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At least 343 records · Page 19

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DOE OSTI2024

Tax Credits for Clean Electricity: The Distributional Impacts of Supply-Push Policies in the Power Sector

We evaluate distributional and efficiency consequences of the bulk power clean electricity tax credits authorized by the 2022 Inflation Reduction Act. To do so, we link detailed electricity capacity expansion, computable general equilibrium, microsimulation, and air pollution models to estimate economic welfare and health incidence across demographic groups. We evaluate trade-offs between policy efficiency and income progressivity by comparing the tax credits to cap-and-trade policies. The tax credits encourage increased clean electricity investment, resulting in a reallocation of capital from elsewhere in the economy, higher prices for capital and other goods, lower power prices, and lower emissions. The tax credits yield progressive outcomes for economic welfare at the expense of efficiency while all modeled policies demonstrate progressivity in health impacts. The health benefits, absent climate benefits, exceed total policy costs and provide greater benefits for low-income and historically marginalized households given coincidence of household locations and emissions exposure intensity.

distributional impacts↗

DOE OSTI2025

Predictive outlook for experiments resolving prompt vs local redeposition of high- Z materials in tokamaks

High-Z plasma facing components redeposit within the sheath through a combination of two distinct mechanisms: prompt (or geometric-driven) and local (or sheath-driven) redeposition. Experimental efforts are needed to determine the leading-order parameters influencing prompt-vs-local trade-off, which sets the fraction of material entering the scrape-off layer. In preparation for such experiments, leading-order parameters are isolated within the PYEAD-RustBCA-GITR coupled net erosion code using Sobol’ sensitivity analysis. Then, experiments resolving prompt-vs-local trade-off under variation of these leading-order parameters are proposed using an isotopic coupon design with multifaceted diagnostic coverage. The measurability of these experiments is evaluated using synthetic diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

The physics basis to integrate an MHD stable, high-power hybrid scenario to a cool divertor for steady-state reactor operation

Abstract Coupling a high-performance core to a low heat flux divertor is a crucial step for ITER and a Fusion Pilot Plant or DEMO. Experiments in DIII-D recently expanded the steady-state hybrid scenario to high density and divertor impurity injection to study the feasibility of a radiating mantle solution. This work presents the physics basis for trade-offs between density, current drive and stability to tearing modes (TMs) at high β. EC power is crucial to tailor the plasma profiles into a passively stable state, and to eject impurities from the core. Off-axis EC depositions decrease the heating efficiency, but calculated electron heat transport coefficients show that this effect is partially mitigated by improved confinement inside the EC deposition. Additionally, the reduction in pressure is recovered by increasing the density. This favourable scaling of confinement with density was observed in high power plasmas for years, and this work provides a comprehensive explanation. ELITE predictions indicate that a path in peeling-ballooning stability opens up for certain conditions of density, power, q 95 and shaping, allowing the edge pressure to continue increasing without encountering a limit. In the core, calculated anomalous fast-ion diffusion coefficients are consistent with density fluctuation measurements in the toroidicity-induced Alfvén eigenmode range, showing that smaller fast-ion losses contribute to the enhanced confinement at high density. The edge integration study shows that divertor heat loads can be reduced with Ne and Ar injection, but this eventually triggers a cascade of n = 1, 2, 3 core TMs. We can now show that impurity radiation in the core is small and it is not the cause for the drop in confinement at high Ar and Ne injection rates. The overlap between the core TMs is consistent with the loss of pressure as estimated by the Belt model for the coupled rational surfaces. Optimization of these trade-offs has achieved plasmas with sustained H 98y2 = 1.7, f GW = 0.7 and ∼85% mantle radiation. The scenario and its variations at higher density and on- vs off-axis EC heating has been studied as a candidate for an integrated solution for several reactor designs, such as ITER, ARC, and the ARIES-ACT1 case, showing promising results in terms of fusion power and gain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Electromagnetic coil optimization for reduced Lorentz forces

Abstract The reduction of magnetic forces on electromagnetic coils is an important consideration in the design of high-field devices such as the stellarator or tokamak. Unfortunately, these forces may be too time-consuming to evaluate by conventional finite element modeling within an optimization loop. Although mutual forces can be computed rapidly by approximating large-bore coils as infinitely thin, this approximation does not hold for self-forces as it leads to an unphysical divergence. Recently, a novel reduced model for the self-field, self-force, and self-inductance of electromagnetic coils based on filamentary models was rigorously derived and demonstrated to be highly accurate and numerically efficient to evaluate (Hurwitz et al 2024 IEEE Trans. Magn. 60 7001614). In this paper, we present an implementation of the reduced self-force model employing automatic differentiation within the simsopt stellarator design software and use it in derivative-based coil optimization for a quasi-axisymmetric stellarator. We show that it is possible to significantly reduce point-wise forces throughout the coils, though this comes with trade-offs to fast particle losses and the minimum distance between coils and the plasma surface. The trade-off between magnetic forces and coil-surface distance is mediated by the minimum coil–coil distance for coils near the inboard side of the ‘bean’ cross-section of the plasma. The relationship between forces and fast particle losses is mediated by the normal field error. Coil forces can be lowered to a threshold with minimal deterioration to losses. Importantly, the magnet optimization approach here can be used also for tokamaks, other fusion concepts, and applications outside of fusion.

Hurwitz, Siena (ORCID:0000000166599659)↗

DOE OSTI2026

Power and particle exhaust in the ST-E1 fusion power plant

Power exhaust challenges and potential solutions for a 5 m major radius, low-aspect ratio burning tokamak have been explored. 1D edge plasma models have been used to screen for access to detachment using short and long outer divertor legs in double and single null configurations, using Ar as the primary impurity and assuming tungsten plasma-facing components (PFCs). These show that detachment access can be accessed for all but the most conservative assumptions on scrape-off layer (SOL) width and power, but that trade-offs will be required between magnet engineering and the size of the acceptable window of as-yet uncertain plasma parameters. SOLPS-ITER was used to further model selected plasma scenarios, confirming that Ar seeding can be used to achieve dissipative divertor scenarios with peak deposited heat fluxes below 15 MWm -2 . Initial scoping of first wall loads and positioning of limiters has been carried out, showing the feasibility of protecting the breeding blanket wall during steady state without impeding tritium breeding. Initial PFC technology selection is also presented, identifying this as a critical area where further work is needed to find an attractive solution for helium-cooled PFCs that can handle high heat fluxes without excessive power requirements. Key questions and trade-offs for concept development have been identified, including: how to achieve high radiation for reduction of SOL power without core performance degradation; whether power exhaust can be well-controlled in a double null plasma; mechanical design and materials challenges of high-heat flux PFCs; and control of material erosion, redeposition and tritium retention.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

An efficient approach to explore the solution space of a wind turbine rotor design process

This study proposes a novel approach to explore the solution space of a wind turbine rotor design process. The goal is to offer to blade designers the possibility to select an optimal rotor for given market conditions, assessing trade-offs and alternatives in a matter of minutes. The design process consists of sequential aerodynamic-structural optimizations, where the two loops are linked via a blade-loading parameter that can be varied by the user. A design study is performed starting from the IEA Wind Task 37 land-based reference wind turbine. The solution space is characterized for rotor diameters in the range of 130–160 m, rated generator power values in the range of 3.0–6.0 MW, and tip-speed ratios in the range of 7.5–12.5. Results are discussed highlighting optimal design decisions and trade-offs.

17 WIND ENERGY↗

DOE OSTI2022

Floating Wind Turbine Control Optimization

We present a framework for optimizing the control parameters of floating offshore wind turbines (FOWTs). The framework combines aeroelastic simulations with a systems engineering model and control software. In an example of the optimization framework, we minimize tower damage equivalent loading with generator speed constraints. We also study the effect of thrust-limiting control and quantify the trade off between fatigue loading and energy capture using a set of optimal controller designs. Finally, we optimize the controller of four different FOWT models and compare their dynamic responses. Additional details and other use cases for the framework are presented, which can optimize different control problems and evaluate FOWT designs.

controls↗

DOE OSTI2026

Financial-technical co-design for capital-intensive, resource-responsive energy systems

Because of their capital-intensive operation, wind energy systems that are competitive in terms of the cost of the energy that they produce lead to risk-reward trade-offs that make their business cases less favorable than those of conventional energy generation technologies. However, wind energy systems tend to be designed to maximize energy production or minimize cost of energy rather than to maximize their business cases. In this work, we attempt to exploit designs specifically tailored to business cases. We develop a novel framework for analyzing energy systems that ties their design variables to monthly operating incomes using simple models and historical hourly market and resource data. Using this approach, we demonstrate that for a wind site with abundant wind resource in the California Independent System Operator market, we can control the trade-off between mean and 5th percentile monthly returns by choosing the specific power of the turbine at a fixed modeled initial capital cost. Our framework gives a measure of the risk-reward spectrum of energy generation assets that could be built at a given site with respect to the sub-annual resource/market variation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

A rapid embodied carbon assessment tool for priority materials

Embodied carbon limits within building materials are a driving factor in global trade, generating new research and analysis tools in industry. These product assessments, which require utilizing life-cycle assessment (LCA) across broad supply chains, can be expensive, time and data-intensive, and subject to significant variations. Existing methods and tools, such as specific environmental product declarations, typically do not capture these variations and dynamics in supply and manufacturing. Moreover, models and tools must enable stakeholders to assess customized supply chains and future scenarios. In this study, we present the Rapid Embodied Carbon Assessment and Target-setting for Emissions-intensive Materials (REDuCE) tool for building materials. We developed a tool that allows users to select production technologies, transportation mode and distances, concrete carbonation, fuel sources, and regional electricity mixes to supply customization for cement and concrete produced and consumed in California. We generated and integrated a material demand model using residential building stock projections. We provide the user with a wide range of mitigation alternatives through low-carbon production pathways, material use efficiency, transportation modes, and projected electricity grid mixes. In a case study application through four mitigation scenarios, we find emission savings up to 80% by maximizing user mitigation alternatives, primarily driven by reductions in material use intensities. This work represents a foundation for expanding LCA and embodied carbon tools to better enable stakeholders to rapidly and accurately assess customized supply chains while meeting trade requirements.

building materials↗

DOE OSTI2025

The Cost of Scaling Up in Large-Format Additive Manufacturing

Additive manufacturing (AM) of large objects has, over the last decade, required the scaling of existing material extrusion processes. The current generation of large-scale printers are primarily gantry robots with high-throughput extrusion systems. With workspaces approaching 50 m 3 , these printers have pushed the boundaries of achievable print volume while allowing the utilization of low-cost feedstocks, such as cementitious materials and polymer pellets, like those used in injection molding. Continued workspace expansion requires an examination of the inherent trade-offs, which impact capital and operational costs. Here, in this work, the authors examine these trade-offs to determine fundamental scaling laws for existing system architectures, survey the state of the art for alternative system configurations, and pose recommendations for future system designers to continue the evolution of large-scale AM systems.

3D printing↗

DOE OSTI2022

Regression of exchangeable relational arrays

Relational arrays represent measures of association between pairs of actors, often in varied contexts or over time. Trade flows between countries, financial transactions between individuals, contact frequencies between school children in classrooms and dynamic protein-protein interactions are all examples of relational arrays. Elements of a relational array are often modelled as a linear function of observable covariates. Uncertainty estimates for regression coefficient estimators, and ideally the coefficient estimators themselves, must account for dependence between elements of the array, e.g., relations involving the same actor. Existing estimators of standard errors that recognize such relational dependence rely on estimating extremely complex, heterogeneous structure across actors. This paper develops a new class of parsimonious coefficient and standard error estimators for regressions of relational arrays. Here we leverage an exchangeability assumption to derive standard error estimators that pool information across actors, and are substantially more accurate than existing estimators in a variety of settings. This exchangeability assumption is pervasive in network and array models in the statistics literature, but not previously considered when adjusting for dependence in a regression setting with relational data. We demonstrate improvements in inference theoretically, via a simulation study, and by analysis of a dataset involving international trade.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Improving Traditional Registrational Trial End Points: Development and Application of a Desirability of Outcome Ranking End Point for Complicated Urinary Tract Infection Clinical Trials

Abstract Background Traditional end points used in registrational randomized, controlled trials (RCTs) often do not allow for complete interpretation of the full range of potential clinical outcomes. Desirability of outcome ranking (DOOR) is an approach to the design and analysis of clinical trials that incorporates benefits and risks of novel treatment strategies and provides a global assessment of patient experience. Methods Through a multidisciplinary committee of experts in infectious diseases, clinical trial design, drug regulation, and patient experience, we developed a DOOR end point for infectious disease syndromes and demonstrated how this could be applied to 3 registrational drug trials (ZEUS, APEKS-cUTI, and DORI-05) for complicated urinary tract infections (cUTIs). ZEUS compared fosfomycin to piperacillin/tazobactam, APEKS-cUTI compared cefiderocol to imipenem, and DORI-05 compared doripenem to levofloxacin. Using DOOR, we estimated the probability of a more desirable outcome with each investigational antibacterial drug. Results In each RCT, the DOOR distribution was similar and the probability that a patient in the investigational arm would have a more desirable outcome than a patient in the control arm had a 95% confidence interval containing 50%, indicating no significant difference between treatment arms. DOOR facilitated improved understanding of potential trade-offs between clinical efficacy and safety. Partial credit and subgroup analyses also highlight unique attributes of DOOR. Conclusions DOOR can effectively be used in registrational cUTI trials. The DOOR end point presented here can be adapted for other infectious disease syndromes and prospectively incorporated into future clinical trials.

Immunology↗

DOE OSTI2023

Seeing through noise in power laws

Despite widespread claims of power laws across the natural and social sciences, evidence in data is often equivocal. Modern data and statistical methods reject even classic power laws such as Pareto’s law of wealth and the Gutenberg–Richter law for earthquake magnitudes. We show that the maximum-likelihood estimators and Kolmogorov–Smirnov (K-S) statistics in widespread use are unexpectedly sensitive to ubiquitous errors in data such as measurement noise, quantization noise, heaping and censorship of small values. This sensitivity causes spurious rejection of power laws and biases parameter estimates even in arbitrarily large samples, which explains inconsistencies between theory and data. We show that logarithmic binning by powers of λ > 1 attenuates these errors in a manner analogous to noise averaging in normal statistics and that λ thereby tunes a trade-off between accuracy and precision in estimation. Binning also removes potentially misleading within-scale information while preserving information about the shape of a distribution over powers of λ, and we show that some amount of binning can improve sensitivity and specificity of K-S tests without any cost, while more extreme binning tunes a trade-off between sensitivity and specificity. We therefore advocate logarithmic binning as a simple essential step in power-law inference.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Scalable Parallel Measurement of Individual Nitrogen-Vacancy Centers

The nitrogen-vacancy (NV) center in diamond is a solid-state spin defect that has been widely adopted for quantum sensing and quantum information processing applications. Typically, experiments are performed either with a single isolated NV center or with an unresolved ensemble of many NV centers, resulting in a trade-off between measurement speed and spatial resolution or control over individual defects. In this work, we introduce an experimental platform that bypasses this trade-off by addressing multiple optically resolved NV centers in parallel. We perform charge- and spin-state manipulations selectively on multiple NV centers from within a larger set, and we manipulate and measure the electronic spin states of over 100 NV centers in parallel. We show that the high signal-to-noise ratio of the measurements enables the detection of shot-to-shot pairwise correlations between the spin states of 108 NV centers, corresponding to the simultaneous measurement of 5778 unique correlation coefficients. We discuss how our platform can be scaled to parallel experiments with thousands of individually resolved NV centers. These results enable parallelized high-throughput sensing experiments that retain the spatial resolution of single defects and will, thereby, help to unlock advances in applications such as single-molecule NMR and characterization of integrated circuits. In addition, our approach to multiplexing provides a natural platform for the application of recently developed correlated sensing techniques.

NV centers↗

DOE OSTI2022

Heralded Multiplexed High-Efficiency Cascaded Source of Dual-Rail Entangled Photon Pairs Using Spontaneous Parametric Down-Conversion

Deterministic sources of high-fidelity entangled qubit pairs encoded in the dual-rail photonic basis, i.e., presence of a single photon in one of two orthogonal modes, are a key enabling technology of many applications of quantum information processing, including high-rate, high-fidelity quantum communications over long distances. The most popular and mature sources of such photonic entanglement, e.g., those that leverage spontaneous parametric down-conversion (SPDC) or spontaneous four-wave mixing, generate an entangled (so-called continuous-variable) quantum state that contains contributions from high-order photon terms that lie outside the span of the dual-rail basis, which is detrimental to most applications. One often uses low pump power to mitigate the effects of those high-order terms. However, that reduces the pair generation rate, and the source becomes inherently probabilistic. We investigate a cascaded source that performs a linear-optical entanglement swap between two SPDC sources, to generate a heralded photonic entangled state that has a higher fidelity (to the ideal Bell state) compared to a free-running SPDC source. Furthermore, with the Bell swap providing a heralding trigger, we show how to build a multiplexed source, which despite reasonable switching losses and detector loss and noise, yields a fidelity versus success probability trade-off of a high-efficiency source of high-fidelity dual-rail photonic entanglement. We find, however, that there is a threshold of 1.5 dB of loss per switch, beyond which multiplexing hurts the fidelity versus success probability trade-off.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Ion-chain sympathetic cooling and gate dynamics

Sympathetic cooling is a technique often employed to mitigate motional heating in trapped-ion quantum computers. However, choosing system parameters such as number of coolants and cooling duty cycle for optimal gate performance requires evaluating trade-offs between motional errors and other slower errors such as qubit dephasing. The optimal parameters depend on cooling power, heating rate, and ion spacing in a particular system. In this study, we aim to analyze best practices for sympathetic cooling of long chains of trapped ions using analytical and computational methods. We use a case study to show that optimal cooling performance is achieved when coolants are placed at the center of the chain and provide a perturbative upper bound on the cooling limit of a mode given a particular set of cooling parameters. In addition, using computational tools, we analyze the trade-off between the number of coolant ions in a chain and the center-of-mass mode heating rate. We also show that cooling as often as possible when running a circuit is optimal when the qubit coherence time is otherwise long. These results provide a roadmap for how to choose sympathetic cooling parameters to maximize circuit performance in trapped-ion quantum computers using long chains of ions.

Cooling & trapping↗

DOE OSTI2025

Fundamental limits to the generation of highly displaced bright squeezed light using linear optics and parametric amplifiers

High-quality squeezed light is an important resource for a variety of applications. Multiple methods for generating squeezed light are known, having been demonstrated theoretically and experimentally. However, the effectiveness of these methods—in particular, the inherent limitations to the signals that can be produced—has received little consideration. Here we present a comparative theoretical analysis for generating a highly displaced squeezed light from a linear optical method—a beamsplitter mixing a squeezed vacuum and a strong coherent state—and well-studied parametric amplification methods including an optical parametric oscillator, an optical parametric amplifier, and a dissipative optomechanical squeezer seeded with coherent states. We show that the quality of highly displaced squeezed states that can be generated using these methods is limited on a fundamental level by the physical mechanism utilized; across all methods there are significant trade-offs between displacement, squeezing, and overall uncertainty. We explore the nature and extent of these trade-offs specific to each mechanism and identify the optimal operation modes for each. Finally, we identify the conditions for minimum-uncertainty squeezing in arbitrary parametric amplifying systems and show that displacing the output signal will in general violate these conditions, adding noise and degrading squeezing. Published by the American Physical Society 2025

Young, Steve M. (ORCID:0000000173839366)↗

DOE OSTI2021

Planning for a Resilient Home Electricity Supply System

Resilience of power systems is already a key issue that is getting frequent attention all over the world. It is useful to analyze resilience issues not only for bulk supply, but at all levels including at a customer level. This is because distributed energy resources can play a prominent role in enhancing resilience. Although the literature on planning models, tools and data for bulk supply and distribution systems have expanded in recent years, customer-centric planning, e.g., for an individual household, is yet to receive adequate attention. Although solar PV and battery storage at a household level have been analyzed, how these resources can be optimally combined, together with grid supply, from a resilience perspective is the focus of this study. The study demonstrates how a conceptual framework can be developed to show the trade-off between system costs and resilience including its dimensions such as duration, depth and frequency of service outages. A planning model is developed that incorporates multiple facets of resilience and individual customer preferences. The model considers power system resilience explicitly as a constraint. The model is implemented for a household level case study in Miami, Florida. The results show there are complex trade-offs among different dimensions of resilience. The study demonstrates how combined resilience metrics can be formulated and evaluated using the proposed least-cost planning model at a household level to optimize grid supply together with solar, battery storage and diesel generators. The model allows a planner to directly embed a resilience standard to drive the optimal supply mix. These concepts and the modeling construct can also be applied at other levels of planning, including community level and bulk supply system planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗