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DOE OSTI2022

A reforecasting-based dynamic reserve estimation for variable renewable generation and demand uncertainty

The installed capacity of renewables-based energy sources has been increasing in traditional power systems. In order to accommodate the increased variability and uncertainty associated with the deeper penetration of renewable sources like solar and wind, adjusted amounts of dynamic reserve are needed. Although probabilistic dynamic reserve estimation methods have been previously developed, most of them consider the uncertainty to be represented by parametric density functions that tend to perform poorly under extreme events and, moreover, neglect uncertainty introduced by the forecasting model itself. Toward addressing these limitations, this work presents, for the first time, a dynamic reserve estimation method for flexibility that incorporates nonparametric density estimation and a machine learning based reforecasting to provide a day-ahead prediction of the mean and spread of uncertainty around the base forecast. The prediction is, in turn, used to estimate the up and down reserve relative to the base forecast. Here, the present method takes various endogenous and exogenous features, including the calendar variables, as input to estimate the day-ahead reserve. Using a combination of reforecasting and dynamic reserve estimation techniques, the method is shown to adjust better to the dynamic nature of reserve requirements providing only what is needed to accommodate the expected deviations. Considering California Independent System Operator (CAISO) solar, wind and load data over an 18 month period, up to 67% reduction in the amount of reserve capacity needed for a one day reserve and reserve penalty for solar uncertainty is demonstrated. Additionally, the risk of reserve insufficiency in meeting the net demand is reduced by 20% with the proposed method.

14 SOLAR ENERGY↗

DOE OSTI2019

Enhanced hydrogen storage by a variable temperature process

We present a simple method of variable temperature process that can potentially enhance the hydrogen storage properties of a large variety of solid state materials. In this approach, hydrogen gas is first introduced at about room temperature, which is followed by a gradual increase to a preset maximum temperature value, T max . Using this approach, we investigated hydrogen absorption properties of vertically aligned arrays of magnesium nanotrees and nanoblades fabricated by glancing angle deposition (GLAD) technique, and conventional Mg thin film. Weight percentage (wt%) storage values were measured by quartz crystal microbalance (QCM). After exposing Mg samples to H 2 at 30 bar and 30 °C, dynamic absorption measurements were conducted as the temperature was increased from 30 °C to maximum values of T max = 100, 200, and 300 °C all within 150 min. QCM measurements revealed that variable temperature method results in significant improvements in hydrogen storage values over the ones obtained by conventional constant temperature process. At a low effective temperature T eff = 165 °C (T max = 300 °C), we achieved storage values of 6.19, 4.76, and 2.79 wt% for Mg nanotrees, nanoblades, and thin film, respectively.

08 HYDROGEN↗

DOE OSTI2023

Learning macroscopic internal variables and history dependence from microscopic models

This paper concerns the study of history dependent phenomena in heterogeneous materials in a two-scale setting where the material is specified at a fine microscopic scale of heterogeneities that is much smaller than the coarse macroscopic scale of application. Here, we specifically study a polycrystalline medium where each grain is governed by crystal plasticity while the solid is subjected to macroscopic dynamic loads. The theory of homogenization allows us to solve the macroscale problem directly with a constitutive relation that is defined implicitly by the solution of the microscale problem. However, the homogenization leads to a highly complex history dependence at the macroscale, one that can be quite different from that at the microscale. In this paper, we examine the use of machine-learning, and especially deep neural networks, to harness data generated by repeatedly solving the finer scale model to: (i) gain insights into the history dependence and the macroscopic internal variables that govern the overall response; and (ii) to create a computationally efficient surrogate of its solution operator, that can directly be used at the coarser scale with no further modeling. We do so by introducing a recurrent neural operator (RNO), and show that: (i) the architecture and the learned internal variables can provide insight into the physics of the macroscopic problem; and (ii) that the RNO can provide multiscale, specifically FE 2 , accuracy at a cost comparable to a conventional empirical constitutive relation.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Characterisation of the spatial variability of material properties of Gilsocarbon and NBG-18 using random fields

Graphite is a candidate material for Generation IV concepts and is used as a moderator in Advanced Gas-cooled Reactors (AGR) in the UK. Spatial material variability is present within billets causing different material property values between different components. Variations in material properties and irradiation effects can produce stress concentrations and diverse mechanical responses in a nuclear reactor graphite core. In order to characterise the material variability, geostatistical techniques called variography and random field theory were adapted for studying the density and Young's modulus of a billet of Gilsocarbon and NBG-18 graphite grades. Variography is a technique for estimating the distance over which material property values have significant spatial correlation, known as the scale of fluctuation or spatial correlation length. The paper uses random field theory to create models that mimic the original spatial and statistical distributions of the original data set. This study found different values of correlation length for density and Young's modulus around the edges of a Gilsocarbon billet, while in the case of NBG-18, similar correlation lengths where found across the billet. Furthermore examples of several random fields are given to reproduce the spatial patterns and values found in the original data.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Effect of heat treatment variables on the formation of precipitate free zones (PFZs) in Mg-8Al-0.5Zn alloy

Highlights: • The effect of heat treatment variables on the development of PFZs in the AZ80 Mg alloy has been systematically examined. • PFZ width is found to be strongly dependant on aging temperature as compared to aging time. • The PFZ width in the AZ80 alloy is found to be weakly dependant on the solution temperature and quenching rate. • The solute depletion is found to be the dominant factor in explaining the evolution of PFZ width. - Abstract: The present study is focussed on investigating the effect of heat treatment variables on the formation of precipitate free zones (PFZs) in the AZ80 Mg alloy. The effect of solutionizing temperature, quenching media, aging temperature and time on the PFZ development has been systematically examined. Scanning electron microscopy and nanoindentation were employed to characterize the PFZ regions. Electron probe micro analysis (EPMA) was used to examine the role of solute depletion in the formation of these zones. Moreover, the estimation of vacancy concentration profiles near the grain boundary was used to investigate the role of vacancy depletion. The solute depletion is found to be the dominant mechanism in the development of PFZ regions as compared to vacancy.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Effect of non-axisymmetric arc on microstructure, texture and properties of variable polarity plasma arc welded 5A06 Al alloy

Highlights: • Variable polarity plasma arc welding of 5A06 Al alloy was carried out under the condition of non-axisymmetric arc. • Deformation bands formed in the weld joint were due to microstructural inhomogeneities. • Tensile fracture occurred along the deformation bands in the TZ/HAZ fusion boundary on the side of “lower arc”. • The weld zones are harder than the BM due to dislocation sub-structure, deformation bands and ultrafine subgrain. - Abstract: Microstructure, texture and mechanical properties in the weld joint of variable polarity plasma arc welding of 5A06 Al alloy under the condition of non-axisymmetric arc have been investigated. The weld joint are characterized by elongated structure in the base material (BM), the heat affected zone (HAZ) and the transition zone (TZ) and equiaxed structure in the fusion zone (FZ). Microstructure of the weld joint is asymmetrical and inhomogeneous leading to deformation bands. Deformation texture and recrystallization texture were developed in the weld zones. The FZ center was dynamic recrystallized due to severe deformation. Materials in the TZ have undergone dynamic recovery. The weld zones are harder than the BM due to dislocation sub-structure, deformation bands and ultrafine subgrains. Microhardness distribution was homogeneous in the regions without deformation bands. Tensile fracture occurred along the deformation bands on the side of “lower arc” exhibiting ductile fracture, while the BM is less ductile.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Ocean circulation and climate variability in the northern South China Sea during the Greek Minimum derived from coral Δ 14 C and Sr/Ca records

Ocean circulation transports heat, salt and nutrients, and has profound impacts on the marine environment and climate change. However, the seasonal to centennial variations of the paleocirculation of the South China Sea (SCS) and their driving forces are still unclear due to limited records. Here we reconstructed a high-resolution Δ 14 C record of a coral from Sanya to investigate the seasonal variations of the SCS ocean circulation around 2300 cal yr BP during a grand solar minimum (GSM) period. The seasonal Δ 14 C variability shows the influence of coastal upwelling caused by the East Asian Summer Monsoon (EASM) in summer and the effect of water intrusion from the western Pacific Ocean driven by the Kuroshio Intrusion (KI) in winter. Here we compiled the marine radiocarbon reservoir correction (ΔR) records since 2500 cal yr BP, which indicate a gradual decrease of upwelling significantly correlated with the EASM. Comparisons with other climate records suggest that both the EASM and KI may regulate the ocean circulation variability on centennial time scales. As a good index of the sea surface temperature (SST), our Sr/Ca record and spectral analysis results show a low temperature and a low frequency of El Niño-Southern Oscillation (ENSO) events around 2300 cal yr BP. Moreover, the composite coral Sr/Ca-SST and ENSO index records since 2500 cal yr BP show relatively low SST and weak ENSO during GSMs, supporting the modulation of tropical SST and ENSO by solar activity. Our study has provided high-resolution proxy data and revealed the driving forces of ocean circulation and climate change in the SCS at multiple time scales, which should be considered in further modeling work.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Multiple independent records of local glacier variability on Nuussuaq, West Greenland, during the Holocene

The sensitivity of mountain glaciers to small-scale climate fluctuations makes records of their past extent among the best proxies for identifying spatio-temporal climate variability. Here we build on the few existing Holocene records of local glacier change in Greenland by using three independent geochronological methods—proglacial lake sediment analysis, cosmogenic 10 Be surface-exposure dating, and in situ 14 C burial modeling—to reconstruct continuous records of Holocene glacier variability on Nuussuaq, West Greenland. 10 Be ages of perched boulders indicate eastern Nuussuaq was deglaciated between ~11.0 and 10.5 ka. Radiocarbon-dated sediments from two lakes on Nuussuaq contain mineral-rich layers between ~9.6 and 9.0 and ~8.7–8.0 cal ka BP that may be correlative with nearby ice sheet moraines deposited in the early Holocene. Multiple proxies for glacier size indicate frequent, high-amplitude glacier fluctuations superimposed on net glacier growth during the late Holocene, with significant ice expansion phases at ~3.7 ka, 2.8 ka, and throughout the past ~2 ka. Mean 10 Be ages from five nested moraine crests confirm that local glacier extents on Nuussuaq culminated during both the Little Ice Age [~1470 C.E. (n=3) and 1750 C.E. (n=3)] and the preceding centuries (~520–1320 C.E.; n=11). Results reveal that local glaciers on Nuussuaq episodically advanced and retreated at centennial timescales throughout the Holocene, most likely in response to regional climate changes in West Greenland superimposed on the progressive insolation-driven cooling trend in the Northern Hemisphere. Our new 10 Be moraine chronologies coupled with other glacier-size proxies corroborate an emerging pattern of significant summer cooling and glacier expansion in the centuries prior to the Little Ice Age in the Arctic.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Hydrodynamics and Load Shedding Behavior of a Variable-Geometry Oscillating Surge Wave Energy Converter (OSWEC)

In order to improve their long-term viability, wave energy converters (WECs) need to be able to shed loads when a threshold wave condition is exceeded. As shown by Tom et al. (2016) [1], provision of adjustable flaps within the body of an oscillating surge wave energy converter (OSWEC) allows wave energy to pass through the device. A control system may then be able to open and close the flaps when waves approaching the device exceed preset thresholds. The variable-geometry OSWEC (VG-OSWEC) concept studied in this paper is a bottom-hinged, rectangular wave paddle with five flaps of elliptical cross-section embedded into the face of the paddle. System ID tests were conducted on this VG-OSWEC device at a 1:14 scale in a wave basin. Free decay tests showed that the damping was distinctly nonlinear when the flaps were fully open, and the natural frequency increased by 40% when compared with the flaps in a fully closed configuration. Tests with regular wave conditions were used to develop the response amplitude operator for the rotational motion about the hinge. These response amplitude operator results when compared with numerical simulations run using WEC-Sim/WAMIT and ANSYS AQWA, show strong agreement with the flap open and closed conditions. The regular-wave condition measurements also show that the wave excitation moment about the hinge was reduced by up to 60% when the flaps were fully open. The experiments serve to demonstrate the potential of the variable geometry design to shed loads and survive harsh ocean environments.

load shedding↗

DOE OSTI2023

Controls and variability of soil respiration temperature sensitivity across China

Understanding the temperature sensitivity (Q 10 ) of soil respiration is critical for benchmarking the potential intensity of regional and global terrestrial soil carbon fluxes-climate feedbacks. Although field observations have demonstrated the strong spatial heterogeneity of Q 10 , a significant knowledge gap still exists regarding to the factors driving spatial and temporal variabilities of Q 10 at regional scales. Here, therefore, we used a machine learning approach to predict Q 10 from 1994 to 2016 with a spatial resolution of 1 km across China from 515 field observations at 5 cm soil depth using climate, soil and vegetation variables. Predicted Q 10 varied from 1.54 to 4.17, with an area-weighted average of 2.52. There was no significant temporal trend for Q 10 (p = 0.32), but annual vegetation production (indicated by normalized difference vegetation index, NDVI) was positively correlated to it (p < 0.01). Spatially, soil organic carbon (SOC) was the most important driving factor in 62 % of the land area across China, and varied greatly, demonstrating soil controls on the spatial pattern of Q 10 . These findings highlighted different environmental controls on the spatial and temporal pattern of soil respiration Q 10 , which should be considered to improve global biogeochemical models used to predict the spatial and temporal patterns of soil carbon fluxes to ongoing climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Numerical study of variable density turbulence interaction with a normal shock wave

Accurate numerical simulations of shock–turbulence interaction (STI) are conducted with a hybrid monotonicity-preserving–compact-finite-difference scheme for a detailed study of STI in variable density flows. Theoretical and numerical assessments of data confirm that all turbulence scales as well as the STI are well captured by the computational method. Linear interaction approximation (LIA) convergence tests conducted with the shock-capturing simulations exhibit a similar trend of converging to LIA predictions to shock-resolving direct numerical simulations (DNS). The effects of density variations on STI are studied by comparing the results corresponding to an upstream multi-fluid mixture with the single-fluid case. Here the results show that for the current parameter ranges, the turbulence amplification by the normal shock wave is much higher and the reduction in turbulence length scales is more significant when strong density variations exist. Turbulent mixing enhancement by the shock is also increased and stronger mixing asymmetry in the postshock region is observed when there is significant density variation. The turbulence structure is strongly modified by the shock wave, with a differential distribution of turbulent statistics in regions having different densities. The dominant mechanisms behind the variable density STI are identified by analysing the transport equations for the Reynolds stresses, vorticity, normalized mass flux and density specific volume covariance.

42 ENGINEERING↗

DOE OSTI2020

Effects of Atwood and Reynolds numbers on the evolution of buoyancy-driven homogeneous variable-density turbulence

The evolution of buoyancy-driven homogeneous variable-density turbulence (HVDT) at Atwood numbers up to 0.75 and large Reynolds numbers is studied by using high-resolution direct numerical simulations. To help understand the highly non-equilibrium nature of buoyancy-driven HVDT, the flow evolution is divided into four different regimes based on the behaviour of turbulent kinetic energy derivatives. The results show that each regime has a unique type of dependence on both Atwood and Reynolds numbers. It is found that the local statistics of the flow based on the flow composition are more sensitive to Atwood and Reynolds numbers compared to those based on the entire flow. It is also observed that, at higher Atwood numbers, different flow features reach their asymptotic Reynolds-number behaviour at different times. The energy spectrum defined based on the Favre fluctuations momentum has less large-scale contamination from viscous effects for variable-density flows with constant properties, compared to other forms used previously. The evolution of the energy spectrum highlights distinct dynamical features of the four flow regimes. Thus, the slope of the energy spectrum at intermediate to large scales evolves from -7/3 to -1 , as a function of the production-to-dissipation ratio. The classical Kolmogorov spectrum emerges at intermediate to high scales at the highest Reynolds numbers examined, after the turbulence starts to decay. Finally, the similarities and differences between buoyancy-driven HVDT and the more conventional stationary turbulence are discussed and new strategies and tools for analysis are proposed.

42 ENGINEERING↗

DOE OSTI2020

Variable-density effects in incompressible non-buoyant shear-driven turbulent mixing layers

The asymmetries that arise when a mixing layer involves two miscible fluids of differing densities are investigated using incompressible (low-speed) direct numerical simulations. The simulations are performed in the temporal configuration with very large domain sizes, to allow the mixing layers to reach prolonged states of fully turbulent self-similar growth. Imposing a mean density variation breaks the mean symmetry relative to the classical single-fluid temporal mixing layer problem. Unlike prior variable-density mixing layer simulations in which the streams are composed of the same fluids with dissimilar thermodynamic properties, the density variations are presently due to compositional differences between the fluid streams, leading to different mixing dynamics. Variable-density (non-Boussinesq) effects introduce strong asymmetries in the flow statistics that can be explained by the strongest turbulence increasingly migrating to the lighter fluid side as free-stream density difference increases. Interface thickness growth rates also reduce, with some thickness definitions particularly sensitive to the corresponding changes in alignment between density and streamwise velocity profiles. Additional asymmetries in the sense of statistical distributions of densities at a given position within the mixing layer reveal that fine scales of turbulence are preferentially sustained in lighter fluid, which also is where fastest mixing occurs. These effects influence statistics involving density fluctuations, which have important implications for mixing and more complicated phenomena that are sensitive to the mixing dynamics, such as combustion.

42 ENGINEERING↗

DOE OSTI2022

Combined Raman and Turbidity Probe for Real-Time Analysis of Variable Turbidity Streams

We know that real-time and in situ process monitoring is a powerful tool that can empower operators of hazardous processes to better understand and control their chemical systems without increased risk to themselves. However, applying monitoring techniques to complex chemical processes can face challenges. An example of this is the application of optical spectroscopy, otherwise capable of providing detailed chemical composition information, to processes exhibiting variable turbidity. Here, details on a novel combined Raman spectroscopy and turbidimetry probe are discussed. Furthermore, the analytical approach to accurately account for both Raman signal and turbidity while quantifying chemical targets is detailed. Through leveraging Raman and turbidity data simultaneously collected from the combined probe within chemometric models, accurate quantification of multiple chemical targets can be achieved under conditions of variable concentrations and turbidity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Individual variability of protein expression in human tissues

Human tissues are known to exhibit inter-individual proteomic variability, but a deeper understanding of the different factors affecting peptide expression is necessary to further apply this knowledge. Our goal was to explore proteomic discrepancies between individuals as well as between healthy and diseased samples, and to test whether heterogeneous data from many different individuals could be used to build a tissue classifier. In order to investigate whether disparate proteomics datasets may be combined to provide meaningful insights, we performed a retrospective analysis of proteomics data from 9 different human tissues. These datasets represent several different sample prep methods, mass spectrometry instruments, and tissue health. Using this data we examined inter-individual and inter-tissue variability in peptide expression, and analyzed the methods required to build accurate tissue classifiers. We also evaluated the limits of tissue classification, and how results may be improved. These tests provided insights about how classification techniques may be applied to situations where less data is available, such as clinical biopsies, laser capture microdissected samples or potentially to classify cells types based on single cell proteomics. Our findings reveal the strong potential for utilizing proteomics data to build robust tissue classifiers, which has many prospective clinical applications.

Kushner, Irena K.↗

DOE OSTI2021

Toward Decoding the Relationship between Domain Structure and Functionality in Ferroelectrics via Hidden Latent Variables

Polarization switching mechanisms in ferroelectric materials are fundamentally linked to local domain structure and the presence of the structural defects, which both can act as nucleation and pinning centers and create local electrostatic and mechanical depolarization fields affecting wall dynamics. However, the general correlative mechanisms between domain structure and polarization dynamics are only weakly explored, precluding insight into the associated physical mechanisms. In this work, the correlation between local domain structures and switching behavior in ferroelectric materials is explored using convolutional encoder–decoder networks, enabling image to spectral (im2spec) and spectral to image (spec2im) translations via encoding of latent variables. The latter reflect the assumption that the relationship between domain structure and polarization switching is parsimonious, i.e., is based upon a small number of local mechanisms. The analysis of latent variables distributions and their real-space representations provides insight into the predictability of the local switching behavior and hence associated physical mechanisms. We further pose that the regions where these correlative relationships are violated, i.e., predictability of the polarization dynamics from domain structure is reduced, represent the obvious target for detailed studies, e.g., in the context of automated experiments. This approach provides a workflow to establish the presence of correlation between local spectral responses and local structure and can be universally applied to spectral imaging techniques such as piezoresponse force microscopy (PFM), scanning tunneling microscopy (STM) and spectroscopy, and electron energy loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM).

36 MATERIALS SCIENCE↗

DOE OSTI2019

Passively Sampled Environmental Films Show Geographic Variability and Host a Variety of Microorganisms

Environmental films are ubiquitous coatings that form on virtually all surfaces exposed to the troposphere. This work analyzes large molecular weight species in native environmental films acquired at three collection sites in the vicinity of Iowa City, Iowa, USA that include an urban residence, a wooded area, and a metropolitan building rooftop. The films are developed for up to twelve months on polished silicon wafer substrates housed in flat-plate passive samplers. Film composition was assessed by Fourier transform ion cyclotron resonance secondary ion mass spectrometry (FTICR-SIMS), and spatially resolved chemical morphology was analyzed via timeof- flight secondary ion mass spectrometry (ToF-SIMS) imaging. Mass analysis spanning up to m/z 2,000 included detection of a variety of organic and inorganic compounds. We characterize MS data with PCA to identify variability between the collection sites and the respective films generated therein, where we detected a variety of organic and biotically generated species consistent with fungal and bacterial microorganisms. Here, the film collection site as well as deposition time contribute to spectral variability, suggesting that geographic location as well as seasonal diversity may affect composition. SIMS analyses were complemented with microscopy and SYBR-Safe staining to highlight biological microorganisms within the films, which include evidence of fungi, protozoa, and bacteria. SIMS imaging also reveals domains concentrated with fragments indicative of proteinaceous macromolecules and microbial biomass, characteristic of biological presence within the film.

42 ENGINEERING↗

DOE OSTI2023

Functional Predictor Variables for the Leaching Potential of Arsenic and Selenium from Coal Fly Ash

The release of leachates from intact coal ash impoundments is a concern due to the enrichment and mobilization of toxic elements such as arsenic (As) and selenium (Se). This study aims to explore the intrinsic properties of coal fly ash that correlate with the relative leachability of As and Se. We performed leaching experiments with 52 fly ash samples collected from 15 different U.S. power plants and representing coal feedstocks from the three major domestic regions. We assessed the mobilization potential of As and Se in fly ash based on standardized leaching protocols and performed multivariate and lasso regression analyses to explore correlations of leachable As and Se contents with characteristics such as major element contents, loss on ignition, and pH. The results of regression models indicated that major elements (Fe, Ca, and Al) for a wide range of fly ashes can serve as predictor variables for the leaching potential of As but not for Se. LOI and pH were not important predictive variables in the models. Both regression approaches resulted in relatively strong fits for leachable As (correlation coefficient R 2 = 0.78 for both models) compared to models for leachable Se (R 2 = 0.49). Overall, these results suggest that correlation models combined with on-site elemental analysis with portable analyzers may enable a screening method for leachable As in coal ash.

01 COAL, LIGNITE, AND PEAT↗