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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

2024 Milestone Report: Site 300 mPDV Optical Fiducials

In the early 2000s Photon Doppler Velocimetry (PDV) replaced the Fabry-Perot many beam system1 and has since become ubiquitous across dynamic experimental platforms to measure velocity and event times such as shock breakout, key variables for high pressure physics research. The advent of optically multiplexed oscilloscope channels to create multiplexed PDV (mPDV) increased portability and reduced price per data point. However, these advantages came with the cost of additional fielding complexity and thermally induced timing drift, which directly affects the ability to use PDV for high precision time measurement. Controlling the temperature or incorporating optical fiducials allows researchers to characterize, reduce, and correct this thermal drift in analysis. Our implemented optical fiducial or “timing marker” allows us to reduce thermal drift uncertainty from the 10s of nanoseconds down to the 100s of picoseconds with minimal added complexity to existing systems. The implementation of this timing marker normalizes uncertainty across optical delays, brings our facility cross timing into the sub nanosecond regime and lets us identify/study anomalies in our data. This improvement increases experiment reliability and quality enabling a new class of high precision experiments at S300.

42 ENGINEERING↗

Stellar Mergers or Truly Young? Intermediate-age Stars on Highly Radial Orbits in the Milky Way’s Stellar Halo

Reconstructing the mass assembly history of the Milky Way relies on obtaining detailed measurements of the properties of many stars in the galaxy, especially in the stellar halo. One of the most constraining quantities is stellar age, as it can shed light on the accretion time and quenching of star formation in merging satellites. However, obtaining reliable age estimates for large samples of halo stars is difficult. We report published ages of 120 subgiant halo stars with highly radial orbits that likely belong to the debris of the Gaia-Enceladus/Sausage (GES) galaxy. The majority of these halo stars are old, with an age distribution characterized by a median of 11.6 Gyr and a 16th (84th) percentile of 10.5 (12.7) Gyr. However, the distribution is skewed, with a tail of younger stars that span ages down to ~6–9 Gyr. All highly radial halo stars have chemical and kinematic/orbital quantities that associate them with the GES debris. Initial results suggest that these intermediate-age stars are not a product of mass transfer and/or stellar mergers, which can bias their age determination low. If this conclusion is upheld by upcoming spectrophotometric studies, then the presence of these stars will pose an important challenge for constraining the properties of the GES merger and the accretion history of the galaxy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Optimal Operations Management of Mobility-on-Demand Systems

The emergence of the sharing economy in urban transportation networks has enabled new fast, convenient and accessible mobility services referred to as Mobilty-on-Demand systems (e.g., Uber, Lyft, DiDi). These platforms have flourished in the last decade around the globe and face many operational challenges in order to be competitive and provide good quality of service. A crucial step in the effective operation of these systems is to reduce customers' waiting time while properly selecting the optimal fleet size and pricing policy. In this paper, we jointly tackle three operational decisions: (i) fleet size, (ii) pricing, and (iii) rebalancing, in order to maximize the platform's profit or its customers' welfare. To accomplish this, we first devise an optimization framework which gives rise to a static policy. Then, we elaborate and propose dynamic policies that are more responsive to perturbations such as unexpected increases in demand. We test this framework in a simulation environment using three case studies and leveraging traffic flow and taxi data from Eastern Massachusetts, New York City, and Chicago. Our results show that solving the problem jointly could increase profits between 1% and up to 50%, depending on the benchmark. Moreover, we observe that the proposed fleet size yield utilization of the vehicles in the fleet is around 75% compared to private vehicle utilization of 5%.

Wollenstein-Betech, Salomón↗

Incorporation of market signals for the optimal design of post combustion carbon capture systems

Recent studies have shown that fossil generators equipped with post-combustion carbon capture (PCC) systems are needed to reduce the cost of deep decarbonization. Such generators need to be flexible and responsive to grid conditions, particularly in a high variable renewable energy (VRE) environment. In this work, we evaluate the net present value (NPV) of retrofitting an existing natural gas combined cycle (NGCC) unit with a flexible PCC system while incorporating market signals from a high VRE grid. We use our industrial partner’s NGCC configuration as representative of existing NGCC units and Svante’s rapid-temperature swing adsorption (TSA) for PCC. Because of its ability to rapidly startup/shutdown and ramp-up/ramp-down, the chosen capture technology is very attractive for load-following operations. For a given set of market signals, we formulate a two-stage stochastic multi-period optimization problem, under the price-taker assumption, to simultaneously optimize the design of the capture system and operation of the entire plant. Rigorous models for the NGCC unit, PCC system, and compression system are developed using commercial process simulators and validated with either plant or vendor data. For computational tractability, we develop surrogate/reduced-order models for use in the optimization problem. The surrogate model for the NGCC plant is constructed by linearizing the rigorous dynamic model at 75% load, while data-driven nonlinear surrogate models for the capture and compression systems are constructed using simulation data from the rigorous models. The optimization problem, formulated as a mixed integer bilinear program, is implemented in the IDAES® integrated platform and solved to global optimality using Gurobi 9.5. Using this formulation, we determine the profitability of retrofitting an existing NGCC unit with the chosen capture system for multiple regions in the U.S. under two scenarios with different carbon prices. Importantly, the results show that the optimal decision strongly depends on the region and on the carbon price, thereby demonstrating the importance of the inclusion of market signals in the design process.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Interplays In The Rare Earth Element Value Chain

An imbalance problem exists in the rare earth element (REE) market with cerium and lanthanum being more abundant and less valuable than REEs used in permanent magnets such as neodymium, praseodymium, and dysprosium. Research has been conducted on new applications for abundant REEs to improve mining economics. However, potential market impacts of these applications on individual REE commodities are unknown. A system dynamics model was built to investigate the impacts of a new aluminum-cerium (Al-Ce) alloy that can theoretically utilize three separate cerium forms: cerium carbonate, cerium oxide, or cerium metal. Cerium carbonate currently possesses the lowest price of the three available forms making it initially the most favorable choice. However, model results showed that cerium oxide could provide the best economics for future Al-Ce alloy deployment because its larger market size buffers major shocks to price.

Severson, Michael [Idaho National Laboratory (INL)↗

Net Present Value Optimization of a Natural Gas Combined Cycle Plant with CO 2 Capture using a Water-Lean Solvent Considering Transient Electricity Price for Multiple Regions

Global CO 2 emissions are increasing at about a 1.5% rate per year. Fossil fuel-based plants are one of the main contributors to this rise. In the power generation industry, fossil fuel plants are dominant, and many plants are under development. In this study, a natural gas combined cycle (NGCC) power plant with postcombustion capture using a leading water-lean solvent is considered. For optimal design and operating schedule, large-scale dynamic optimization is undertaken for net present value (NPV) optimization. The first principle dynamic model of NGCC is developed, including a model of the highly efficient H-class gas turbines. For computational tractability of the dynamic optimization problem, a reduced-order model is developed by using the Hankel singular value decomposition. A waterlean solvent, N-(2-ethoxyethyl)-3-morpholinopropan-1-amine, is used for carbon capture. A model of the capture system is developed in Aspen Plus, which is used to develop a reduced-order model by using ALAMO, a machine learning software. In addition, a reduced model of the CO 2 compression system with a dehydration unit is also considered. The integrated system is used for NPV optimization by using the Python-based PYOMO platform. The PCC process is analyzed for three configurations-conventional packed bed, rotating packed bed (RPB), and a combination of RPB and direct contact cooler. The NPV optimization is performed for 14 regional markets by considering year-long clustered and continuous locational marginal price data with a 1 h interval. Optimization results show that the PCC can achieve 90% CO 2 capture with a positive NPV for six regions. Sensitivity studies conducted by using the PCC configurations indicate that the process is economically feasible for 9 regions out of 14 regional electricity markets with NPV values in the range of 33−540 $MM.

cabon capture↗

Distributed Energy Resource (DER) Integration Framework: Regulatory Innovation for DER Compensation and Cost Allocation

Existing regulatory approaches to DER lack the precision and granularity necessary to ensure that DER can continue to scale in a cost-effective manner that is aligned with the public interest. To address this need, with the support of the U.S. Department of Energy’s Office of Electricity, Berkeley Lab and Current Energy Group developed an illustrative regulatory framework. By adopting a technology-neutral and modular approach, the framework enables flexibility and scalability for DER providers, utilities, and regulators. Clear price signals and incentives encourage the provision of valuable grid services, while equitable cost allocation promotes efficient use of distribution capacity and interconnection resources. This approach mirrors traditional ratemaking principles for importing customers and positions DERs as integral components of a dynamic and cost-effective energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimizing cost-effective and benchmarked industry standards to quantify nutrient bioextraction by seaweed

Interest in the utility of seaweed farms to mitigate coastal eutrophication, or nutrient loading, has grown commensurate with the recent rise of the farmed seaweed industry in the U.S. But economic valuation of this ecosystem service remains elusive in part because of challenges in quantifying this spatiotemporally variable biological process with reproducible and comparable metrics. Regulatory bodies that permit wastewater discharge or lease area for aquaculture farms require water quality testing and reporting of dissolved total nitrogen (N) in nearshore marine environments. These metrics must meet EPA standards for testing and reporting (e.g., Total Kjeldahl Nitrogen - TKN). However, these metrics are inherently highly variable over space and time in dynamic nearshore systems, and expensive to evaluate with sufficient breadth to constrain this variance, creating a critical bottleneck to direct quantification of farmed seaweed net uptake rates in situ.

59 BASIC BIOLOGICAL SCIENCES↗

ESCARGOT: Mapping Vertical Phase Spiral Characteristics Throughout the Real and Simulated Milky Way

Abstract The recent discovery of a spiral pattern in the vertical kinematic structure in the solar neighborhood provides a prime opportunity to study nonequilibrium dynamics in the Milky Way from local stellar kinematics. Furthermore, results from simulations indicate that even in a limited volume, differences in stellar orbital histories allow us to trace variations in the initial perturbation across large regions of the disk. We present ESCARGOT , a novel algorithm for studying these variations in both simulated and observed data sets. ESCARGOT automatically extracts key quantities from the structure of a given phase spiral, including the time since perturbation and the perturbation mode. We test ESCARGOT on simulated data and show that it is capable of accurately recovering information about the time since the perturbation occurred as well as subtle differences in phase spiral morphology due to stellar locations in the disk at the time of perturbation. We apply ESCARGOT to kinematic data from data release 3 of the Gaia mission in bins of guiding radius. We show that similar structural differences in morphology occur in the Gaia phase spirals as a function of stellar orbital history. These results indicate that the phase spirals are the product of a complex dynamical response in the disk with large-scale coupling between different regions of phase space.

Darragh-Ford, Elise (ORCID:0000000288005652)↗

PyDA: A Hands-On Introduction to Dynamical Data Assimilation with Python

Dynamic data assimilation offers a suite of algorithms that merge measurement data with numerical simulations to predict accurate state trajectories. Meteorological centers rely heavily on data assimilation to achieve trustworthy weather forecast. With the advance in measurement systems, as well as the reduction in sensor prices, data assimilation (DA) techniques are applicable to various fields, other than meteorology. However, beginners usually face hardships digesting the core ideas from the available sophisticated resources requiring a steep learning curve. In this tutorial, we lay out the mathematical principles behind DA with easy-to-follow Python module implementations so that this group of newcomers can quickly feel the essence of DA algorithms. We explore a series of common variational, and sequential techniques, and highlight major differences and potential extensions. We demonstrate the presented approaches using an array of fluid flow applications with varying levels of complexity.

97 MATHEMATICS AND COMPUTING↗

An Atlas of Current Customer-Facing Utility Program Designs and Pricing

The National Renewable Energy Laboratory (NREL) and Kevala conducted a targeted literature review and leveraged extensive expertise, including team members with four decades of experience in the utility sector, to characterize utility programs and rate designs. This analysis delves into the motivations behind these programs and the various hurdles they face. Through this in-depth study, the team provides critical insights into the operational dynamics of utility programs, identifying key drivers and barriers that influence their effectiveness and implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Solid State Power Substation DC Node Optimization and Controller Hardware-In-The-Loop Demonstration

A solid state power substation (SSPS) node is a microgrid that integrates distributed energy resources and loads and injects/absorbs power to/from the SSPS distribution network. It is an essential building block of a futuristic distribution grid network. This paper presents the development and demonstration of optimization use cases of a SSPS DC node. By adopting multi-layer hierarchical control architecture and developing automatic device identification and dynamic optimization formulation algorithms, the SSPS DC node can perform plug-and-play resource integration and seamless transition of the optimized node operation under on and off grid condition without sophisticated algorithms, control mode changes, and user interactions. Four optimization use cases including economic dispatches with price signal changes, a sudden PV power drop, and a single directional meter and its associated costs with sending power back to the grid, and resiliency under a grid inverter trip condition were demonstrated through the real-time controller hardware-in-the-loop simulation.

Kim, Namwon↗

INITIAL EXPLORATION OF A NOVEL TRANSIENT ARREST SYSTEM INVOLVING FUEL HEATING

A preliminary analysis on a novel accident response system to diminish the severity of supercritical transients was conducted. The novel accident response system, called the instant shock arrest system, involves using electricity to heat the nuclear fuel at the onset of a large accidental reactivity insertion. This system is specifically designed for reactors with metallic fuel, such that the fuel is capable of conducting electricity, and being resistively heated. A reactor dynamics model of the advanced test reactor was created using the point kinetics equations and a linear reactivity feedback model to simulate how the system would effect the maximum fuel temperatures experienced during the transient. Transients with the instant shock arrest system were compare to those without it. It was found that the instant shock arrest system initially heated the fuel more than the unaffected transient but the negative reactivity inserted from such heating was enough to lower the maximum fuel temperature experienced during the transient. After simulating six different accident scenarios with reactivity insertions ranging from 0.5 \$ to 1.3 \$, it was found that the an optimal system response could reduce peak fuel temperatures during the transient by 3.5\% to 5\%. Furthermore, discussion was given on how the optimal system response could be obtained using relatively simple numerical optimization algorithms due to the smoothness of the optimization problem.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

INITIAL EXPLORATION OF A NOVEL TRANSIENT ARREST SYSTEM INVOLVING FUEL HEATING (Presentation)

A preliminary analysis on a novel accident response system to diminish the severity of supercritical transients was conducted. The novel accident response system, called the instant shock arrest system, involves using electricity to heat the nuclear fuel at the onset of a large accidental reactivity insertion. This system is specifically designed for reactors with metallic fuel, such that the fuel is capable of conducting electricity, and being resistively heated. A reactor dynamics model of the advanced test reactor was created using the point kinetics equations and a linear reactivity feedback model to simulate how the system would effect the maximum fuel temperatures experienced during the transient. Transients with the instant shock arrest system were compare to those without it. It was found that the instant shock arrest system initially heated the fuel more than the unaffected transient but the negative reactivity inserted from such heating was enough to lower the maximum fuel temperature experienced during the transient. After simulating six different accident scenarios with reactivity insertions ranging from 0.5 \$ to 1.3 \$, it was found that the an optimal system response could reduce peak fuel temperatures during the transient by 3.5% to 5%. Furthermore, discussion was given on how the optimal system response could be obtained using relatively simple numerical optimization algorithms due to the smoothness of the optimization problem.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Optimal renormalization of multiscale systems

While model order reduction is a promising approach in dealing with multi-scale time-dependent systems that are too large or too expensive to simulate for long times, the resulting reduced order models can suffer from instabilities. We have recently developed a time-dependent renormalization approach to stabilize such reduced models. In the current work, we extend this framework by introducing a parameter that controls the time-decay of the memory of such models and optimally selecting this parameter based on limited fully resolved simulations. First, we demonstrate our framework on the inviscid Burgers equation whose solution develops a finite-time singularity. Our renormalized reduced order models are stable and accurate for long times while using for their calibration only data from a full order simulation before the occurrence of the singularity. Furthermore, we apply this framework to the 3D Euler equations of incompressible fluid flow, where the problem of finite-time singularity formation is still open and where brute force simulation is only feasible for short times. Our approach allows us to obtain for the first time a perturbatively renormalizable model which is stable for long times and includes all the complex effects present in the 3D Euler dynamics. We find that, in each application, the renormalization coefficients display algebraic decay with increasing resolution, and that the parameter which controls the time-decay of the memory is problem-dependent.

Price, Jacob↗

Pathways of clean energy heating electrification programs for reducing carbon emissions in Northwest China

We report clean energy heating electrification programs provide a promising way to reduce carbon emissions from fossil fuel combustion and consumption. This work studies the cost competitiveness of clean energy heating technologies under three dynamic mechanisms: investment costs, subsidy policies, and operating costs with real data. It provides key insights into the cost competitiveness of the different heating technologies deployed in different areas, as well as their sensitivity to the three dynamic mechanisms. The results show that currently, the distinct heating programs are more cost-efficient in the urban area with existing heating networks. The average payback period of all district clean energy heating programs in the urban area is 14.9 years, while that of the individual clean heating programs is 24.7 years. The individual heating programs are becoming increasingly cost-competitive with the incentive mechanisms, especially the electricity pricing mechanisms. Moreover, individual heating technologies present remarkable advantages on flexibility and sustainability in the long run. According to the technology diffusion model proposed in this paper, the individual clean heating programs will occupy more than 50% of the market share in 2050 under the comprehensive effect of CAPEX, government subsidies, and OPEX. The real-world results and analysis render references to shape the pathway of clean energy heating electrification in Northwest China and other regions with a similar situation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗