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DOE OSTI2021

Thermal confinement and transport in spherical tokamaks: a review

Here, we review the thermal plasma confinement and transport properties observed and predicted in low aspect ratio tokamaks, or spherical tokamaks (STs), which can depart significantly from those observed at higher aspect ratio. In particular, thermal energy confinement scalings show a strong, near linear dependence of energy confinement time on toroidal magnetic field, while the dependence on plasma current is more modest, the opposite of what is seen at higher aspect ratio. STs have revealed a very strong improvement in normalized confinement with decreasing collisionality, much stronger than at higher aspect ratio, which bodes well for an ST-based fusion pilot plant should this trend continue at an even lower collisionality than has already been accessed. These differences arise because of fundamental differences in transport in STs due to the more extreme toroidicity (i.e. reduced region of bad curvature), and to the relatively larger $E_r \times B$ shearing rates, both of which can suppress electrostatic drift wave instabilities at both ion and electron gyroradius scales. In addition, electromagnetic effects are much stronger in STs because they operate at high β T . Gyrokinetic (GK) studies, coupled with low- and high-k turbulence measurements, have shed light on the underlying physics controlling transport. At lower β T , both ion- and electron-scale electrostatic drift turbulence may be responsible for transport. At higher β T , microtearing, kinetic ballooning, and hybrid trapped electron/kinetic ballooning modes increasingly play a role, and they have a much stronger impact in the core of ST plasmas than at higher aspect ratio. Flow shear affects the balance between ion- and electron-scale modes. Non-linear GK simulations find regimes where the electron heat flux decreases with decreasing collisionality, consistent with the experimental global normalized confinement scaling. The ST is unique in that the relatively low toroidal magnetic field allows for localized measurements of electron-scale turbulence, and this coupled with turbulence measurements at ion-scales has facilitated detailed comparisons with GK simulations. These data have provided compelling evidence for the presence of ion temperature gradient and electron temperature gradient turbulence in some plasmas, and direct experimental support for the impact of experimental actuators like rotation shear, density gradient and magnetic shear on turbulence and transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Steady-State Analysis of Microgrid Distributed Control Under Denial of Service Attacks

Distributed control is an effective method to coordinate multiple components in a microgrid. It usually has mandatory requirements for communication graph topology; changing the topology unexpectedly could disrupt the operation of a distributed controller. A denial of service (DoS) attack blocks communication channels to cause variations in communication graph. Unforeseen topology changes render a controller to receive incomplete system information. Control decisions made based on incorrect information can lead to significantly reduced grid supporting capability. As a result, the vital power balance between generation and load may be challenged. Determining power balance requires steady-state power flow analysis; however, the cyber-induced steady-state analysis is not well studied in the literature. Here, in this article, we show that a cyber–physical microgrid with unknown DoS attacks has augmented uncertain power flow equations, whose special structure creates new computational issue to determining power balance. To deal with the issue, we develop a novel cyber-induced microgrid model: the cyber–physical system is transformed into a pure physical model, where the disruption effects of DoS in the cyber layer are shown to be equivalent to the variations of the physical model parameters. With the transformed system, we develop a sufficient condition to ascertain the system power balance under unknown DoS attacks. In addition, practical insights for resilient distributed control design are shown as well.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Leveraging Multiple Connected Traffic Light Signals in an Energy-Efficient Speed Planner

Connecting automated vehicles to traffic lights can lead to significant energy savings by enabling them to pass through intersections in an energy-efficient way without unnecessary stops. A cellular-based communication system connecting multiple traffic lights can help realize the full potential of energy-efficient driving at intersections. Thus, we propose a hierarchical speed planner that can leverage information from multiple connected traffic lights. The proposed speed planner consists of two modules: a green window selector and a reference trajectory generator. The green window selector, based on Dijkstra’s algorithm, finds a series of "green windows" for connected traffic lights that builds an energy-optimal path for vehicles to follow. The reference trajectory generator finds optimal entering times, based on the selected green window at each intersection, and then computes reference trajectories. Deriving and using analytical optimal entering speeds as a function of entering times allows us to guarantee the computational simplicity suitable for real-time implementation. We also demonstrate how to balance energy and traffic flow perspectives in the reference trajectory generator. Lastly, a high-fidelity simulation framework is used to evaluate the proposed speed planner and quantify the extent to which it can save energy in various real-world urban route scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

WaterTAP3 (The Water Technoeconomic Assessment Pipe-Parity Platform)

The Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3) was developed under the National Alliance for Water Innovation (NAWI) to facilitate consistent technoeconomic assessments of desalination treatment trains. The WaterTAP3 is an analytically robust modeling tool that can be used to evaluate water technology cost, energy, environmental, and resiliency tradeoffs across different water sources, sectors, and scales. The model simulates steady-state water treatment train performance and costs including flow and constituent mass balance across unit processes, based on source water conditions, configurations of treatment technologies, and system-level techno-economic assumptions. Users can build a new treatment train by connecting any number of unit processes, specific for their context and system, or selecting a train from the treatment train library. The model contains various technical and cost parameter options for a range of treatment processes and a library of influent water quality characteristics for a variety of source waters and case studies. Users can customize water quality parameters to evaluate the technology performance in their context. The model can be set up for different assessment needs including simulation, optimization, and uncertainty and sensitivity analyses. The results from WaterTAP3 can help identify trade-offs among the different system performance metrics, with insight on how particular technologies or systems promote pipe-parity. The flexibility and comprehensive scope of the tool makes it a promising solution to industry-wide water technoeconomic evaluations, leading to more informed water investment decisions and technologies. As a user-friendly, open-source platform, WaterTAP3 can be used by industry, academia, policymakers, planners, and those with or without extensive analytical experience.

Miara, Ariel↗

DOE OSTI2021

Water Technoeconomic Assessment Pipe-Parity Platform (WaterTAP3)

Miara, Ariel↗

DOE OSTI2022

Hydrogen Storage for Load-Following and Clean Power: Duct-firing of Hydrogen to Improve the Capacity Factor of NGCC Plants (Final Report, Phase I Conceptual Study)

The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and the proposed system is an improvement over alternate low carbon dispatchable power options. Our demonstration will include 54 MWh of hydrogen storage. CO 2 capture inherent to the CHG process can capture 90% of the CO 2 (with upgrades to >98%) in a commercial system (~300 MWth) for sequestration or other uses. The hydrogen will be utilized in a duct burner in a Heat Recovery Steam Generator (HRSG) integrated with the existing Southern Company fossil asset. Here, the firing rate of the duct burner is varied to let the plant respond to fluctuations of electrical load. However, H 2 production is relatively constant by storing H 2 , and revenues are improved by arbitrage between use of low-cost off-peak variable electricity generation or use of stored H 2 under peak demand. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via system requirements review with the whole team. These requirements were then incorporated into/iterated with our Heat & Mass Balance models and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Our system generates power at 17.4% lower cost than other low carbon approaches for the H 2 generation, H 2 compression and storage, carbon sequestration, and HRSG added electricity production for a large-scale duct-fired system. Our team recommends completing the Phase II Pre-FEED study for the proposed system as the next step for the project and its tasks will achieve the overall objective and be ready to launch the FEED. The Pre-FEED tasks include updating the requirements, Concept of Operations, plant scope/process description, component modeling, system modeling, performance estimates, emission estimates, block flow diagrams, fluid/process conditions (PFD), utility usage, and facility sizing/definition. The approach will be to complete these updates in a greater level of detail for the selected site. The approach for developing the EIV is to use the updated results, including model outputs, for carbon dioxide and waste streams.

03 NATURAL GAS↗

DOE OSTI2022

Bidisperse supension balance model

The suspension balance model (SBM) for viscous Stokes flow has been well studied for the case of identical, monodisperse spherical particles in a channel, however, more work remains to be done to explore the bidisperse and polydisperse SBM. Here, we present a simple extension of the SBM that allows for modeling of suspensions of particles of bidisperse size. The comparison with avaiable experiments and direct simulations is found to be good. Additionally, we present a range of simulations to justify the assumptions made in the polydisperse suspension balance model for non-Brownian, neutrally buoyant particles that vary in size with a bidisperse distribution. The aim is to study the effects of moderate size variation on the rheology of the suspension and the distribution of the particles across the flow, especially in the near-wall regions. It is shown that, at the size ratios considered, bidispersity in the particle size does not significantly affect rheological parameters including the particle volume fraction and relative viscosity in the bulk of a Couette flow. The particle phase stresses are distributed between small and large particles in proportion to the relative volume fractions of each species. In bidisperse suspensions, the large particles in the wall layer develop a spatial structure and form chains in the streamwise direction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Engineering Study of Svante’s Solid Sorbent Post-Combustion CO 2 Capture Technology at a Linde Steam Methane Reforming H 2 Plant

An initial engineering design study was performed for an advanced post combustion CO 2 capture (PCC) technology to be installed at a commercial-scale steam methane reforming (SMR) hydrogen plant located in the US Gulf Coast. The PCC process integrated the VeloxoTherm™ structured adsorbent technology from Svante for the CO 2 separation and CO 2 compression and purification and balance of plant systems provided by Linde. This pre-FEED equivalent study included following: (1) design basis, (2) basic engineering, including development of process flow diagrams and heat & material balances, (3) inside the battery limit (ISBL) equipment and systems specification, (4) balance of plant outside the battery limit (OSBL) equipment and systems specifications, (5) technology maturation plan, (6) hazard identification (HAZID) review, (7) environmental, health and safety (EH&S) assessment and environmental permitting analysis, (8) constructability review, (9) ISBL and OSBL EPC cost estimation, and (10) commercial-scale techno-economic analysis including capital expenditures (CAPEX) and operating expenditures (OPEX) and CO 2 capture cost estimates.

03 NATURAL GAS↗

DOE OSTI2022

Conservative Numerical Schemes with Optimal Dispersive Wave Relations: Part II. Numerical Evaluations

A new energy and enstrophy conserving scheme (EEC) for the shallow water equations is proposed and evaluated using a suite of test cases over the global spherical or bounded domain. The evaluation is organized around a set of pre-defined properties: accuracy of individual operators, accuracy of the whole scheme, conservation of key quantities, control of the divergence variable, representation of the energy and enstrophy spectra, and simulation of nonlinear dynamics. The results confirm that the scheme is between the first and second order accurate, and conserves the total energy and potential enstrophy up to the time truncation errors. Here, the scheme is capable of producing more physically realistic energy and enstrophy spectra, indicating that it can help prevent the unphysical energy cascade towards the finest resolvable scales. With an optimal representation of the dispersive wave relations, the scheme is able to keep the flow close to being non-divergent, and maintain the geostrophically balanced structures with large-scale geophysical flows over long-term simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Numerical Investigation of Butterfly Valve Performance in Variable Valve Sizes, Positions and Flow Regimes

Reliability and efficiency of valves are necessary for precise control and sufficient heat-flow to heat application plants for the integrated energy systems of nuclear power plants (NPPs). Strategic Management Analysis Requirement and Technology (SMART) valves’ ability to control flow and assess environmental parameters stands out for these requirements. Their ability to sustain the downstream flow rate, prevent reverse flow, and maintain pressure in the heat transport loop is much more efficient with the integration of sensors and intelligent algorithms. For assessing valve performance and monitoring, mechanical design and operating conditions are two important parameters. In this study, the butterfly valves of three different sizes are simulated with water and steam using STAR-CCM+ in various flow regimes and positions to analyze performance parameters to strategize an automated control system for efficiently balancing the heat–transport network. Also, flow behavior is studied using velocity and pressure fields for valve–body geometry optimization. It can be observed, through performance parameters, that the valves are suitable for operation between 30° and 90° positions with significantly low loss coefficients and high flow coefficients, and the performance parameters follow a certain pattern in both water and steam flow in each scenario.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Force balance model predictions of sliding bubbles velocity in vertical subcooled boiling flow

Not Available

Yoo, Junsoo↗

DOE OSTI2020

Analytical model of plasma response to external magnetic perturbation in absence of no-slip condition

Recent simulation and experimental results suggest that the magnetic island and flow on a resonant surface often do not satisfy the “no-slip” condition in the steady state. A new theoretical model on a nonlinear plasma response to external magnetic perturbation in the absence of a no-slip condition is proposed. The model is composed of the equations for the evolution of both the width and phase of the magnetic island due to forced reconnection driven by the external magnetic perturbation, and the force-balance equation for the plasma flow. When the island width is much less than the resistive layer width, the island growth is governed by the linear Hahm–Kulsrud–Taylor solution in the presence of time-dependent plasma flow. In the other regime when the island width is much larger than the resistive layer width, the evolution of both the island width and phase can be described using the Rutherford theory. The island solution is used to construct the quasilinear electromagnetic force, which, together with the viscous one, contributes to the nonlinear variation in plasma flow. The no-slip condition assumed in the conventional error field theory is not imposed here, where the island oscillation frequency depends on but does not necessarily equal to the plasma flow frequency at the rational surface.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Scalable Risk Assessment of Rare Events in Power Systems With Uncertain Wind Generation and Loads

Risk assessment of rare events has become increasingly important in power system planning and operation with the increasing integration of renewable energy and the presence of system uncertainties. However, quantifying the risk posed by rare events via the traditional method, i.e., Monte Carlo sampling (MCS), incurs substantial computational expense stemming from the vast ensemble of power flow simulations. To accelerate the assessment, this paper proposes a Deep Neural Network (DNN)-kernelized vector-valued Gaussian Process (VVGP) approach with excellent computational efficiency while maintaining high accuracy. Consequently, serving as a surrogate model for the power flow solver, the DNN-kernelized VVGP enables significantly faster but accurate risk assessment compared to the power flow solver. The developed surrogate model evaluates low-order N - k events that contain more than 90% instances by adeptly capturing the topological features while the high-order N - k events are assessed via a power flow solver, thereby striking a balance between computational efficiency and uncertainty quantification accuracy. Moreover, the model incorporates a Support Vector Machine (SVM) classifier to resample concerning low-probability tail events to counteract the biases potentially introduced during the DNN-kernelized VVGP evaluations. Simulations conducted on the modified IEEE 24-bus, 118-bus, and European 1354-bus systems demonstrate that the proposed method maintains the accuracy benchmark set by MCS while significantly reducing computational demands in large-scale power systems as compared to other state-of-the-art methods.

17 WIND ENERGY↗

DOE OSTI2025

Active Fluids Form System-Spanning Filamentary Networks

Recent experimental realizations of liquid-liquid phase separation of active liquid crystals have offered an insight into the interaction between phase separation, ubiquitous in soft matter and biology, and chaotic active flows. Here, in this Letter, we use continuum theory to examine phase separation of an active liquid crystal and a passive fluid and report two new results. First, we provide an analytical derivation of the activity-induced suppression of the phase boundary of the coexistence region—a result first reported in simulations and experiments. We show that the shift in the critical point is a result of the balance between self-stirring active flows and phase-separating diffusive fluxes. Second, we show that this same balance is responsible for dramatically changing the morphology of the phase separated state, resulting in the emergence of a new mixed active phase consisting of a dynamical filamentous active network that invades the entire system area, trapping droplets of passive material. This structure exists even for very low volume fractions of active material. Our work provides an important step towards the goal of understanding how to use activity as a new handle for sculpting interfaces.

active nematics↗

DOE OSTI2022

Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system

New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.

08 HYDROGEN↗

DOE OSTI2023

DT-HYDRO

The software solves the time dependent, one dimensional (1D) coupled mass and momentum balance equations governing the elastic flow of water through the penstock, turbine and draft tube in a hydroelectric facility using a high order finite volume based method. The numerical method is based on the Kurganov-Tadmor central method paired with the Monotonic Upstream-centered Scheme for Conservation Laws (MUSCL). This solution method accurately resolves the fast transient behavior of the flow, including water hammer. Additionally, the software estimates the full 3D flow field within the turbine chamber in real time, a feat that is made possible by leveraging pre-computed CFD results by utilizing a reduced order modeling method based on an efficient randomized singular value decomposition (SVD) driven proper orthogonal decomposition (POD) with POD-mode weight regression. The reduced order model of the 3D flow is directly coupled to the 1D elastic flow model so the entire flow field through the penstock and turbine system is resolved quickly and with high fidelity.

Gurecky, William [Oak Ridge National Laboratory (O↗

DOE OSTI2022

EGS Collab Experiment 2: Results of Tracer Tests

Multiple sets of tracer tests were conducted at the EGS Collab Testbed 2 on the 4100 L at the Sanford Underground Research Facility (SURF), Lead, SD. The enclosed data package includes: tracer recovery results, water balance calculations and rationales, water flow measurement for north ditch, (manual) water flow measurements at different production points, and a tracer-interpretation paper presented at the Stanford Geothermal Workshop, 2023.

15 GEOTHERMAL ENERGY↗

DOE OSTI2026

Model data for infrastructure-aware simulation of compound flooding at Alligator Bayou Watershed, southeast Texas

This dataset supports infrastructure-aware hydrologic modeling and flood scenario analysis for the Alligator Bayou Watershed, a highly managed urban watershed in Southeast Texas. It includes Jupyter notebooks for figure reproduction, model configuration files, simulation outputs, and derived products used to quantify the influence of engineered stormwater infrastructure on flood behavior across multiple spatial scales. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations on a channel-aligned mesh with explicit representations of pump stations, gate structures, detention basins, and impervious surfaces. Outputs include time series of gate and pump flows, stage observations, and water balance components, as well as spatially explicit fields of peak ponded depth and flood duration across multiple infrastructure scenarios spanning a single-location detention basin expansion, distributed drainage limitations, and compound coastal flooding. These data facilitate full reproducibility of the manuscript figures and support further research on urban flood dynamics and the role of stormwater infrastructure in shaping watershed-scale flood response.

EARTH SCIENCE > OCEANS > COASTAL PROCESSES↗