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DOE OSTI2015

Integrated modeling applications for tokamak experiments with OMFIT

We developed one modeling framework for integrated tasks (OMFIT) is a comprehensive integrated modeling framework which will enable physics codes to interact in complicated workflows, and support scientists at all stages of the modeling cycle. The OMFIT development follows a unique bottom-up approach, where the framework design and capabilities organically evolve to support progressive integration of the components that are required to accomplish physics goals of increasing complexity. OMFIT provides a workflow for easily generating full kinetic equilibrium reconstructions that are constrained by magnetic and motional Stark effect measurements, and kinetic profile information that includes fast-ion pressure modeled by a transport code. It was found that magnetic measurements can be used to quantify the amount of anomalous fast-ion diffusion that is present in DIII-D discharges, and provide an estimate that is consistent with what would be needed for transport simulations to match the measured neutron rates. OMFIT was used to streamline edge-stability analyses, and evaluate the effect of resonant magnetic perturbation (RMP) on the pedestal stability, which have been found to be consistent with the experimental observations. Moreover, the development of a five-dimensional numerical fluid model for estimating the effects of the interaction between magnetohydrodynamic (MHD) and microturbulence, and its systematic verification against analytic models was also supported by the framework. OMFIT was used for optimizing an innovative high-harmonic fast wave system proposed for DIII-D. For a parallel refractive index n(parallel to) > 3, the conditions for strong electron-Landau damping were found to be independent of launched n(parallel to) and poloidal angle. OMFIT has been the platform of choice for developing a neural-network based approach to efficiently perform a non-linear multivariate regression of local transport fluxes as a function of local dimensionless parameters. Transport predictions for thousands of DIII-D discharges showed excellent agreement with the power balance calculations across the whole plasma radius and over a broad range of operating regimes. Concerning predictive transport simulations, the framework made possible the design and automation of a workflow that enables self-consistent predictions of kinetic profiles and the plasma equilibrium. It is found that the feedback between the transport fluxes and plasma equilibrium can significantly affect the kinetic profiles predictions. Finally, such a rich set of results provide tangible evidence of how bottom-up approaches can potentially provide a fast track to integrated modeling solutions that are functional, cost-effective, and in sync with the research effort of the community.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

An Integrated Traction Drive with a High Speed Surface Permanent Magnet External Rotor Motor for Electric Vehicles

This work presents the detailed design of an outer rotor motor and integrated drive for passenger electric vehicles. The motor uses non-heavy rare earth permanent magnets and operates at a top speed of 20,000rpm. In-slot ceramic heat exchangers are utilized for the cooling of the windings. The external rotor configuration of the motor leaves a significant amount of space in the stator bore, which is leveraged for the integration of the power electronics. A high speed external rotor motor creates a number of mechanical, thermal and assembly challenges and this work presents detailed thermal, mechanical and rotordynamics analysis.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Integrated Synchronization Control of Grid-Forming Inverters for Smooth Microgrid Transition

This paper develops an integrated synchronization control technique for a grid-forming inverter operating within a microgrid that can improve the microgrid's transients during microgrid transition operation. This integrated synchronization control includes the disconnection synchronization control and the reconnection synchronization control. The simulation results show that the developed synchronization control works effectively to smooth the angle change of the grid-forming inverter during microgrid transition operation. Thus, the microgrid's transients are significantly improved compared to the case without synchronization control.

control↗

DOE OSTI2022

A Blockchain Based Co-Simulation Framework for Integrating DERs to Wholesale Electricity Markets

As the number of distributed energy resources (DERs) continue to increase across energy-delivery systems, there remains a need for integrating their capabilities into traditional grid operations. In this paper, a blockchain-based solution is proposed to facilitate FERC's Order No. 2222 implementations. The presented use-case enables small-scale DERs to participate in wholesale market operations through DER aggregators, while also enabling local distribution system operators to enforce distribution system constraints in a secure and traceable manner. The presented use case is built around the Unified Testing Platform (UTP) being developed as a part of the Blockchain for Optimized Security and Energy Management (BLOSEM) project. This is a multi-lab effort intended to simplify the deployment of blockchain-powered grid solutions by enabling the integration of simulation tools, and blockchain technologies through the use of system-agnostic interfaces that provide a modular, interoperable, and reusable connectivity layer.

blockchain interoperability↗

DOE OSTI2015

Simulating and evaluating best management practices for integrated landscape management scenarios in biofuel feedstock production: Evaluating Best Management Practices for Biofuel Feedstock Production

Sound crop and land management strategies can maintain land productivity and improve the environmental sustainability of agricultural crop and feedstock production. This study evaluates the improvement of water sustainability through an integrated landscaping management strategy, where landscaping design, land management operations, crop systems, and agricultural best management practices (BMPs) play equal roles. The strategy was applied to the watershed of the South Fork Iowa River in Iowa, with a focus on implementing riparian buffers and converting low productivity land to provide cellulosic biomass while benefiting soil and water quality. The Soil and Water Assessment Tool (SWAT) was employed to simulate the impact of integrated landscape design on nutrients, suspended sediments, and flow on the watershed and subbasin scales. First, the study evaluated the representation of buffer strip as a vegetative barrier and as a riparian buffer using trapping efficiency and area ratio methods in SWAT. For the riparian buffer, the area ratio method tends to be more conservative, especially in nitrate loadings, while the trapping efficiency method generates more optimistic results. The differences between the two methods increase with buffer width. The two methods may not be comparable for the field-scale vegetative barrier simulation because of limitations in model spatial resolution. Landscape scenarios were developed to quantify water quality under (1) current land use, (2) partial land conversion to switchgrass, and (3) riparian buffer implementation. Results show that when low productivity land (15.2% of total watershed land area) is converted to grow switchgrass, suspended sediment, total nitrogen, total phosphorus, and nitrate loadings are reduced by 69.3%, 55.5%, 46.1%, and 13.4%, respectively, in the watershed surface streams. The reduction was less extensive when riparian buffer strips (30 m or 50 m) were applied to the stream network at 1.4% of total land area in the watershed. At the subbasin level, the degree of nutrient and suspended sediment reduction varies extensively, ranging from a few percent up to 55%. Results indicate that effective landscape design on current agricultural land can potentially bring marked improvements in water quality and soil erosion control while producing food and fuel feedstock in the South Fork Iowa River watershed. The concept can be integrated with other watershed management programs to improve sustainability of land, water, and the ecosystem.

bioenergy production↗

DOE OSTI2021

Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks

Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.

Bayesian network, Risk assessment, Monitoring, car↗

DOE OSTI2021

Mocking the u-plane integral

Abstract The u -plane integral is the contribution of the Coulomb branch to correlation functions of $${\mathcal {N}}=2$$ N = 2 gauge theory on a compact four-manifold. We consider the u -plane integral for correlators of point and surface observables of topologically twisted theories with gauge group $$\mathrm{SU}(2)$$ SU ( 2 ) , for an arbitrary four-manifold with $$(b_1,b_2^+)=(0,1)$$ ( b 1 , b 2 + ) = ( 0 , 1 ) . The u -plane contribution equals the full correlator in the absence of Seiberg–Witten contributions at strong coupling, and coincides with the mathematically defined Donaldson invariants in such cases. We demonstrate that the u -plane correlators are efficiently determined using mock modular forms for point observables, and Appell–Lerch sums for surface observables. We use these results to discuss the asymptotic behavior of correlators as function of the number of observables. Our findings suggest that the vev of exponentiated point and surface observables is an entire function of the fugacities.

Mathematics↗

DOE OSTI2014

An integrated assessment of location-dependent scaling for microalgae biofuel production facilities

Successful development of a large-scale microalgae-based biofuels industry requires comprehensive analysis and understanding of the feedstock supply chain—from facility siting and design through processing and upgrading of the feedstock to a fuel product. The evolution from pilot-scale production facilities to energy-scale operations presents many multi-disciplinary challenges, including a sustainable supply of water and nutrients, operational and infrastructure logistics, and economic competitiveness with petroleum-based fuels. These challenges are partially addressed by applying the Integrated Assessment Framework (IAF) – an integrated multi-scale modeling, analysis, and data management suite – to address key issues in developing and operating an open-pond microalgae production facility. This is done by analyzing how variability and uncertainty over space and through time affect feedstock production rates, and determining the site-specific “optimum” facility scale to minimize capital and operational expenses. This approach explicitly and systematically assesses the interdependence of biofuel production potential, associated resource requirements, and production system design trade-offs. To provide a baseline analysis, the IAF was applied in this paper to a set of sites in the southeastern U.S. with the potential to cumulatively produce 5 billion gallons per year. Finally, the results indicate costs can be reduced by scaling downstream processing capabilities to fit site-specific growing conditions, available and economically viable resources, and specific microalgal strains.

09 BIOMASS FUELS↗

DOE OSTI2020

Integrated Proteomic and Glycoproteomic Characterization of Human High-Grade Serous Ovarian Carcinoma

Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potentialroles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Hu, Yingwei↗

DOE OSTI2023

Recent advances in integrated hydrologic models: Integration of new domains

Over the past several decades, hydrologic models have advanced from independent models of the surface and subsurface to integrated models that can capture the terrestrial hydrologic cycle within one framework. In recent years, these coupled frameworks have seen the inclusion of biogeochemical processes, ecohydrology, sedimentation and erosion, cold region hydrology, anthropogenic activities, and atmospheric processes. This expansion is the result of increased computational, data, and modeling capabilities and capacities, as well as improved understanding of the processes that drive these integrated systems. Here, in this study, we review these recent advances to integrate new processes and systems into existing terrestrial hydrologic models and highlight the significant challenges and opportunities that remain. We identify that with so many models currently available and in development, selecting the most appropriate model is difficult, and we suggest a path for new or novice modelers to find the most appropriate code based on their needs. In addition, data required to parameterize and calibrate these models can often constrain their applicability and usefulness. However, advances in environmental sensors and measurement technology, in addition to data assimilation of non-traditional data (e.g. remote sensing, qualitative data) are providing new ways of addressing this issue. As we expand hydrologic models to integrate more processes and systems, our computational demands also increase. Recent and emerging advances in computational platforms, including cloud and quantum computing, in addition to the use of machine learning to capture some processes, will continue to support the use of increasingly larger and more complex, process-based models. Finally, we highlight that it is critical to develop state-of-the-science models that are accessible to all model users, not just those applied for research and development. We encourage continued development of diverse modeling platforms, considering the user needs, data availability, and computational resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Integrating computation and experiment to investigate photoelectrodes for solar water splitting at the microscopic scale.

CONSPECTUS: Photoelectrochemical water-splitting is a promising and sustainable way to store the energy of the sun in chemical bonds and use it to produce hydrogen gas, a clean fuel. The key components in photoelectrochemical cells (PECs) are photoelectrodes, including a photocathode that reduces water to hydrogen gas and a photoanode that oxidizes water to oxygen gas. Materials used in photoelectrodes for PECs must effectively absorb sunlight, yield photogenerated carriers, and exhibit electronic properties that enable the efficient shuttling of carriers to the surface to participate in relevant water-splitting reactions. Discovering and understanding the key characteristics of optimal photoelectrode materials is paramount to the realization of PEC technologies. Oxide-based photoelectrodes can satisfy many of these materials requirements, including stability in aqueous environments, band edges with reasonable alignment with the redox potentials for water splitting, and ease of synthesis. However, oxide photoelectrodes generally suffer from poor charge transport properties and considerable bulk electron-hole separation, and they have relatively large band gaps. Numerous strategies have been proposed to improve these aspects and understand how these improvements are reflected in the photoelectrochemical performance. Unfortunately, the structural and compositional complexity of multinary oxides accompanied by the inherent complexity of photoelectrochemical processes makes it challenging to understand the individual effects of composition, structure, and defects in the bulk and on the surface on a material's photoelectrochemical properties. The integration of experiment and theory has great potential to increase our atomic-level understanding of structure-composition-property relationships in oxide photoelectrodes. In this Account, we describe how integrating experiment and theory is beneficial for achieving scientific insights at the microscopic scale. We highlight studies focused on understanding the role of (i) bulk composition via solid-state solutions, intercalation, and comparison with isoelectronic compounds, (ii) dopants for both the anion and cation and their interactions with oxygen vacancies, and (iii) surface/interface structure in the photocurrent generation and photoelectrochemical performance in oxide photoelectrodes. In each instance, we outline strategies and considerations for integrating experiment and theory and describe how this integration led to valuable insights and new directions in uncovering structure-composition-property relationships. Our aim is to demonstrate the unique value of combining experiment and theory in studying photoelectrodes and to encourage the continued effort to bring experiment and theory in closer step with each other.

Wang, Wennie↗

DOE OSTI2022

Spectral control of nonclassical light pulses using an integrated thin-film lithium niobate modulator

Abstract Manipulating the frequency and bandwidth of nonclassical light is essential for implementing frequency-encoded/multiplexed quantum computation, communication, and networking protocols, and for bridging spectral mismatch among various quantum systems. However, quantum spectral control requires a strong nonlinearity mediated by light, microwave, or acoustics, which is challenging to realize with high efficiency, low noise, and on an integrated chip. Here, we demonstrate both frequency shifting and bandwidth compression of heralded single-photon pulses using an integrated thin-film lithium niobate (TFLN) phase modulator. We achieve record-high electro-optic frequency shearing of telecom single photons over terahertz range (±641 GHz or ±5.2 nm), enabling high visibility quantum interference between frequency-nondegenerate photon pairs. We further operate the modulator as a time lens and demonstrate over eighteen-fold (6.55 nm to 0.35 nm) bandwidth compression of single photons. Our results showcase the viability and promise of on-chip quantum spectral control for scalable photonic quantum information processing.

Optics↗

DOE OSTI2019

Building in vitro transcriptional regulatory networks by successively integrating multiple functional circuit modules

The regulation of cellular dynamics and responses to stimuli by genetic regulatory networks suggests how in vitro chemical reaction networks might analogously direct the dynamics of synthetic materials or chemistries. A key step in developing genetic regulatory network analogues capable of this type of sophisticated regulation is the integration of multiple coordinated functions within a single network. In this study, we demonstrate how such functional integration can be achieved using in vitro transcriptional genelet circuits that emulate essential features of cellular genetic regulatory networks. By successively incorporating functional genelet modules into a bistable circuit, we construct an integrated regulatory network that dynamically changes its state in response to upstream stimuli and coordinates the timing of downstream signal expression. We use quantitative models to guide module integration and develop strategies to mitigate undesired interactions between network components that arise as the size of the network increases. This approach could enable the construction of in vitro networks capable of multifaceted chemical and material regulation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Tomographic inversion techniques incorporating physical constraints for line integrated spectroscopy in stellarators and tokamaks

Accurate tomographic inversion is important for diagnostic systems on stellarators and tokamaks which rely on measurements of line integrated emission spectra. A tomographic inversion technique based on spline optimization with enforcement of constraints is described that can produce unique and physically relevant inversions even in situations with noisy or incomplete input data. This inversion technique is routinely used in the analysis of data from the x-ray imaging crystal spectrometer (XICS) installed at the Large Helical Device. The XICS diagnostic records a 1D image of line integrated emission spectra from impurities in the plasma. Through the use of Doppler spectroscopy and tomographic inversion, XICS can provide profile measurements of the local emissivity, temperature, and plasma flow. Tomographic inversion requires the assumption that these measured quantities are flux surface functions, and that a known plasma equilibrium reconstruction is available. In the case of low signal levels or partial spatial coverage of the plasma cross-section, standard inversion techniques utilizing matrix inversion and linear-regularization often cannot produce unique and physically relevant solutions. The addition of physical constraints, such as parameter ranges, derivative directions, and boundary conditions, allow for unique solutions to be reliably found. The constrained inversion technique described here utilizes a modified Levenberg-Marquardt optimization scheme, which introduces a condition avoidance mechanism by selective reduction of search directions. The constrained inversion technique also allows for the addition of more complicated parameter dependencies, for example, geometrical dependence of the emissivity due to asymmetries in the plasma density arising from fast rotation. The accuracy of this constrained inversion technique is discussed, with an emphasis on its applicability to systems with limited plasma coverage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Demonstration of a time-integrated short line of sight neutron imaging system for inertial confinement fusion

The Neutron Imaging System (NIS) is an important diagnostic for understanding implosions of deuterium-tritium capsules at the National Ignition Facility. While the detectors for the existing system must be positioned 28 m from the source to produce sufficient imaging magnification and resolution, recent testing of a new short line of sight neutron imaging system has shown sufficient resolution to allow reconstruction of the source image with quality similar to that of the existing NIS on a 11.6 m line of sight. The new system used the existing pinhole aperture array and a stack of detectors composed of 2 mm thick high-density polyethylene converter material followed by an image plate. In these detectors, neutrons enter the converter material and interact with protons, which recoil and deposit energy within the thin active layer of the image plate through ionization losses. The described system produces time-integrated images for all neutron energies passing through the pinhole. We present details of the measurement scheme for this novel technique to produce energy-integrated neutron images as well as source reconstruction results from recent experiments at NIF.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

MEASUREMENT OF GALAXY CLUSTER INTEGRATED COMPTONIZATION AND MASS SCALING RELATIONS WITH THE SOUTH POLE TELESCOPE

We describe a method for measuring the integrated Comptonization (Y {sub SZ}) of clusters of galaxies from measurements of the Sunyaev-Zel'dovich (SZ) effect in multiple frequency bands and use this method to characterize a sample of galaxy clusters detected in the South Pole Telescope (SPT) data. We use a Markov Chain Monte Carlo method to fit a β-model source profile and integrate Y {sub SZ} within an angular aperture on the sky. In simulated observations of an SPT-like survey that include cosmic microwave background anisotropy, point sources, and atmospheric and instrumental noise at typical SPT-SZ survey levels, we show that we can accurately recover β-model parameters for inputted clusters. We measure Y {sub SZ} for simulated semi-analytic clusters and find that Y {sub SZ} is most accurately determined in an angular aperture comparable to the SPT beam size. We demonstrate the utility of this method to measure Y {sub SZ} and to constrain mass scaling relations using X-ray mass estimates for a sample of 18 galaxy clusters from the SPT-SZ survey. Measuring Y {sub SZ} within a 0.'75 radius aperture, we find an intrinsic log-normal scatter of 21% ± 11% in Y {sub SZ} at a fixed mass. Measuring Y {sub SZ} within a 0.3 Mpc projected radius (equivalent to 0.'75 at the survey median redshift z = 0.6), we find a scatter of 26% ± 9%. Prior to this study, the SPT observable found to have the lowest scatter with mass was cluster detection significance. We demonstrate, from both simulations and SPT observed clusters that Y {sub SZ} measured within an aperture comparable to the SPT beam size is equivalent, in terms of scatter with cluster mass, to SPT cluster detection significance.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Modeling and Assessment of Integrated Hydroelectric Power and Hydrogen Energy Storage

Environmental and regulatory constraints are increasingly posing challenges to the optimal operation of hydroelectric facilities. Hydrogen energy storage (HES) is well-suited to address these challenges.Using excess or low-cost hydroelectric power during off-peak hours to produce hydrogen can help reduce water spills and unlock opportunities for energy arbitrage. Moreover, the oxygen byproduct of electrolysis can be used to improve the dissolved oxygen (DO) levels in tailrace water. %, a key water quality metric for hydroelectric facilities.This paper presents an innovative framework for modeling and assessing the integrated hydroelectric-hydrogen system, considering subsystem constraints and coupling, benefits in spill water reduction and DO mitigation, as well as diverse hydrogen utilization, including re-electrification, blending with natural gas, and direct sales. Comprehensive case studies were conducted to assess the techno-economic performance of the integrated system in different deployment scenarios.

Energy storage, Hydrogen, Hydropower, Optimization↗

DOE OSTI2021

EMS and DMS Integration of the Coordinative Real-time Sub-Transmission Volt-Var Control Tool under High DER Penetration

This paper proposes an applicable approach to deploy the Coordinative Real-time Sub-Transmission Volt-Var Control Tool (CReST-VCT), and a holistic system integration framework considering both the energy management system (EMS) and distribution system management system (DMS). This provides an architectural basis and can serve as the implementation guideline of CReST-VCT and other advanced grid support tools, to co-optimize the operation benefits of DERs and assets in both transmission and distribution networks. Potential communication protocols for different physical domains of a real application is included. Performance and security issues are also discussed, along with specific considerations for field deployment. Finally, the paper presents a viable pathway for CReST-VCT and other advanced grid support tools, which could be integrated in an open-source standardized-based platform that supports distribution utilities.

Nguyen, Quan H.↗