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DOE OSTI2019

Acoustic emission Bayesian source location: Onset time challenge

Robust identification of the most accurate observed input data among a pool of observations is key in modeling and decision making. A statistically biased observed measurement deteriorates the predictive power of a model and affects decision-making ability based on the prediction of the model. When two competing methods of measurement are available, such as methods which identify arrival times in acoustic emission (AE) signals, a principal question is whether one of the two obtained datasets, or a combination of the two, should be used later on, for example, to localize an AE source. This question becomes more important when collecting not repeatable data such as AE signals created by a propagating crack. Here this paper considers an inverse source location problem in a concrete block to address the mentioned issue, a proposed methodology which also has wider application in competitive data selection. Elastic energy released by an AE event, such as a propagating crack, is recorded by acoustic emission data acquisition system. The onset time of AE signals is often used to locate the source of the event, and its accuracy directly affects the precision of source identification. This research proposes an innovative approach to select the most probable onset time obtained from two automatic picker methods. The proposed method selects the most probable onset times, which are observed by each picker for each sensor, in a probabilistic fashion. To validate the proposed method, the most accurate onset time observed by each picker is identified by visual inspection and is compared with the one is selected by the proposed method. Finally, the dataset is used for source location identification. Results show that picked onset times determined by the proposed method generate more accurate source identification when compared with coordinates obtained using each dataset individually.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Molecular dynamics simulations for glass transition temperature predictions of polyhydroxyalkanoate biopolymers

Polyhydroxyalkanoates (PHAs) represent an emerging class of biosynthetic and biodegradable polyesters that exhibit considerable potential to replace petroleum-based plastics towards a sustainable future. Despite the promise, general structure–property mappings within this class of polymers remain largely unexplored. An efficient exploration of this vast chemical space calls for the development and validation of predictive methods for accurate estimation of a diverse range of properties for PHA-based polymers. Towards this aim, we present and validate in this work the results of our molecular dynamics (MD) simulation based approach aimed at predicting glass transition temperatures (T g ) of PHA-based polymers. Since generally available and widely used polymer forcefields exhibit a relatively poor performance for T g predictions, we have developed a new forcefield by modifying the polymer consistent force field (PCFF) via refining a selected set of torsion potentials of the polymer backbone using accurate density functional theory (DFT) computations. After carefully assessing the dependence of critical simulation parameters, such as, polymer chain length, number of polymer chains, supercell size, and thermal quenching rate used in the simulation, the applicability and transferability of the modified PCFF (mPCFF) is demonstrated by directly comparing the computed T g predictions of various polymers with different chemistries, polymer side chain lengths and functional groups forming the polymer side chains against the respective experimentally measured values. Furthermore, the transport properties such as self-diffusion coefficient and viscosity are computationally determined and their well-known correlation with the target properties is demonstrated. Lastly, we have employed the developed approach to predict T g values for a number of yet-to-be-synthesized PHA-based polymers with a diverse set of functional groups in the polymer side chains. The results are further rationalized by correlating the predicted T g values with the inter-chain H-bond formation tendencies of the different side chain functional groups. This work represents an important first step towards computationally guided design of PHA-based functional polymers and opens up new directions for a systematic investigation of composition- and configuration-dependent structure–property relationships in more complex binary and ternary copolymer systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

A Novel Power-Hardware-in-the-Loop Interface Method for Grid-forming Inverter Systems: Preprint

Power Hardware-in-the-Loop (PHIL) simulation of grid-forming (GFM) inverter systems facilitates the testing of drastic scenarios like on-grid to off-grid transition, islanded microgrid operation without stiff grid etc. To the authors best knowledge, most of studies in literature are focused on PHIL simulation for grid-following inverter systems and only few studies are focused on GFM inverters and those are challenging and problematic especially for high-power applications. In this article, a novel PHIL simulation platform is proposed that enables interfacing of high-power GFM inverter systems. It proposes the concept of a virtual GFM inverter as a part of the proposed PHIL interface for GFM inverter. This addition of virtual GFM inverter in the PHIL interface expands the conventional Ideal Transformer Model (ITM) method and enables it to overcome the issues of instability of existing ITM methods. In the validation stage, a PHIL experiment is conducted on a 3-phase 480 V, 125 kVA GFM inverter system with proposed interfacing method. The results corroborates the fact that the proposed PHIL simulation method performs well and stable for GFM inverter system.

grid-forming inverters↗

DOE OSTI2020

Selected Uses of TSUNAMI in Critical Experiment Design and Analysis

Validation in criticality safety is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 and enable investigation of the parameters at which such a critical condition is achieved. For the critical experiments used in a validation to capture the biases of the materials and neutron energy spectra of interest, those materials must be included in the experiment such that they influence k eff or another observable parameter with statistical significance. This paper discusses the use of sensitivity uncertainty (S/U) methods to develop critical experiments for various purposes. S/U techniques are useful for understanding the underlying components of nuclear data which affect the k eff or another parameter of a given configuration. S/U calculations are most commonly used to compare existing experiments to applications of interest; however, S/U techniques can also be used to identify, optimize, or assess features of proposed experiments so that they can better test specific portions of nuclear data or match an application of interest. The S/U techniques discussed here are from the TSUNAMI code system. The two primary codes discussed in this work are TSUNAMI-3D, which implements the KENO criticality code to calculate the sensitivity of k eff to nuclear data, and TSAR, which calculates the sensitivity of a reactivity difference between two configurations based on their TSUNAMI-3D generated sensitivity profiles. The methods used in these tools are discussed in more detail in the SCALE manual. This paper is one of a series on the development and use of TSUNAMI tools. The other papers address development of TSUNAMI methods and a review of TSUNAMI applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Inadequacy of current approaches for characterizing membrane transport properties at high salinities

Cost optimal design of osmotic membrane processes requires an accurate estimate of membrane transport parameters across their full operational range. However, standard approaches for estimating these parameters rely on empirical methods, the accuracy of which remains unquantified as a function of temperature, salinity, and measurement error. Herein, we present a systematic accuracy analysis of previously developed methods for estimation of membrane transport properties in reverse osmosis, high-pressure reverse osmosis, forward osmosis, pressure retarded reverse osmosis, and osmotically assisted reverse osmosis. We use a Monte Carlo approach to sample the full range of feasible membrane water permeabilities, salt permeabilities, structural parameters, and operating conditions for these processes. These material and process parameters are then incorporated into a physical transport model for each process. Our analysis shows that the statistical uncertainty of current empirical methods for estimating membrane parameters increases by 5 times from low-salinity to high-salinity conditions. Here, the result of this work demonstrates that empirical methods are inadequate for precisely estimating membrane transport properties at high salinity and highlight a critical need for the development of statistically validated higher accuracy methods.

42 ENGINEERING↗

DOE OSTI2019

Evaluation of the continuous dilatometer method of silicon carbide thermometry for passive irradiation temperature determination

Silicon carbide (SiC) is a primary candidate for passive irradiation temperature monitoring, and continuous dilatometry (CD) has been proposed as the key method for extracting irradiation temperatures from SiC thermometry samples. The CD method was evaluated to determine the sensitivity of the technique to the analysis procedure, as well as its accuracy and precision. Analysis found that the CD method had a ±20 °C sensitivity to the algorithm used to determine the irradiation temperatures. Comparison of the CD method with the continuous length change method for SiC thermometry showed CD is a more viable method of extracting irradiation temperatures. In conclusion, a comparison of irradiation temperatures determined by CD with those from active thermocouple measurements further validated the CD method for accurately and precisely determining irradiation temperatures in materials test reactor irradiations.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Homonuclear dipolar recoupling of arbitrary pairs in multi-spin systems under magic angle spinning: A double-frequency-selective ZQ-SEASHORE experiment

We introduce a useful method for measuring the internuclear distances within arbitrarily selected pairs of like nuclei in dipolar-coupled multi-spin systems. The approach uses a combination of the zero-quantum shift-evolution-assisted selective homonuclear recoupling (ZQ-SEASHORE) technique developed by Hu and Tycko [ J. Chem. Phys. 2009, 131, 045101] and double-frequency-selective radio-frequency pulse. The double-frequency-selective pulse inverts polarizations of two spins simultaneously, and thus applications of the method presented here are only limited by the spectral resolution, and not by the number of interacting spins. Our experiments demonstrate the validity of the method and present analytical expressions for the dephasing curve.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Direct detection of bacteremia by exploiting host-pathogen interactions of lipoteichoic acid and lipopolysaccharide

Abstract Bacteremia is a leading cause of death in sub-Saharan Africa where childhood mortality rates are the highest in the world. The early diagnosis of bacteremia and initiation of treatment saves lives, especially in high-disease burden areas. However, diagnosing bacteremia is challenging for clinicians, especially in children presenting with co-infections such as malaria and HIV. There is an urgent need for a rapid method for detecting bacteremia in pediatric patients with co-morbidities to inform treatment. In this manuscript, we have developed and clinically validated a novel method for the direct detection of amphiphilic pathogen biomarkers indicative of bacteremia, directly in aqueous blood, by mimicking innate immune recognition. Specifically, we have exploited the interaction of amphiphilic pathogen biomarkers such as lipopolysaccharides (LPS) from Gram-negative bacteria and lipoteichoic acids (LTA) from Gram-positive bacteria with host lipoprotein carriers in blood, in order to develop two tailored assays – lipoprotein capture and membrane insertion – for their direct detection. Our assays demonstrate a sensitivity of detection of 4 ng/mL for LPS and 2 ng/mL for LTA using a waveguide-based optical biosensor platform that was developed at LANL. In this manuscript, we also demonstrate the application of these methods for the detection of LPS in serum from pediatric patients with invasive Salmonella Typhimurium bacteremia (n = 7) and those with Staphylococcal bacteremia (n = 7) with 100% correlation with confirmatory culture. Taken together, these results demonstrate the significance of biochemistry in both our understanding of host-pathogen biology, and development of assay methodology, as well as demonstrate a potential new approach for the rapid, sensitive and accurate diagnosis of bacteremia at the point of need.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

A hybrid finite element-spectral boundary integral approach: Applications to dynamic rupture modeling in unbounded domains

The finite element method (FEM) and the spectral boundary integral method (SBI) have both been widely used in the study of dynamic rupture simulations along a weak interface. Here, we present a hybrid method that combines FEM and SBI through the consistent exchange of displacement and traction boundary conditions, thereby benefiting from the flexibility of FEM in handling problems with nonlinearities or small-scale heterogeneities and from the superior performance and accuracy of SBI. We validate the hybrid method using a benchmark problem from the Southern California Earthquake Center's dynamic rupture simulation validation exercises.We further demonstrate the capability and computational efficiency of the hybrid scheme for resolving off-fault heterogeneities by studying a 2D in-plane shear crack in two different settings: one where the crack is embedded in a high-velocity zone and another where it is embedded in a low-velocity zone. Finally, we discuss the potential of the hybrid method for addressing a wide range of problems in geophysics and engineering.

58 GEOSCIENCES↗

DOE OSTI2024

CMB-PAInT: An inpainting tool for the cosmic microwave background

Abstract The presence of astrophysical emissions in microwave observations forces us to perform component separation to extract the Cosmic Microwave Background (CMB) signal. However, even in the most optimistic cases, there are still strongly contaminated regions, such as the Galactic plane or those with emission from extragalactic point sources, which require the use of a mask. Since many CMB analyses, especially the ones working in harmonic space, need the whole sky map, it is crucial to develop a reliable inpainting algorithm that replaces the values of the excluded pixels by others statistically compatible with the rest of the sky. This is especially important when working withQandUsky maps in order to obtainE- andB-mode maps which are free fromE-to-Bleakage. In this work we study a method based on Gaussian Constrained Realizations (GCR), that can deal with both intensity and polarization. Several tests have been performed to asses the validation of the method, including the study of the one-dimensional probability distribution function (1-PDF),E- andB-mode map reconstruction, and power spectra estimation. We have considered two scenarios for the input simulation: one case with only CMB signal and a second one including also Planck PR4 semi-realistic noise. Even if we are limited to low resolution maps, N side = 64 ifT,QandUare considered, we believe that this is a useful approach to be applied to future missions such as LiteBIRD, where the target are the largest scales.

Astronomy & Astrophysics↗

DOE OSTI2022

Optimal Sizing and Operation of a Hybrid Clean Energy Center

In this paper, we consider the deployment of battery energy storage systems (BESSs) paired with photovoltaics (PV) to form a hybrid clean energy center (HCEC), where the BESS is equipped for two main purposes: i) reducing the volatility of PV output and ii) shifting energy to meet an export limit. We develop a linear dynamical model to characterize the output of an HCEC and express the volatility and export power as functions of the battery's dispatch operations. We also propose an optimal sizing method via second-order cone programming (SOCP) to maximize the net benefits of the HCEC. Numerical studies are performed to illustrate and validate the proposed method.

Battery energy storage systems, photovoltaics, sec↗

DOE OSTI2022

Novel Power-Hardware-in-the-Loop Interface Method for Grid-Forming Inverter Systems

Power-hardware-in-the-loop (PHIL) simulations of grid-forming (GFM) inverter systems facilitate the testing of drastic scenarios, such as on-grid to off-grid transitions and islanded microgrid operations without a stiff grid. To the authors’ best knowledge, most studies in the literature focus on PHIL simulations for grid-following inverter systems. Only a few studies focus on GFM inverters, and those are challenging and problematic, especially for high-power applications. This article proposes a novel PHIL simulation platform that enables interfacing high-power GFM inverter systems. The paper proposes the concept of a virtual GFM inverter as a part of the proposed PHIL interface. This addition of a virtual GFM inverter in the PHIL interface expands the conventional ideal transformer model (ITM) method and enables it to overcome the issues of instability of existing ITM methods. In the validation stage, a PHIL experiment is conducted on a three-phase, 480-V, 125-kVA GFM inverter system with the proposed interfacing method. The results corroborate that the proposed PHIL simulation method performs well and is stable for GFM inverter systems.

droop control↗

DOE OSTI2026

ODIN: Characterizing the Three-dimensional Structure of Two Protocluster Complexes at z = 3.1

We present a detailed study of the 3D morphology of two extended associations of multiple protoclusters at z = 3.1. These protocluster "complexes," designated COSMOS-z3.1-A and COSMOS-z3.1-C, are the most prominent overdensities of z = 3.1 Lyα emitters (LAEs) identified in the COSMOS field by the One-hundred-deg$^{2}$ DECam Imaging in Narrowbands survey. These protocluster complexes have been followed up with extensive spectroscopy from Keck, Gemini, and DESI. Using a probabilistic method that combines photometrically selected and spectroscopically confirmed LAEs, we reconstruct the 3D structure of these complexes on scales of ≈50 cMpc. We validate our reconstruction method using the IllustrisTNG300-1 cosmological hydrodynamical simulation and show that it consistently outperforms approaches relying solely on spectroscopic data. The resulting 3D maps reveal that both complexes are irregular and elongated along a single axis, emphasizing the impact of sightline on our perception of structure morphology. The complexes consist of multiple density peaks, 10 in COSMOS-z3.1-A and 4 in COSMOS-z3.1-C. The former is confirmed to be a proto-supercluster, similar to Hyperion at z = 2.4 but observed at an even earlier epoch. Multiple "tails" connected to the cores of the density peaks are seen, likely representing cosmic filaments feeding into these extremely overdense regions. The 3D reconstructions further provide strong evidence that Lyα blobs preferentially reside in the outskirts of the highest density regions. Descendant mass estimates of the density peaks suggest that COSMOS-z3.1-A and COSMOS-z3.1-C will evolve to become ultramassive structures by z = 0, with total masses log ( M / M ,⊙ ,) ≳ 15.3 , exceeding that of Coma.

Ramakrishnan, Vandana [Purdue U., West Lafayette] ↗

DOE OSTI2020

Machine-Learning-Driven, Site-Specific Weather Forecasting for Grid-Interactive Efficient Buildings: Preprint

Emerging grid-interactive efficient buildings (GEBs) have great potential to provide much-needed demand flexibility to electric grids while fulfilling their own control targets by co-optimizing smart appliances, solar photovoltaics, electric vehicles, and energy storage at buildings. To enable the optimal operation of GEBs, site-specific weather information—such as temperature, solar irradiance, relative humidity, and wind speed—is crucial; however, this information is generally unavailable or expensive to obtain. This paper develops advanced machine learning methods to provide precise weather forecasts for individual building sites using readily available weather station data. Support vector regression and artificial neural networks have been employed to learn the spatiotemporal correlations between the weather conditions at nearby weather stations and the individual building site. The proposed site-specific weather forecasting methods have been validated using 1-year actual weather measurement data collected in the Denver metro area. Results show that the developed machine-learning-driven methods can accurately forecast the temperature at the target building site 1 hour ahead with mean absolute error less than 0.72°C and a 48% improvement over the persistence method. Site-specific weather forecasts will improve the understanding of the microclimate effect and its impact on building energy consumption. This information will drive efficiency upgrades and adjustments of building control strategies to improve energy savings and increase flexibility in building loads.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2021

Pore-scale simulation of drying in porous media using a hybrid lattice Boltzmann: pore network model

In this work, a hybrid method coupling a pseudo-potential lattice Boltzmann model (LBM) and a pore network model (PNM) to simulate drying in porous media is proposed. Based on the watershed method, the porous medium is firstly decomposed into pore regions. According to the liquid–vapor phase distribution at a given time, the pore regions are further divided into four pore types, namely two-phase pores where a liquid–vapor interface exists, buffer pores next to the two-phase pores, single-liquid and single-vapor phase pores. The pseudo-potential LBM is used in the two-phase and buffer pores to simulate liquid drying and track the movement of the interfaces, while the single-phase PNM simulations are conducted in the buffer and single-phase pores to simulate vapor or liquid flow. LBM and PNM are coupled in the buffer pores through exchange of boundary information. The hybrid method is applied to simulate liquid drying in a porous medium. The whole-domain LBM simulation is considered as the reference solution to validate the hybrid method. Liquid saturation variation during the drying process and detailed phase and pressure distributions obtained by the two methods match quite well, demonstrating the accuracy of the hybrid method. For the specific case studied, the hybrid method saves more than 60% computational time compared to the whole-domain LBM simulation. In addition, the speedup of the hybrid method becomes more significant for a larger computational domain. In summary, the hybrid method developed in this work combines the accuracy of LBM and the efficiency of PNM to simulate drying in porous media at pore scale and can lead to significant reduction of computation time, thus allowing the pore-scale consideration of drying in larger porous systems.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Functional Data Analysis in Wearable Body Sensor Networks

Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Functional Data Analysis in Wearable Body Sensor Networks

60 - APPLIED LIFE SCIENCES↗

DOE OSTI2017

Industrializing Offshore Wind Power with Serial Assembly and Lower-cost Deployment - Final Report

A team of engineers and contractors has developed a method to move offshore wind installation toward lower cost, faster deployment, and lower environmental impact. A combination of methods, some incremental and some breaks from past practice, interact to yield multiple improvements. Three designs were evaluated based on detailed engineering: 1) a 5 MW turbine on a jacket with pin piles (base case), 2) a 10 MW turbine on a conventional jacket with pin piles, assembled at sea, and 3) a 10 MW turbine on tripod jacket with suction buckets (caissons) and with complete turbine assembly on-shore. The larger turbine, assembly ashore, and the use of suction buckets together substantially reduce capital cost of offshore wind projects. Notable capital cost reductions are: changing from 5 MW to 10 MW turbine, a 31% capital cost reduction, and assembly on land then single-piece install at sea an additional 9% capital cost reduction. An estimated Design 4) estimates further cost reduction when equipment and processes of Design 3) are optimized, rather than adapted to existing equipment and process. Cost of energy for each of the four Designs are also calculated, yielding approximately the same percentage reductions. The methods of Design 3) analyzed here include accepted structures such as suction buckets used in new ways, innovations conceived but previously without engineering and economic validation, combined with new methods not previously proposed. Analysis of Designs 2) and 3) are based on extensive engineering calculations and detailed cost estimates. All design methods can be done with existing equipment, including lift equipment, ports and ships (except that design 4 assumes a more optimized ship). The design team consists of experienced offshore structure designers, heavy lift engineers, wind turbine designers, vessel operators, and marine construction contractors. Comparing the methods based on criteria of cost and deployment speed, the study selected the third design. That design is, in brief: a conventional turbine and tubular tower is mounted on a tripod jacket, in turn atop three suction buckets. Blades are mounted on the tower, not on the hub. The entire structure is built in port, from the bottom up, then assembled structures are queued in the port for deployment. During weather windows, the fully-assembled structures are lifted off the quay, lashed to the vessel, and transported to the deployment site. The vessel analyzed is a shear leg crane vessel with dynamic positioning like the existing Gulliver, or it could be a US-built crane barge. On site, the entire structure is lowered to the bottom by the crane vessel, then pumping of the suction buckets is managed by smaller service vessels. Blades are lifted into place by small winches operated by workers in the nacelle without lift vessel support. Advantages of the selected design include: cost and time at sea of the expensive lift vessel are significantly reduced; no jack up vessel is required; the weather window required for each installation is shorter; turbine structure construction is continuous with a queue feeding the weather-dependent installation process; pre-installation geotechnical work is faster and less expensive; there are no sound impacts on marine mammals, thus minimal spotting and no work stoppage Industrializing Offshore Wind Power 6 of 96 9 for mammal passage; the entire structure can be removed for decommissioning or major repairs; the method has been validated for current turbines up to 10 MW, and a calculation using simple scaling shows it usable up to 20 MW turbines.

17 WIND ENERGY↗