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DOE OSTI2017

A New Method for Generating Probability Tables in the Unresolved Resonance Region

One new method for constructing probability tables in the unresolved resonance region (URR) has been developed. This new methodology is an extensive modification of the single-level Breit-Wigner (SLBW) pseudo-resonance pair sequence method commonly used to generate probability tables in the URR. The new method uses a Monte Carlo process to generate many pseudo-resonance sequences by first sampling the average resonance parameter data in the URR and then converting the sampled resonance parameters to the more robust R-matrix limited (RML) format. Furthermore, for each sampled set of pseudo-resonance sequences, the temperature-dependent cross sections are reconstructed on a small grid around the energy of reference using the Reich-Moore formalism and the Leal-Hwang Doppler broadening methodology. We then use the effective cross sections calculated at the energies of reference to construct probability tables in the URR. The RML cross-section reconstruction algorithm has been rigorously tested for a variety of isotopes, including 16 O, 19 F, 35 Cl, 56 Fe, 63 Cu, and 65 Cu. The new URR method also produced normalized cross-section factor probability tables for 238 U that were found to be in agreement with current standards. The modified 238 U probability tables were shown to produce results in excellent agreement with several standard benchmarks, including the IEU-MET-FAST-007 (BIG TEN), IEU-MET-FAST-003, and IEU-COMP-FAST-004 benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2017

Erratum: First-Principles Approach to Calculating Energy Level Alignment at Aqueous Semiconductor Interfaces [Phys. Rev. Lett. 113, 176802 (2014)]

We note, while extending our approach in our Letter to calculate energy level alignment at aqueous TiO 2 interfaces, we discovered two problems with our application of the GW methodology. Briefly, in our approach, we used a DFT + U approach for the underlying structure determination and as an input to the GW calculations. Then, GW calculations were carried out at the full-frequency spectrum-self-consistent level. All calculations were performed with the projector augmented wave (PAW) method as it is implemented in VASP. The specific semiconductors considered were GaN and ZnO. The first problem was caused by improper handling of the U parameter when initializing the follow-up GW calculations, leading to a final calculated band gap for GaN and ZnO that was too large. Second, we used an older set of pseudopotentials for the PAW method. In a paper that was published while our original manuscript was under review, the impact of the completeness of the partial waves representing empty states in the PAW method was analyzed, showing significant issues with the convergence of the GW results for certain materials, particularly ZnO. Specifically, those issues included use of PAW pseudopotentials that deviate too much from norm conservation, an unduly restricted basis set size that constrains the number of empty states available, and use of a small cutoff for the dielectric matrix size that can result in a false convergence with respect to the number of empty states included. Our GW calculations for GaN and ZnO were affected by these problems.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Transmission Interface Limits for High-Spatial Resolution Capacity Expansion Modeling

Large-scale capacity expansion models typically rely on estimates of the power transfer limits between modeled zones. Accurate estimation of these interface transfer limits (ITLs) requires modeling the underlying transmission network. Here we expand on a maximum flow optimization method that uses linearized power flow to estimate transfer limits. We apply this method to a data set of the U.S. transmission network to estimate ITLs between U.S. counties. By calculating ITLs using different subsets of the network, we evaluate how the size of the network used in the estimation affects the results. The results show diminishing returns to ITL accuracy after six hops, suggesting that a network subset can reasonably be used to approximate ITLs. The county-level estimates produced in this study will support more spatially resolved capacity expansion modeling and will help inform policy making at local and national levels.

capacity planning↗

DOE OSTI2021

A Bilevel Voltage Regulation Operation for Distribution Systems With Self-Operated Microgrids

The emerging of microgrids in distribution systems has significantly enhanced the resilience of power grids. However, the operators of a distribution system and microgrids therein can be different and have accessibility to different devices. To model the operation of such a grid, this work proposes a bilevel formulation and probes into the voltage regulation operation, considering the interaction between different systems. The proposed bilevel formulation considers the cooperation of active energy resources (AER), transformer tap-changers, and capacitor banks that are controlled by different operators. To facilitate the solution time of the target bilevel optimization, the lower-level problems with different objectives are modeled using deep neural networks (DNNs) which are then converted into a set of constraints. Hence, the bilevel problem can be reformed to a single-level problem. Lastly, the proposed solution procedures are validated using a customized joint system constructed by the IEEE 123-bus system and a real distribution system in Iowa. According to the numerical validation results, the solution time of the proposed nonlinear activation function based DNN model is 69 times faster than other methods in solving voltage regulation with a bilevel structure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Data‐driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates

Summary Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well‐studied major crops. Using 727 maize ( Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre‐ and postanthesis maximum temperature, mid‐season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well‐studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Kusmec, Aaron↗

DOE OSTI2015

Algorithms for propagating uncertainty across heterogeneous domains

We address an important research area in stochastic multi-scale modeling, namely the propagation of uncertainty across heterogeneous domains characterized by partially correlated processes with vastly different correlation lengths. This class of problems arise very often when computing stochastic PDEs and particle models with stochastic/stochastic domain interaction but also with stochastic/deterministic coupling. The domains may be fully embedded, adjacent or partially overlapping. The fundamental open question we address is the construction of proper transmission boundary conditions that preserve global statistical properties of the solution across different subdomains. Often, the codes that model different parts of the domains are black-box and hence a domain decomposition technique is required. No rigorous theory or even effective empirical algorithms have yet been developed for this purpose, although interfaces defined in terms of functionals of random fields (e.g., multi-point cumulants) can overcome the computationally prohibitive problem of preserving sample-path continuity across domains. The key idea of the different methods we propose relies on combining local reduced-order representations of random fields with multi-level domain decomposition. Specifically, we propose two new algorithms: The first one enforces the continuity of the conditional mean and variance of the solution across adjacent subdomains by using Schwarz iterations. The second algorithm is based on PDE-constrained multi-objective optimization, and it allows us to set more general interface conditions. The effectiveness of these new algorithms is demonstrated in numerical examples involving elliptic problems with random diffusion coefficients, stochastically advected scalar fields, and nonlinear advection-reaction problems with random reaction rates.

Cho, Heyrim↗

DOE OSTI2023

Study on Electrostatic Separation of Quinoline Insolubles from Coal Tar Pitch

The feasibility of electrical separation in the removal of quinoline insoluble (QI) particles from coal tar pitch (CTP) was experimentally investigated. QI particle involvement prohibits the effective fabrication of high-quality value-added products, such as carbon fibers, from CTP. A substantial and sustainable CTP market exists around the world; therefore, a strong incentive exists to develop a viable technical approach to effectively and economically remove QI particles from CTP. The electrical separation method shows promise to achieve this technical goal (Cao et al., 2012). Even with the given setup (wire- cylinder adapted), critical issues remain to be addressed for this method to be applicable to the CTP: (1) identifying the wash oil used in the original QI separation, (2) understanding the mechanism of QI separation, (3) characterizing the deposit, and (4) identifying the QI. This study integrated a set of experimental and analysis techniques into the electrical separation tests to address the aforementioned issues. Key findings are as follows: 1. Electric current responses: • The electric current level of the CTP–wash oil solution reported by Cao et al. (2012) can be attained by using a mixture of 25% quinoline and 75% toluene for the CTPs examined in this study under the same electrical load condition. • The electric current tends to decrease during the test period because of the decreasing number of charged particles. • The reversed field corresponded to the configuration of electrostatic precipitation for positive corona discharge. The high electric field can result in dielectric breakdown and lead to an abrupt current surge. 2 Deposit response and solvent candidates: • Deposit of particles in CTP mixture can be effectively implemented in a wire-cylinder configuration as proposed and examined in this study. • Deposit depends on the solvents. Among the solvents tested, two- and three-part solvents that included quinoline and ethanol (i.e., 25% quinoline and 75% toluene; 50% quinoline and 50% toluene; and 33% wash oil, 33% BTX, and 34% ethanol) produced the highest deposit weight. • The deposit process examined in this study is derived from the charged particles. An appreciable relation exists between deposit weight and electric charge. 3. QI removal efficiency (RE): • The RE of the electrostatic separation can reach as high as 76.2% for Carbores, and 61.6% for Koppers. • The RE can be further enhanced if the field level increases from 0.16 kV/mm that was used in the current study to 0.23 kV/mm, according to the relation established between the RE and the electric field. 4. Testing of the modeling system: • The motion of particles is originally driven by the charge-based electric force in the cases tested. The solid particle separation mechanism is similar to that of QI deposition in CTP. • The mechanical movement of solid particles can be strongly affected by the gravitational and viscous forces in the electric field. 5. EDS analysis and chemical compositions: • The main chemical composition of deposit QI matches that of as-prepared CTP QI. The deposit QI is derived from the same group of the CTP QI. • In addition to carbon, the QI contains oxygen, sodium, aluminum, silicon, iron, and sulfur. The work for the near future is also discussed.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2016

Adsorption Modeling at the Front and Back Ends of the Nuclear Fuel Cycle

Adsorption is a diverse and complex physicochemical process that has many different applications in chemical, environmental, and nuclear sciences. For example, adsorption can be found at both the front and back ends of the nuclear fuel cycle for (i) capturing uranium from seawater to use as a new source of nuclear fuel and (ii) treatment of the off-gases produced when reprocessing used nuclear fuel. Accurate modeling of these processes is important for the design of efficient capture, recovery, and removal systems for the particular aqueous or gaseous species of interest. A set of algorithms and methods designed for flexibility and portability will greatly improve the ability to rigorously model such a complex set of systems. This approach allows more specific models to be built upon the more generic methods, which gives the overall modeling effort larger breadth and greater usability. Due to the complexity of adsorption processes, it is necessary to develop relatively complex mechanistic models to accurately predict the behavior of engineered adsorption systems. Capture and recovery systems designed for nuclear energy need to have a high level of accuracy to reduce uncertainties and aid in the implementation of separations technologies for efficient nuclear energy systems. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Transmission Interface Limits for High-Spatial Resolution Capacity Expansion Modeling

capacity planning↗

DOE OSTI2022

Multi-Pressure Rail System Design with Variable Pressure Control Strategy

This paper presents the design and the control method of a Multiple Pressure Rail system (MPR) with a variable pressure control logic that allows minimization of throttling loss, therefore, increasing the overall fluid power actuation efficiency. An MPR system allows controlling hydraulic actuators with a pressure control logic, as opposed to traditional flow control logics which are well established in mobile applications. A proper setting of the number of pressure rails and the pressure level in each rail permits optimizing the system efficiency of an MPR solution. MPR systems have been recently proposed with different purposes, but seldom adopt variable pressure control strategies to manage the pressure variations in the rails. Moreover, the related past work attempts to maximize the energy recovery during overrunning load conditions. This paper, instead, addresses the case of an MPR system that handles a multitude of hydraulic functions without significant overrunning loads, as it occurs in many mobile applications such as in agriculture. The paper first presents the design alternatives considered for the MPR system, including the supply, the control valves, and the controller. Second, a dedicated test rig is developed to support experimental activities and validations of a lumped parameter model developed within this research to develop the MPR control strategy. The results describe the operating features of the proposed MPR solution. By considering the case of a traditional LS system, the paper results also show how system efficiency can be highly improved, with energy savings in the order of 49%

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Integrating Multi-Source Data for Bi-Level Traffic Simulator Calibration: A Literature Review and Highway Case Study

Traffic simulation serves as a powerful tool for pre-evaluating policies and technologies. In this context, simulation-based Dynamic traffic assignment (DTA) models are capable of capturing traffic dynamics. They are well-known as critical tools in controlling and predicting traffic situations. The reliability of simulation results heavily depends on the calibration process. Most studies in the literature formulate and calibrate simulators based on a single source of collected data or multiple data sets with the same spatiotemporal characteristics. However, in practice, traffic data is collected by various tools with usually different spatial and temporal resolutions. This study introduces a novel approach to taking into account diverse input data from a variety of sources. An iterative bi-level solution is proposed. to equally treat traffic flow and speed data. The upper level solves flow calibration with the exact solution method, and the lower level calibrates the speed with the simultaneous perturbation stochastic approximation (SPSA) algorithm. Subsequently, the effectiveness of the proposed model is investigated using data from a six-mile section of Nashville's I-24 highway in Tennessee. The results demonstrate that our proposed model creates an effective feedback loop between the optimizer and the simulator for calibrating flow and speed to reduce the error between simulated and real data.

42 ENGINEERING↗

DOE OSTI2021

A Short-Term Solar Forecasting Platform Using a Physics-Based Smart Persistence Model and Data Imputation Method

Electrical energy plays vital role in our socio-economic activity and therefore ensuring the reliability of the electric grid, from the generation, transmission and distribution level is critical. In order to maintain the power system parameter viz., frequency, voltage, etc., optimally, balancing of generation and consumption is very much essential. However, solar energy is infirm power by nature this is due to cloud cover / other local phenomena. Hence, Photovoltaic (PV) power generation brings a significant challenge to the grid operator due to the variability of the solar energy. The complexity of this challenge in terms of planning and dispatch ability of PV resources, aggravates with the high penetration of solar energy into the electric grid. In this setting, reliable solar radiation forecasting models based on accurate and quality input data become essential. In order to develop a suitable model for predicting solar radiation, quality historical / real time measurement is also needed. Under this study NIWE and NREL jointly developed / tested short-term solar forecasting frameworks using a smart persistence and physics-based smart persistence models for intra-hour forecasting of solar radiation (PSPI) and benchmarked 9 different data imputation techniques in 15 Solar Radiation Resource Assessment (SRRA) stations, located at different parts of India. During any measurement campaign, due to various technical reasons, we may miss few observations. However, the missing observation often reduce the performance of any forecasting model. Therefore, suitable data imputation method would assist us to obtain continuous observation of solar radiation. A station-by-station and method-by-method analysis was carried out to understand the performance of each model. Based on our analysis, among all the data imputation methods, the Kalman data imputation method is better for Indian Weather condition. In addition, Kalman StructTS, Linear, Stine and Arima methods yield slightly inferior accuracy compared to Kalman, but outperform the other methods. The extended solar radiation data are used by solar forecasting models to provide the prediction of solar radiation at 15 SRRA stations. As far as short term forecasting model is concerned, the PSPI model outperforms the Smart Persistence model. However, the forecast error is increases with the forecasting horizon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2015

SU-E-J-114: A Practical Hybrid Method for Improving the Quality of CT-CBCT Deformable Image Registration for Head and Neck Radiotherapy

Purpose: Accurate deformable image registration (DIR) between CT and CBCT in H&N is challenging. In this study, we propose a practical hybrid method that uses not only the pixel intensities but also organ physical properties, structure volume of interest (VOI), and interactive local registrations. Methods: Five oropharyngeal cancer patients were selected retrospectively. For each patient, the planning CT was registered to the last fraction CBCT, where the anatomy difference was largest. A three step registration strategy was tested; Step1) DIR using pixel intensity only, Step2) DIR with additional use of structure VOI and rigidity penalty, and Step3) interactive local correction. For Step1, a public-domain open-source DIR algorithm was used (cubic B-spline, mutual information, steepest gradient optimization, and 4-level multi-resolution). For Step2, rigidity penalty was applied on bony anatomies and brain, and a structure VOI was used to handle the body truncation such as the shoulder cut-off on CBCT. Finally, in Step3, the registrations were reviewed on our in-house developed software and the erroneous areas were corrected via a local registration using level-set motion algorithm. Results: After Step1, there were considerable amount of registration errors in soft tissues and unrealistic stretching in the posterior to the neck and near the shoulder due to body truncation. The brain was also found deformed to a measurable extent near the superior border of CBCT. Such errors could be effectively removed by using a structure VOI and rigidity penalty. The rest of the local soft tissue error could be corrected using the interactive software tool. The estimated interactive correction time was approximately 5 minutes. Conclusion: The DIR using only the image pixel intensity was vulnerable to noise and body truncation. A corrective action was inevitable to achieve good quality of registrations. We found the proposed three-step hybrid method efficient and practical for CT/CBCT registrations in H&N. My department receives grant support from Industrial partners: (a) Varian Medical Systems, Palo Alto, CA, and (b) Philips HealthCare, Best, Netherlands.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Multivariate moment closure techniques for stochastic kinetic models

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

OzDES reverberation mapping program: Lag recovery reliability for 6-yr C iv analysis

ABSTRACT We present the statistical methods that have been developed to analyse the OzDES reverberation mapping sample. To perform this statistical analysis we have created a suite of customizable simulations that mimic the characteristics of each source in the OzDES sample. These characteristics include: the variability in the photometric and spectroscopic light curves, the measurement uncertainties, and the observational cadence. By simulating the sources in the OzDES sample that contain the C iv emission line, we developed a set of criteria that rank the reliability of a recovered time-lag depending on the agreement between different recovery methods, the magnitude of the uncertainties, and the rate at which false positives were found in the simulations. These criteria were applied to simulated light curves and these results used to estimate the quality of the resulting Radius–Luminosity relation. We grade the results using three quality levels (gold, silver, and bronze). The input slope of the R–L relation was recovered within 1σ for each of the three quality samples, with the gold standard having the lowest dispersion with a recovered a R–L relation slope of 0.454 ± 0.016 with an input slope of 0.47. Future work will apply these methods to the entire OzDES sample of 771 AGN.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

The impact of tomographic redshift bin width errors on cosmological probes

ABSTRACT Systematic errors in the galaxy redshift distribution n(z) can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy–galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter S8 ≡ σ8(Ωm/.3)1/2 decreases from $0.841^{+0.062}_{-0.061}$ to $0.781^{0.061}_{0.054}$ upon correcting the n(z) errors in the second method.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

Multienergy CT acquisition and reconstruction with a stepped tube potential scan

Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT can be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed SegMECT can provide both attenuation images and material decomposition images of reasonable image quality. Compared to existing methods, the new system configuration demonstrates advantages in simplicity of implementation, system cost, and dose control. Conclusions: This proposed SegMECT imaging approach has great potential for practical applications. It can be readily realized on a conventional CT system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗