious challenge to 21st century medicine. A key feature of its pathogenicity is its ability to adapt its transcriptional response to environmental stresses through its transcriptional regulatory network (TRN). While many studies have sought to characterize specific portions of the M. tuberculosis TRN, and some studies have performed system-level analysis, few have been able to provide a network-based model of the TRN that also provides the relative shifts in transcriptional regulator activity triggered by changing environments. Here, we compiled a compendium of nearly 650 publicly available, high quality M. tuberculosis RNA-sequencing data sets and applied an unsupervised machine learning method to obtain a quantitative, top-down TRN. It consists of 80 independently modulated gene sets known as “iModulons,” 41 of which correspond to known regulons. These iModulons explain 61% of the variance in the organism’s transcriptional response. We show that iModulons (i) reveal the function of poorly characterized regulons, (ii) describe the transcriptional shifts that occur during environmental changes such as shifting carbon sources, oxidative stress, and infection events, and (iii) identify intrinsic clusters of regulons that link several important metabolic systems, including lipid, cholesterol, and sulfur metabolism. This transcriptome-wide analysis of the M. tuberculosis TRN informs future research on effective ways to study and manipulate its transcriptional regulation and presents a knowledge-enhanced database of all published high-quality RNA-seq data for this organism to date.

59 BASIC BIOLOGICAL SCIENCES↗

A multi-dimensional search for new heavy resonances decaying to boosted $\text{W}$ $\text{W}$, $\text{W}$ $\text{Z}$, or $\text{Z}$ $\text{Z}$ boson pairs in the dijet final state at 13 $\text {Te}\text{V}$

A search in an all-jet final state for new massive resonances decaying to $\text{ W }{}{}\text{ W }{}{}$, $\text{ W }{}{}\text{ Z }{}{}$, or $\text{ Z }{}{}\text{ Z }{}{}$ boson pairs using a novel analysis method is presented. The analysis is performed on data corresponding to an integrated luminosity of 77.3 $\,\text {fb}^{-1}$ recorded with the CMS experiment at the LHC at a centre-of-mass energy of 13 $\text {Te}\text {V}$. The search is focussed on potential narrow-width resonances with masses above 1.2 $\text {Te}\text {V}$, where the decay products of each $\text{ W }{}{}$ or $\text{ Z }{}{}$ boson are expected to be collimated into a single, large-radius jet. The signal is extracted using a three-dimensional maximum likelihood fit of the two jet masses and the dijet invariant mass, yielding an improvement in sensitivity of up to 30% relative to previous search methods. No excess is observed above the estimated standard model background. In a heavy vector triplet model, spin-1 ${\text {Z}}^{\prime }$ and ${\text {W}}^{\prime }$ resonances with masses below 3.5 and 3.8 $\text {Te}\text {V}$, respectively, are excluded at 95% confidence level. In a bulk graviton model, upper limits on cross sections are set between 27 and 0.2 $\,\text {fb}$ for resonance masses between 1.2 and 5.2 $\text {Te}\text {V}$, respectively. The limits presented in this paper are the best to date in the dijet final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Automated model formulation for time-varying flexible structures

Presented here is an identification technique that uses the sensor information to choose a new model out of a finite set of discrete model space, in order to follow the observed changes to the given time varying flexible structure. Boundary condition sets or other information on model variations are used to organize the set of possible models laterally into a search tree with levels of abstraction used to order the models vertically within branches. An object-oriented programming approach is used to represent the model set in the search tree. A modified A (asterisk) best first search algorithm finds the model where the model response best matches the current observations. Several extensions to this methodology are discussed. Methods of possible integration of rules with the current search algorithm are considered to give weight to interpreted trends that may be found in a series of observations. This capability might lead, for instance, to identifying a model that incorporates a progressive damage rather than with incorrect paramenters such as added mass. Another new direction is to consider the use of noisy time domain sensor feedback rather than frequency domain information in the search algorithm to improve the real-time capability of the developed procedure.

Glass, B. J.↗

DRS: Derivational Reasoning System

The high reliability requirements for airborne systems requires fault-tolerant architectures to address failures in the presence of physical faults, and the elimination of design flaws during the specification and validation phase of the design cycle. Although much progress has been made in developing methods to address physical faults, design flaws remain a serious problem. Formal methods provides a mathematical basis for removing design flaws from digital systems. DRS (Derivational Reasoning System) is a formal design tool based on advanced research in mathematical modeling and formal synthesis. The system implements a basic design algebra for synthesizing digital circuit descriptions from high level functional specifications. DRS incorporates an executable specification language, a set of correctness preserving transformations, verification interface, and a logic synthesis interface, making it a powerful tool for realizing hardware from abstract specifications. DRS integrates recent advances in transformational reasoning, automated theorem proving and high-level CAD synthesis systems in order to provide enhanced reliability in designs with reduced time and cost.

Bose, Bhaskar↗

THE ATTRACTIVENESS OF MATERIALS IN ADVANCED NUCLEAR FUEL CYCLES FOR VARIOUS PROLIFERATION AND THEFT SCENARIOS

We must anticipate that the day is approaching when details of nuclear weapons design and fabrication will become common knowledge. On that day we must be particularly certain that all special nuclear materials (SNM) are adequately accounted for and protected and that we have a clear understanding of the utility of nuclear materials to potential adversaries. To this end, this paper examines the attractiveness of materials mixtures containing SNM and alternate nuclear materials associated with the plutonium-uranium reduction extraction (Purex), uranium extraction (UREX), coextraction (COEX), thorium extraction (THOREX), and PYROX (an electrochemical refining method) reprocessing schemes. This paper provides a set of figures of merit for evaluating material attractiveness that covers a broad range of proliferant state and subnational group capabilities. The primary conclusion of this paper is that all fissile material must be rigorously safeguarded to detect diversion by a state and must be provided the highest levels of physical protection to prevent theft by subnational groups; no 'silver bullet' fuel cycle has been found that will permit the relaxation of current international safeguards or national physical security protection levels. The work reported herein has been performed at the request of the U.S. Department of Energy (DOE) and is based on the calculation of 'attractiveness levels' that are expressed in terms consistent with, but normally reserved for, the nuclear materials in DOE nuclear facilities. The methodology and findings are presented. Additionally, how these attractiveness levels relate to proliferation resistance and physical security is discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Detector positioning for the initial subcriticality level determination in accelerator-driven systems

Within the GUINEVERE project (Generation of Uninterrupted Intense Neutrons at the lead Venus Reactor) carried out at SCK-CEN in Mol, the continuous deuteron accelerator GENEPI-3C was coupled to the VENUS-F fast simulated lead-cooled reactor. Today the FREYA project (Fast Reactor Experiments for hYbrid Applications) is ongoing to study the neutronic behavior of this Accelerator Driven System (ADS) during different phases of operation. In particular the set-up of a monitoring system for the subcriticality of an ADS is envisaged to guarantee safe operation of the installation. The methodology for subcriticality monitoring in ADS takes into account the determination of the initial subcriticality level, the monitoring of reactivity variations, and interim cross-checking. At start-up, the Pulsed Neutron Source (PNS) technique is envisaged to determine the initial subcriticality level. Thanks to its reference critical state, the PNS technique can be validated on the VENUS-F core. A detector positioning methodology for the PNS technique is set up in this paper for the subcritical VENUS-F core, based on the reduction of higher harmonics in a static evaluation of the Sjoestrand area method. A first case study is provided on the VENUS-F core. This method can be generalised in order to create general rules for detector positions and types for full-scale ADS. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Atmospheric parameters and metallicities for 2191 stars in the globular cluster M4

We report new metallicities for stars of Galactic globular cluster M4 using the largest number of stars ever observed at high spectral resolution in any cluster. We analyzed 7250 spectra for 2771 cluster stars gathered with the Very Large Telescope (VLT) FLAMES+GIRAFFE spectrograph at VLT. These medium-resolution spectra cover a small wavelength range, and often have very low signal-to-noise ratios. We approached this data set by reconsidering the whole method of abundance analysis of large stellar samples from beginning to end. We developed a new algorithm that automatically determines the atmospheric parameters of a star. Nearly all of the data preparation steps for spectroscopic analyses are processed on the syntheses, not the observed spectra. For 322 red giant branch (RGB) stars with V ≤ 14.7, we obtain a nearly constant metallicity, ([Fe/H]) = –1.07 (σ = 0.02). No difference in the metallicity at the level of 0.01 dex is observed between the two RGB sequences identified by Monelli et al. For 1869 subgiant and main-sequence stars with V > 14.7, we obtain ([Fe/H]) = –1.16 (σ = 0.09) after fixing the microturbulent velocity. These values are consistent with previous studies that have performed detailed analyses of brighter RGB stars at higher spectroscopic resolution and wavelength coverage. It is not clear if the small mean metallicity difference between brighter and fainter M4 members is real or is the result of the low signal-to-noise characteristics of the fainter stars. The strength of our approach is shown by recovering a metallicity close to a single value for more than 2000 stars, using a data set that is non-optimal for atmospheric analyses. This technique is particularly suitable for noisy data taken in difficult observing conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

A Monte Carlo Technique to Estimate Emissions from R&D Facilities

The Pacific Northwest National Laboratory (PNNL) operates multidisciplinary laboratory Research and Development (R&D) facilities for the U. S. Department of Energy and sampled air chemical emissions from some of these facilities from 1998 until 2008. Although sampling was not required for environmental compliance, PNNL conducted sampling to provide data to compare estimated release fractions to those used for emissions estimates and to verify that methods used to determine compliance with air regulations and permits conservatively predict actual emissions. Sampling also identifies and quantifies air toxics emitted to compare with compliance limits established by the State. The sampling data provides a unique opportunity to quantify emissions and investigate factors potentially impacting emissions. Previous work using this data set include a paper by Woodruff, Benar, and McCarthy1 who summarized the compliance approach used by PNNL and described sampling and analytical measurements for the first sampling campaigns. Conclusions reported in the paper were that none of the measurements of the target compounds exceeded a State acceptable source impact level (ASIL)2 even using significant overestimation factors, and that an average release fraction calculated from the data provided reasonable validation of the factor used in compliance assessments. Other reports using the data include the following: • A metric was developed by Ballinger, Duchsherer, and Metoyer3 to compare chemical signatures. The analysis found similarities in chemical signatures from three of the buildings but a markedly different signature from the fourth building. • A method was developed and used on the data to rank the chemical compounds that present the greatest risk to a potential downstream receptor and to determine whether the sampling parameters and detection limits provided sufficient resolution to verify compliance at potential receptor locations.4 • The stack data from one of the buildings was analyzed using a statistical technique called Positive Matrix Factorization (PMF) to identify the number and composition of major contributing sources to measured stack concentrations.5 In this analysis, a method is described that uses a Monte Carlo technique to produce a distribution of emission estimates from the measured data. The method is applied to one of the chemicals previously identified as more significant than others using the ranking process.4 Variations on the method are investigated and compared to determine their effects on the emission estimates.

Laboratory, air chemical emissions, volatile organ↗

Time-dependent THMC properties and microstructural evolution of damaged rocks in excavation damage zone

Modeling coupled thermo-hydro-mechanical-chemical (THMC) processes in host rocks near high-level nuclear waste (HLW) repositories at various time scales is an extremely challenging task. The current study integrates experimental, theoretical, and numerical methods in assessing the evolution of excavation damage zone (EDZ) over time and its implication on the long-term migration of hazardous species. Argillite and rock salt and are the focus of this study. The first part of the report presents a novel time-dependent directional microcrack damage theory for generic brittle rocks. It features detailed statistical description of the microcracks within a damaged solid, permitting a direct upscaling of microscale processes such as crack growth kinetics, crack closure/opening, sliding friction to explain the macroscopic creep, nonlinear elasticity, shear dilation, and loading-unloading hysteresis. This provides a basic platform for describing the anisotropic mechanical and transport properties of damaged rocks during excavation and subsequent THMC loadings. The model is validated and numerically implemented to Finite Element (FE) package ABAQUS through the user-defined material (UMAT) interface and have demonstrated great potential in resolving the time-dependent and anisotropic evolution of damage in the EDZ. The second part of the report presents a multi-scale experimental effort in characterizing the thermal, hydraulic, and mechanical properties of Mancos shale and Avery Island salt. For the Mancos shale, triaxial compression tests are performed at different confining pressures and temperatures to probe its thermomechanical properties relevant to HLW repositories. The obtained stress-strain data are interpreted using the proposed directional damage theory. Post-test specimens are subjected to gas permeability tests to reveal the correlation between permeability and the degree of microcracking. At microscale, temperature-controlled nanoindentation tests are performed and found a linear correlation between fracture toughness and elastic modulus from 25°C to 300°C. For Avery Island salt, we have designed and manufactured a novel relative-humidity controlled uniaxial creep device. Long-term creep tests at low stresses (< 5 MPa) are performed at different levels of relative humidity (RH). Besides confirming the much higher creep rates as one would expect through extrapolating the high-stress creep data, the results reveal that the steady-state creep rate of rock salt is strongly dependent on the ambient RH, an aspect that is often neglected in the literature. Both behaviors can be attributed to the pressure-solution creep mechanism which dominates at low stress and high RH levels. The third part of the report explores a set of numerical strategies in modeling the THMC behavior of porous geomaterials. A fully implicit, monolithic FE solution that can flexibly interface with different material models and coupling mechanisms for THMC problems is developed and verified through the ABAQUS user-defined element (UEL) interface. The scheme is used to study the THM response of a hypothetical HLW storage site with reference to an existing in-situ heater test. Strategies for integrating the UEL and the microcrack UMAT are suggested. Another numerical endeavor of this study is to implement a higher-order asymptotic homogenization method to account for the heterogeneous porous structures. The same method is then extended to perform microstructure-informed thermo-mechanical modeling of generalized continua. The above outcomes of this project provide a strong thrust towards enhancing the fundamental understanding and modeling capability of the long-term evolution of host rocks in EDZ, thus helping achieve the design goal of 1-million-year isolation of high-level nuclear wastes.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptive control with an expert system based supervisory level

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

Sullivan, Gerald A.↗

Goal-oriented sensitivity analysis for lattice kinetic Monte Carlo simulations

In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo (KMC). Sensitivity analysis for stochastic systems is typically based on approximating continuous derivatives with respect to model parameters by the mean value of samples from a finite difference scheme. Instead of using independent samples the proposed algorithm reduces the variance of the estimator by developing a strongly correlated-“coupled”- stochastic process for both the perturbed and unperturbed stochastic processes, defined in a common state space. The novelty of our construction is that the new coupled process depends on the targeted observables, e.g., coverage, Hamiltonian, spatial correlations, surface roughness, etc., hence we refer to the proposed method as goal-oriented sensitivity analysis. In particular, the rates of the coupled Continuous Time Markov Chain are obtained as solutions to a goal-oriented optimization problem, depending on the observable of interest, by considering the minimization functional of the corresponding variance. We show that this functional can be used as a diagnostic tool for the design and evaluation of different classes of couplings. Furthermore, the resulting KMC sensitivity algorithm has an easy implementation that is based on the Bortz–Kalos–Lebowitz algorithm's philosophy, where events are divided in classes depending on level sets of the observable of interest. Finally, we demonstrate in several examples including adsorption, desorption, and diffusion Kinetic Monte Carlo that for the same confidence interval and observable, the proposed goal-oriented algorithm can be two orders of magnitude faster than existing coupling algorithms for spatial KMC such as the Common Random Number approach. We also provide a complete implementation of the proposed sensitivity analysis algorithms, including various spatial KMC examples, in a supplementary MATLAB source code.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Standardizing Performance Metrics for Building-Level Electrical Distribution Systems

Building-level electrical distribution systems comprise a myriad of current-carrying equipment, conversion devices, and protection devices that deliver power from the utility or local distributed energy resources to end-use building loads. Electric power has traditionally been generated, transmitted, and distributed in alternating current (AC). However, the last decade has seen a significant increase in the integration of native direct current (DC) equipment that has elevated the importance of DC distribution systems. Numerous studies have comparatively examined the performance of various electrical distribution systems in buildings but have failed to achieve uniform conclusions, primarily because of a lack of consistent and analogous performance evaluation methods. This paper aims to fill this gap by providing a standard set of metrics and measurement boundaries to consistently evaluate the performance of AC, DC, or hybrid AC/DC electrical distribution systems. The efficacy of the proposed approach is evaluated on a representative medium-sized commercial office building model with AC distribution and an equivalent hybrid AC/DC and DC distribution model, wherein the AC distribution model is concluded to be the most efficient. The simulation results show variation in computed metrics with different selected boundaries that verify the effectiveness of the proposed approach in ensuring consistent computation of the performance of building-level electrical distribution systems. This paper provides an initial set of guidelines for building energy system stakeholders to adopt appropriate solutions, thus leading to more efficient energy systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗