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DOE OSTI2023

Granger Causality for prediction in Dynamic Mode Decomposition: Application to power systems

Here, the dynamic mode decomposition (DMD) technique extracts the dominant modes characterizing the innate dynamical behavior of the system within the measurement data. For appropriate identification of dominant modes from the measurement data, the DMD algorithm necessitates ensuring the quality of the input measurement data sequences. On that account, for validating the usability of the dataset for the DMD algorithm, the paper proposed two conditions: Persistence of excitation (PE) and the Granger Causality Test (GCT). The virtual data sequences are designed with the hankel matrix representation such that the dimensions of the subspace spanning the essential system modes are increased with the addition of new state variables. The PE condition provides the lower bound for the trajectory length, and the GCT provides the order of the model. Satisfying the PE condition enables estimating an approximate linear model, but the predictability with the identified model is only assured with the temporal causation among data searched with GCT. The proposed methodology is validated with the application for coherency identification (CI) in a multi-machine power system (MMPS), an essential phenomenon in transient stability analysis. The significance of PE condition and GCT is demonstrated through various case studies implemented on 22 bus six generator system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Robust verification of stochastic simulation codes

We introduce a robust verification tool for computational codes, which we call Stochastic Robust Extrapolation based Error Quantification (StREEQ). Unlike the prevalent Grid Convergence Index (GCI) [1] method, our approach is suitable for both stochastic and deterministic computational codes and is generalizable to any number of discretization variables. Building on ideas introduced in the Robust Verification [2] approach, we estimate the converged solution and orders of convergence with uncertainty using multiple fits of a discretization error model. In contrast to Robust Verification, we perform these fits to many bootstrap samples yielding a larger set of predictions with smoother statistics. Here, bootstrap resampling is performed on the lack-of-fit errors for deterministic code responses, and directly on the noisy data set for stochastic responses. This approach lends a degree of robustness to the overall results, capable of yielding precise verification results for sufficiently resolved data sets, and appropriately expanding the uncertainty when the data set does not support a precise result. For stochastic responses, a credibility assessment is also performed to give the analyst an indication of the trustworthiness of the results. Furthermore, this approach is suitable for both code and solution verification, and is particularly useful for solution verification of high-consequence simulations..

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Sylvester-preconditioned adaptive-rank implicit time integrators for advection-diffusion equations with variable coefficients

Here, we consider the adaptive-rank integration of multi-dimensional time-dependent advection-diffusion partial differential equations (PDEs) with variable coefficients. We employ a standard finite-difference method for spatial discretization coupled with high-order diagonally implicit Runge-Kutta temporal schemes. The discrete equation is a generalized Sylvester equation (GSE), which we solve with a projection-based adaptive-rank algorithm structured around two key strategies: (i) constructing dimension-wise subspaces using a novel atypical extended Krylov strategy, and (ii) efficiently solving the basis coefficient matrix with a preconditioned GMRES solver. The low-rank decomposition is performed in 2D using SVD and with high-order SVD (HOSVD) in 3D to represent the tensor in a compressed Tucker format. For d-dimensional problems (here, d = 2 or 3), the computational complexity and memory storage of the approach are found numerically to scale as and $\mathscr{O}(Nr^2) + \mathscr{O} (r^{d+1})$ and $\mathscr{O}(Nr) + \mathscr{O} (r^{d})$, respectively, with the one-dimensional resolution and the maximal rank during the Krylov iteration (which we find to be largely independent of on our numerical examples). We present numerical examples that illustrate the advertised properties of the algorithm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Predicting environmental mitigation requirements for hydropower projects through the integration of biophysical and socio-political geographies

Uncertainty about environmental mitigation needs at existing and proposed hydropower projects makes it difficult for stakeholders to minimize environmental impacts. Hydropower developers and operators desire tools to better anticipate mitigation requirements, while natural resource managers and regulators need tools to evaluate different mitigation scenarios and order effective mitigation. Here we sought to examine the feasibility of using a suite of multidisciplinary explanatory variables within a spatially explicit modeling framework to fit predictive models for future environmental mitigation requirements at hydropower projects across the conterminous U.S. Using a database comprised of mitigation requirements from more than 300 hydropower project licenses, we were able to successfully fit models for nearly 50 types of environmental mitigation and to apply the predictive models to a set of more than 500 non-powered dams identified as having hydropower potential. The results demonstrate that mitigation requirements have been a result of a range of factors, from biological and hydrological to political and cultural. Furthermore, project developers can use these models to inform cost projections and design considerations, while regulators can use the models to more quickly identify likely environmental issues and potential solutions, hopefully resulting in more timely and more effective decisions on environmental mitigation.

13 HYDRO ENERGY↗

DOE OSTI2013

Assessment of health-care waste disposal methods using a VIKOR-based fuzzy multi-criteria decision making method

Highlights: • Propose a VIKOR-based fuzzy MCDM technique for evaluating HCW disposal methods. • Linguistic variables are used to assess the ratings and weights for the criteria. • The OWA operator is utilized to aggregate individual opinions of decision makers. • A case study is given to illustrate the procedure of the proposed framework. - Abstract: Nowadays selection of the appropriate treatment method in health-care waste (HCW) management has become a challenge task for the municipal authorities especially in developing countries. Assessment of HCW disposal alternatives can be regarded as a complicated multi-criteria decision making (MCDM) problem which requires consideration of multiple alternative solutions and conflicting tangible and intangible criteria. The objective of this paper is to present a new MCDM technique based on fuzzy set theory and VIKOR method for evaluating HCW disposal methods. Linguistic variables are used by decision makers to assess the ratings and weights for the established criteria. The ordered weighted averaging (OWA) operator is utilized to aggregate individual opinions of decision makers into a group assessment. The computational procedure of the proposed framework is illustrated through a case study in Shanghai, one of the largest cities of China. The HCW treatment alternatives considered in this study include “incineration”, “steam sterilization”, “microwave” and “landfill”. The results obtained using the proposed approach are analyzed in a comparative way.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Mixed-Valent Copper Chalcogenides: Tuning Structures and Electronic Properties Using Multiple Anions

A series of mixed-anion copper chalcogenides have been prepared using solid-state methods including ACu 4.2 TeS 2 (A = K, Rb, Cs), which adopt the KCu 4 S 3 structure type. The mixedanion motif has an expanded sublattice, relative to KCu 4 S 3 , that can accommodate additional Cu atoms at its interstitial sites that are unoccupied in the parent structure. The variable temperature transport shows that the materials are p-type metals with carrier densities on the order of 10 21 cm -3 and room-temperature electrical conductivity as high as 4000 S cm -1 . Band structures calculated using density functional theory corroborate the experimental data and indicate that the interstitial Cu atoms lower the carrier concentration and increase the Fermi level of the materials. The layered structure has Te and S atoms occupying unique sites within the ACu 4.2 TeS 2 structure, where relatively hard S 2- anions prefer Wyckoff positions where they can form energetically favorable acid-base interactions with hard alkali cations. The phenomenon is observed in the related K 3 Cu 8 Te 2 S 4 system, which also has a fully ordered layered structure. Here, we believe that the report provides new chemical guidelines for targeting ordered multianion structures, as well as a unique method for tuning the electronic properties of metallic chalcogenides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Mechanistic Insights into C–H Borylation of Arenes with Organoiridium Catalysts Embedded in a Microporous Metal–Organic Framework

Organometallic iridium catalysts can be used in conjunction with bispinacolatodiboron (B 2 Pin 2 ) to effect the borylation of a variety of substrates such as arenes, alkanes, heteroarenes, and oxygenates. Recently, efforts have also focused on integrating these catalysts into porous supports, such as metal–organic frameworks (MOFs). While the mechanism of homogeneous borylation systems has been thoroughly investigated experimentally and computationally, analogous studies in MOF-supported iridium catalysts have not been conducted. In this paper, we report the mechanistic investigation of a phenanthroline-iridium catalyst immobilized in the organic linker of Universitetet i Oslo (UiO)-67 (Zr 6 O 4 (OH) 4 (BPDC) 4 (PhenDC) 2 , BPDC = biphenyl-4,4'-dicarboxylate, PhenDC = 1,10-phenanthroline-4,4'-dicarboxylate). By using benzene as a model substrate, variable time normalization analysis (VTNA) of the kinetic data suggested a rate law consistent with zero-order in B 2 Pin 2 , and first-order in arene. A primary kinetic isotope effect (KIE) in the time course of benzene-d 6 borylation also provided complementary information about the role of the arene in the rate-determining step of the reaction. Characterization by techniques such as X-ray absorption spectroscopy (XAS) confirmed the presence of Ir(III), while pair distribution function (PDF) analysis suggested structures containing an Ir–Cl bond, further substantiated by X-ray photoelectron spectroscopy (XPS). Analysis of postcatalysis materials by inductively coupled plasma–optical emission spectroscopy (ICP-OES) revealed low boron accumulation, which may indicate an absence of boron in the resting state of the catalyst. Finally, in comparing borylation of benzene and toluene, a slight selectivity for benzene is observed, which is similar to the analogous homogeneous reaction, indicating the influence of substrate sterics on reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework

In the process of calibrating distributed hydrological models, accounting for input uncertainty is important, yet challenging. In this study, we develop a Bayesian model to estimate parameters associated with a geomorphology‐based hydrological model (GBHM). The GBHM model uses geomorphic characteristics to simplify model structure and physically based methods to represent hydrological processes. We divide the observed discharge into low‐ and high‐flow data, and use the first‐order autoregressive model to describe their temporal dependence. We consider relative errors in rainfall as spatially distributed variables and estimate them jointly with the GBHM parameters. The joint posterior probability distribution is explored using Markov chain Monte Carlo methods, which include Metropolis‐Hastings, delay rejection adaptive Metropolis, and Gibbs sampling methods. We evaluate the Bayesian model using both synthetic and field data sets. The synthetic case study demonstrates that the developed method generally is effective in calibrating GBHM parameters and in estimating their associated uncertainty. The calibration ignoring input errors has lower accuracy and lower reliability compared to the calibration that includes estimation of the input errors, especially under model structure uncertainty. The field case study shows that calibration of GBHM parameters under complex field conditions remains a challenge. Although jointly estimating input errors and GBHM parameters improves the continuous ranked probability score and the consistency of the predictive distribution with the observed data, the improvement is incremental. To better calibrate parameters in a distributed model, such as GBHM here, we need to develop a more complex model and incorporate much more information.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Improved inertial confinement fusion gamma reaction history 12 C gamma-ray signal by direct subtraction

The Gamma Reaction History Diagnostic (GRH) located at the National Ignition Facility (NIF) measures time resolved gamma rays released from inertial confinement fusion experiments by converting emitted gamma rays into Cherenkov light. Imploded capsules have a bright 4.4 MeV gamma ray from fusion neutrons inelastically scattering with carbon atoms in the remaining ablator. The strength of 4.4 MeV gamma ray line is proportional to the capsule’s carbon ablator areal density and can be used to understand the dynamics and energy budget of a carbon-based ablator capsule implosion. Historically, the GRH’s four gas cells use the energy thresholding from the Cherenkov process to forward fit an estimation of the experiment’s complete gamma ray spectrum by modeling the surrounding environment in order to estimate the 4.4 MeV neutron induced carbon gamma ray signal. However, the high number of variables, local minima and uncertainties in detector sensitivities and relative timing had prevented routine use of the forward fit to generate carbon areal density measurements. A new, more straightforward, process of direct subtraction of deconvolved signals was developed to simplify the extraction of the carbon areal density. Beryllium capsules are used as a calibration to measure a capsule environment with no carbon signal. This is then used to appropriately subtract and isolate the carbon signal on shots with carbon ablators. The subtraction algorithm achieves good results across all major capsule campaigns, achieving similar results to the forward fit. This method is now used routinely to measure carbon areal density for NIF shots.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

To TDE or not to TDE: the luminous transient ASASSN-18jd with TDE-like and AGN-like qualities

ABSTRACT We present the discovery of ASASSN-18jd (AT 2018bcb), a luminous optical/ultraviolet(UV)/X-ray transient located in the nucleus of the galaxy 2MASX J22434289–1659083 at z = 0.1192. Over the year after discovery, Swift UltraViolet and Optical Telescope (UVOT) photometry shows the UV spectral energy distribution of the transient to be well modelled by a slowly shrinking blackbody with temperature $T \sim 2.5 \times 10^{4} \, {\rm K}$, a maximum observed luminosity of $L_{\rm max} = 4.5^{+0.6}_{-0.3}\times 10^{44} \, {\rm erg \,s}^{-1}$, and a radiated energy of $E = 9.6^{+1.1}_{-0.6} \times 10^{51} \, {\rm erg}$. X-ray data from Swift X-Ray Telescope (XRT) and XMM–Newton show a transient, variable X-ray flux with blackbody and power-law components that fade by nearly an order of magnitude over the following year. Optical spectra show strong, roughly constant broad Balmer emission and transient features attributable to He ii, N iii–v, O iii, and coronal Fe. While ASASSN-18jd shares similarities with tidal disruption events (TDEs), it is also similar to the newly discovered nuclear transients seen in quiescent galaxies and faint active galactic nuclei (AGNs).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

ORGANIC RANKINE CYCLE TURBINE AND HEAT EXCHANGER SIZING FOR LIQUID AIR COMBINED CYCLE

Cryogenic energy storage offers several opportunities to design turbomachinery and other equipment for novel cycles. This paper presents the design and analysis of turbomachinery and heat exchangers for an Organic Rankine Cycle (ORC) subsystem for a hybrid energy storage concept. The Liquid Air Combined Cycle is an energy storage system that stores air at cryogenic conditions at times with high variable renewable energy to be dispatched along with a gas turbine to recover the exhaust heat. In order to re-vaporize the air, the liquid air is coupled with an ORC as an additional bottoming cycle. The ORC turbine is expected to expand the fluid with a pressure ratio of nearly 30 and a flow rate of approximately 45 kg/s. Sizing calculations for both a radial and axial turbine solution were performed over a range of speeds and stages to determine the optimal design point. The results show that either an axial (8- or 9-stage) or radial (four stages at two shaft speeds) turbine are capable of handling the pressure ratios. Further trades of the two configurations would be required to determine the best option. The ORC system also incorporates five heat exchangers to distribute heat, vaporize the liquid air, or recover exhaust heat from the gas turbine. Three heat exchangers were analyzed to understand the size of heat exchangers and pressure drop for the overall system. Different types of heat exchangers were explored for the different purposes, including plate-fin heat exchangers, gasketed plate heat exchangers and shell-in-tube heat exchangers. It was determined that the ORC recuperator, liquid-air vaporizer, and vaporized air pre-heater would be counter-flow heat exchangers using a gasketed plate design. Keywords: Energy Storage, Liquid Air Energy Storage, Organic Rankine Cycle

Pryor, Owen↗

DOE OSTI2014

Nalu

Nalu is a Sierra ToolKit (STK) based application module, and it has provided a set of "lessons learned" for the STK transition effort through its early adoption of STK. It makes use of the open-sourced Trilinos/ Tpetra library. Through the investment of LORD and ASCR projects, the Nalu code module has been extended beyond prototype status. Physics capability includes low Mach, variable density turbulent flow. The ongoing objective for Nalu is to facilitate partnerships with external organizations in order to extend code capability and knowledge; however, it is not intended to support routine CFD analysis. The targeted usage of this module is for non-NW applications that support work-for-others in the multiphysics energy sector.

Source record↗

DOE OSTI2022

Radiosonde Intercomparison and Validation (RIVAL) Field Campaign Report

Radiosondes provide the primary source of high-vertical-resolution temperature, humidity, and pressure data from the surface through to the lower stratosphere, and are a key component of the sustained measurement program at U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility observatories. At the end of 2017 the radiosonde manufacturer Vaisala ceased sales and production of the RS92 radiosondes, which were in use at the ARM field sites since 2005, and transitioned to the RS41 model. The Radiosonde Intercomparison and Validation (RIVAL) field campaign was proposed in order to undertake a sustained intercomparison and validation campaign at the Eastern North Atlantic (ENA), North Slope of Alaska (NSA) at Barrow, and Southern Great Plains (SGP) observatories in order to fully quantify the RS92-RS41 sonde differences and their dependence on all relevant influencing variables, and to understand the effects of the sonde model transition.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Isoprene emissions over Asia 1979–2012: impact of climate and land-use changes

Due to the scarcity of observational constraints and the rapidly changing environment in East and Southeast Asia, isoprene emissions predicted by models are expected to bear substantial uncertainties. The aim of this study is to improve upon the existing bottom-up estimates, and to investigate the temporal evolution of the fluxes in Asia over 1979–2012. To this purpose, we calculate the hourly emissions at 0.5°×0.5° resolution using the MEGAN–MOHYCAN model driven by ECMWF ERA-Interim climatology. In order to remedy for known biases identified in previous studies, and to improve the simulation of interannual variability and trends in emissions, this study incorporates (i) changes in land use, including the rapid expansion of oil palms, (ii) meteorological variability according to ERA-Interim, (iii) long-term changes in solar radiation (dimming/brightening) constrained by surface network radiation measurements, and (iv) recent experimental evidence that South Asian tropical forests are much weaker isoprene emitters than previously assumed, and on the other hand, that oil palms have a strong isoprene emission capacity. These effects lead to a significant lowering (factor of 2) in the total isoprene fluxes over the studied domain, and to emission reductions reaching a factor of 3.5 in Southeast Asia. The bottom-up annual isoprene emissions for 2005 are estimated at 7.0, 4.8, 8.3, and 2.9 Tg in China, India, Indonesia and Malaysia, respectively. The isoprene flux anomaly over the whole domain and studied period is found to be strongly correlated with the Oceanic Niño Index (r = 0.73), with positive (negative) anomalies related to El Niño (La Niña) years. Changes in temperature and solar radiation are the major drivers of the interannual variability and trends in the emissions, except over semi-arid areas such as northwestern China, Pakistan and Kazakhstan, where soil moisture is by far the main cause of interannual emission changes. In our base simulation, annual positive flux trends of 0.2% and 0.52% throughout the entire period are found in Asia and China, respectively, related to a positive trend in temperature and solar radiation. The impact of oil palm expansion in Indonesia and Malaysia is to enhance the trends over that region, e.g., from 1.17% to 1.5% in 1979–2005 in Malaysia. A negative emission trend is derived in India (-0.4%), owing to the negative trend in solar radiation data associated with the strong dimming effect likely due to increasing aerosol loadings. The bottom-up emissions are compared to field campaign measurements in Borneo and South China and further evaluated against top-down isoprene emission estimates constrained by GOME-2/MetOp-A formaldehyde columns through 2007–2012. The satellite-based estimates appear to support our assumptions, and confirm the lower emission rate in tropical forests of Indonesia and Malaysia. Additional flux measurements are clearly needed to characterize the spatial variability of emission factors better. To conclude, a decreasing trend in the inferred top-down Chinese emissions since 2007 is in line with recorded cooling in China after that year, thus suggesting that the satellite HCHO columns are able to capture climate-induced changes in emissions.

Stavrakou, T.↗

DOE OSTI2014

Nalu

Source record↗

DOE OSTI2018

Single-pass parallel prefix scan with dynamic look back

One embodiment of the present invention performs a parallel prefix scan in a single pass that incorporates variable look-back. A parallel processing unit (PPU) subdivides a list of inputs into sequentially-ordered segments and assigns each segment to a streaming multiprocessor (SM) included in the PPU. Notably, the SMs may operate in parallel. Each SM executes write operations on a segment descriptor that includes the status, aggregate, and inclusive-prefix associated with the assigned segment. Further, each SM may execute read operations on segment descriptors associated with other segments. In operation, each SM may perform reduction operations to determine a segment-wide aggregate, may perform look-back operations across multiple preceding segments to determine an exclusive-prefix, and may perform a scan seeded with the exclusive prefix to generate output data. Advantageously, the PPU performs one read operation per input, thereby reducing the time required to execute the prefix scan relative to prior-art parallel implementations.

Merrill, Duane↗

DOE OSTI2020

Real-Time Distributed Control of Smart Inverters for Network-level Optimization

The limitations of centralized optimization methods in managing electric power distribution systems operations have led to the distributed paradigm of computing and decision-making. Unfortunately, the existing distributed optimization algorithms are limited in their applicability to managing fast varying phenomena such as those resulting from highly variable Distributed Energy Resource (DER) generation patterns. They require a large number of communication rounds (in the order of 10 2 to 10 3 ) among the computing agents to solve one instance of the optimization problem. Related real-time distributed control methods are equally limited in their applications to power distribution systems with fast-changing DER generation; they require hundreds of rounds of communication and thus are slow in tracking the network-level optimal solutions. In this paper, we propose a novel distributed voltage controller that provides a fast-tracking of rapidly varying DER generation profiles while simultaneously converging to network-level optimal solutions within a few communication rounds. The proposed control algorithm leverages the radial topology of the system, which reduces the required communication rounds to reach the network-level optimum solution by order of magnitude. The novelty lies in carefully reducing the electrical network model from the perspective of each distributed controller and enabling appropriate data sharing among upstream and downstream nodes to achieve fast convergence. The simulation results demonstrate the effectiveness of the proposed approach in minimizing the feeder losses while maintaining the node voltage within the pre-specified limits.

voltage control, optimization, reactive power, inv↗

DOE OSTI2020

Strong temporal variability in methane fluxes from natural gas well pad soils

We measured methane and carbon dioxide fluxes at natural gas well pad soils and undisturbed soils in the Rocky Mountain and Gulf Coast regions of the United States, including producing and gas storage wells. We collected both short-term (15 min) and multi-day (between 3 and 8), continuous measurements at 47 well pads and two undisturbed locations. Methane fluxes varied by more than an order of magnitude over periods as short as 30 min (e.g., 19–593 mg m -2 h -1 in one instance), and diurnal and seasonal variability was also significant (e.g., spring-to-fall change from 509 to 14174 mg m -2 h -1 ). We hypothesize that short-term flux variability was caused by pulsed flow of methane during its migration through the subsurface. Barometric pressure and well conditions likely impacted fluxes, but we found only weak evidence for this. Bacterial methanotrophy appeared to impact methane flux magnitude and variability. We injected methane into the subsurface at one well, and we found that, while fluxes of methane and carbon dioxide, and combustible soil gas concentrations, increased in response to the injection, the response was not uniform, and fluxes exhibited high hourly-scale variability, in spite of a constant injection rate. Methane fluxes tended to be higher at well pad soils compared to background soils (often much higher), and fluxes tended to be higher at well pad locations closer to the well head.

03 NATURAL GAS↗