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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Cost Drivers and The Most Time-Consuming Activities of the MARVEL Microreactor Project

This study aims to identify what drives cost and what project activities are the most time consuming within a microreactor project such as MARVEL. Identifying these cost and time drivers is necessary since nuclear projects are vulnerable to schedule delays and cost increases. This work also paves the way for possible cost reductions, decreasing the MARVEL levelized cost of energy and reducing the microreactors' construction time which in turn leads to a lower cost of interest during construction

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Ab Initio Modeling of Aqueous Methanol Mixtures at DFT-SCAN Level Using Machine Learning Interatomic Potentials

Abstract Methanol–water mixtures find use in many applications, particularly catalytic energy conversion processes. Their importance has motivated numerous computational studies, most of which employed molecular dynamics based on classical force fields. These enable simulations of large systems on long time scales but do not reliably describe reactive dynamics involving bond breaking and bond formation. In contrast, ab initio molecular dynamics (AIMD) based on density functional theory (DFT) is generally more reliable for such applications but has a high computational cost, which discourages systematic studies of alcohol-water mixtures. To remedy this, we trained a machine learning interatomic potential capable of probing the properties of aqueous methanol mixtures at the DFT level using the SCAN functional. Our results show that SCAN qualitatively reproduces multiple key experimental features arising from the amphiphilic nature of methanol, including density, diffusion coefficients, X-ray structure factors, and Kirkwood–Buff integrals. We also find that structural correlations between water molecules are somewhat overestimated, leading to a stronger preferential association than that predicted by experiments. However, increasing the temperature by 30 K mitigates this effect and also recovers the correct mobilities of both methanol and water. These results indicate that SCAN provides an accurate description of methanol–water mixtures, making it a reliable choice for investigating the reactive dynamics in such systems.

Park, Sanghyun J. [Princeton University , , , ,]↗
DOE OSTI2021

Excitonic effects in absorption spectra of carbon dioxide reduction photocatalysts

Abstract The formation and disassociation of excitons play a crucial role in any photovoltaic or photocatalytic application. However, excitonic effects are seldom considered in materials discovery studies due to the monumental computational cost associated with the examination of these properties. Here, we study the excitonic properties of nearly 50 photocatalysts using state-of-the-art Bethe–Salpeter formalism. These ~50 materials were recently recognized as promising photocatalysts for CO 2 reduction through a data-driven screening of 68,860 materials. Here, we propose three screening criteria based on the optical properties of these materials, taking excitonic effects into account, to further down select six materials. Furthermore, we study the correlation between the exciton binding energies obtained from the Bethe–Salpeter formalism and those obtained from the computationally much less-expensive Wannier–Mott model for these chemically diverse ~50 materials. This work presents a paradigm towards the inclusion of excitonic effects in future materials discovery for solar-energy harvesting applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Forest residue harvest optimization: spanning the bridge between plant biology and biorefinery performance

Forestry residues have immense potential as alternative feedstocks to petroleum, yet their inherent complexity remains a major challenge to widespread use. Pairing the temporal rhythms of plant biology with biorefinery performance is critical to industrial-scale biorefinery development. Here, we provide the first report of a techno-economic analysis (TEA) and life cycle assessment (LCA) for a model integrated reductive catalytic fractionation (RCF)–molten salt hydrolysis process for forestry residues varying in tree part, species, and phenophase. All forestry residues resulted in net-negative greenhouse gas (GHG) emissions vs. comparable petroleum feedstocks, with GHG emissions potentially reduced >4.0× through composition-based feedstock selection (e.g., harvesting American beech bark in spring vs. summer). Moreover, American beech twigs/branchlets and bark in leafed and emergence phenophases, respectively, had 7.9× lower predicted phenolic minimum selling prices (MSPs) vs. other feedstocks and MSPs within the current global phenolic market range. Hemicellulose content and RCF yield emerged as key parameters impacting GHG emissions and biorefinery revenue, identifying hardwood twigs/branchlets in the leafed phenophase as optimal biofeedstocks. Biorefinery expenses were dominated by purchased equipment, raw materials, and utility costs, highlighting essential areas for future study. Notably, RCF reactor pressures drove 85–90% of equipment costs, but sensitivity analysis revealed that decreasing the pressure 20% could reduce the phenol MSP 4-fold. Structural carbohydrate dynamics were also investigated using a two-step acid hydrolysis method to resolve tissue- and species-level patterns in biomass composition throughout the year to enable harvest optimization based on TEA/LCA findings. Ultimately, elucidating the impact of biofeedstock dynamics on biorefinery performance enables harvest optimization, informed engineering design, and progress towards an expanded bioeconomy.

Shapiro, Alison J. [University of Delaware, Newark↗
DOE OSTI2020

Engine-in-the-Loop Study of a Hierarchical Predictive Online Controller for Connected and Automated Heavy-Duty Vehicles

This paper presents a cohesive set of engine-in-the-loop (EIL) studies examining the use of hierarchical model-predictive control for fuel consumption minimization in a class-8 heavy-duty truck intended to be equipped with Level-1 connectivity/automation. This work is motivated by the potential of connected/automated vehicle technologies to reduce fuel consumption in both urban/suburban and highway scenarios. The authors begin by presenting a hierarchical model-predictive control scheme that optimizes multiple chassis and powertrain functionalities for fuel consumption. These functionalities include: vehicle routing, arrival/departure at signalized intersections, speed trajectory optimization, platooning, predictive optimal gear shifting, and engine demand torque shaping. The primary optimization goal is to minimize fuel consumption, but the hierarchical controller explicitly accounts for other key objectives/constraints, including operator comfort and safe inter-vehicle spacing. This work is experimentally experimentally validated via a sequence of EIL studies intended for evaluating the computational costs and fuel savings associated with these algorithms. These EIL studies involve the closed-loop validation of the proposed control strategies, both individually and combined. These studies show that this hierarchy of algorithms is capable of running online, with the round-trip communication delay inherent in EIL simulation being one of the key factors affecting the EIL results. Moreover, the EIL studies are encouraging, both in terms of the successful hierarchical integration of the underlying algorithms and also in the resulting fuel savings seen in the EIL tests. In particular, the EIL results suggest that an aggressive overall goal of reducing vehicle fuel consumption by 15-20% or more is potentially achievable, especially in urban/suburban scenarios.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Low-Cost Sulfur Thermal Storage for Increased Flexibility and Improved Economics of Fossil-Fueled Electricity Generating Units (Final Report)

The US electric grid relies on conventional fossil fuel power plants for reliable and secure power, but these plants suffer from physical and financial strain due to the influx of inexpensive and variable solar and wind electricity. Conventional power plants need to generate electricity flexibly and on-demand to accommodate these renewable resources on the grid. Integrating a low-cost thermal energy storage (TES) gives fossil assets the ability to regulate their output efficiently and optimize the plant operation to maximize revenue in the wholesale electricity market. Element 16’s TES concept uses sulfur, a byproduct of the oil & gas industry, as the storage media that is 10 times cheaper than molten salt used in commercial two-tank TES technology. In this project, the team completed a detailed feasibility and technoeconomic study establishing the impact, cost and performance of molten sulfur TES system integrated with fossil assets.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Energy Paths for the Yurok People

The Yurok Tribe has been working for more than two decades to bring adequate, cost-effective energy services to their Tribal members. With the completion of the electric line extension to Wautec, they are well on their way to an effective and sustainable energy future. However, there is still much work to be done; many Tribal households in the Upper Reservation are still without reliable, affordable electric power. Now the Tribe needs to determine the next steps to realize their energy vision. This Yurok Tribe energy strategic planning study examined electricity usage, costs and infrastructure, as well as electricity needs on the Reservation. It also assessed the Tribe’s energy resources. Equipped with this information, the project team conducted an energy options analysis that examined different project opportunities and identified key projects that are both feasible to implement and will help the Tribe reach its stated Energy Vision. There are still numerous households in the Upper Reservation and adjacent lands that are without grid electric power, and it is likely that most of them will remain disconnected from the grid because of their remoteness. To provide these community members with reliable, affordable, modern energy services their homes will need to be electrified via a robust off-grid energy services program that installs and maintains off-grid energy systems. This is the key need that is explored and addressed in this plan.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Optimizing Phase Change Composite Thermal Energy Storage Using the Thermal Ragone Framework

The thermal Ragone framework can be applied to the design of thermal energy storage heat exchangers to identifying relationships between their power requirements and energy capabilities. This presentation focuses on the design of planar thermal energy storage heat exchangers with phase change materials and thermal conductivity additives. Finite-difference models were used to optimize thermal storage heat exchanger designs focusing on key design parameters of conductivity additive volume fraction, spacing between tubes, and the phase transition temperatures. Design trends were developed for optimal designs based on varying thermal power requirements. To aid in future device design, models of reduced complexity were developed with the ability to predict optimal designs with computational speeds up to 5,000 times faster than finite-difference models.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗
DOE OSTI2026

A comparative assessment of the economic viability of nuclear-integrated direct air capture systems

Direct air capture (DAC) systems require heat and electricity to operate, which can be supplied by nuclear power plants (NPPs). In this study, the performance and cost of various conceptual nuclear-DAC systems are assessed, and their performance is compared with several non-nuclear options. Three nuclear-DAC systems are considered: (1) a liquid solvent direct air capture (L-DAC) system with heat supplied from natural gas (NG) and electricity supplied by an NPP, (2) an electrified L-DAC system, fully powered by electricity from an NPP, and (3) a solid sorbent direct air capture (S-DAC) system utilizing both heat and electricity generated by an NPP. Two nuclear technologies are considered: a pressurized water reactor and a high-temperature gas-cooled reactor. Under the medium conservatism scenario, the levelized cost of direct air capture (LCOD) for these systems range from $\$$310/tCO 2 to $\$$525/tCO 2 with the L-DAC system having an NG heat supply at the lower end of the range, and the electrified L-DAC system and the S-DAC system at the higher end of the range. Coupling with nuclear energy led to a 21 % reduction in LCOD for the L-DAC system with NG heat supply and a 29 % reduction for the S-DAC system when compared to fully NG-powered options. When powering the DAC system with grid electricity, the LCOD is highly dependent on the assumed electricity price and carbon intensity. The nuclear option is the cheaper choice when the price of low-carbon grid electricity exceeds $\$$95/MWh and $\$$45/MWh for the L-DAC and S-DAC systems, respectively.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Parametric and Nonparametric Models of U.S. Cost Overruns for Nuclear Power Plants

This study presents new data-driven models to estimate the effect of capacity on the percentage of cost overruns in the United States for nuclear power plant construction projects before and after the Three Mile Island accident. Parametric and nonparametric models have been developed that describe the significant shifts in nuclear energy costs during the dynamic environment. Employing a contemporary descriptive methodology and a quantitative analysis, we furnish a comprehensive overview of the alterations in cost overrun distribution and show the changes observed in other pivotal metrics alongside cost overruns. Our emphasis lies in documenting the fluctuations in cost overruns alongside nuclear reactor capacity levels and the increase of the overnight capital costs to build nuclear reactors. Our results show that increasing the size of nuclear reactors is not a factor statistically significant to decrease the percentage of cost overruns, and the probit model results provide evidence that an increase in size increases the probability of having cost overruns larger than 100% (double the estimated cost). We also compare our findings to two other regions: Asia and Europe.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

C-C Coupling Mechanism on Cu(100) A Molecular Dynamics Study at 298K

The electrochemical reduction of carbon dioxide (CO2) into valuable fuels such as C1 (syngas, methane) and C2 (ethylene, ethanol) products is a key strategy for achieving a carbon-neutral economy. Computational studies of C-C coupling, a critical step in CO2 reduction, are essential for designing more efficient catalysts. However, simulating these processes under realistic electrochemical conditions, including temperature and solvent effects, is computationally demanding. In this work, we develop a machine learning-based atomistic potential to study CO2 reduction on Cu(100) surfaces, accounting for temperature and explicit water solvent effects. We compute thermodynamic free energies of the possible C-C coupling pathways, CO*+CO*→OCCO*, CO*+CHO*→OCCHO*, CO*+COH*→OCCOH*, CHO*+COH*→OHCCOH*, COH*-COH*→HOCCOH*, and CHO*-CHO*→OHCCHO*. Our results quantify the thermodynamic tendencies of these reactions and reveal that, in addition to the well-established CO* + CO* → OCCO* pathway, CHO* is a critical intermediate in the formation of C2 products on Cu(100). Furthermore, we demonstrate that the machine learning approach offers a cost-efficient framework for studying CO2 reduction on diverse catalysts under realistic electrochemical conditions.

machine learning↗
DOE OSTI2023

Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition

Over the past decade, the machine learning security community has developed a myriad of defenses for evasion attacks. An understudied question in that community is: for whom do these defenses defend? This work considers common approaches to defending learned systems and how security defenses result in performance inequities across different sub-populations. We outline appropriate parity metrics for analysis and begin to answer this question through empirical results of the fairness implications of machine learning security methods. We find that many methods that have been proposed can cause direct harm, like false rejection and unequal benefits from robustness training. The framework we propose for measuring defense equality can be applied to robustly trained models, preprocessing-based defenses, and rejection methods. We identify a set of datasets with a user-centered application and a reasonable computational cost suitable for case studies in measuring the equality of defenses. In our case study of speech command recognition, we show how such adversarial training and augmentation have non-equal but complex protections for social subgroups across gender, accent, and age in relation to user coverage. We present a comparison of equality between two rejection-based defenses: randomized smoothing and neural rejection, finding randomized smoothing more equitable due to the sampling mechanism for minority groups. This represents the first work examining the disparity in the adversarial robustness in the speech domain and the fairness evaluation of rejection-based defenses.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2020

Investigating the effect of different shielding gas mixtures on microstructure and mechanical properties of 410 stainless steel fabricated via large scale additive manufacturing

Metal Big Area Additive Manufacturing (mBAAM) offers the potential to fabricate large scale tools at high deposition rates (15 lb/h+). 410 martensitic steel is a potential tooling material, owing to its low cost, good machinability and reasonable printability. During the mBAAM process, the shielding gas can have a significant impact on the material properties as well as the process cost. Therefore, the current study aims to understand the effect of different shielding gas mixtures on large-scale additive manufacturing of 410 martensitic stainless steel. We show that an argon mixture with 3% nitrogen gas produced the best performance in terms of maximum hardness and tensile strength, with much less scatter in tensile strength. He-Ar-CO 2 or tri-mix shielded samples showed a low tensile strength with wide scatter, due to stabilized delta ferrite in microstructure during printing. Both tri-mix and Ar-CO 2 shielded samples showed slightly higher porosity. Thus, we recommend the use of argon-3% nitrogen as a shielding gas mixture for processing 410 steel for tool applications, based on the relatively low cost of this gas mixture and the resulting higher hardness, higher dimensional stability, and lower porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Solid-State Transformer and Hybrid Transformer With Integrated Energy Storage in Active Distribution Grids: Technical and Economic Comparison, Dispatch, and Control

Solid-state transformer (SST) and hybrid transformer (HT) are promising alternatives to the line-frequency transformer (LFT) in smart grids. The SST features medium-frequency isolation, full controllability for voltage regulation, reactive power compensation, and the capability of battery energy storage system (BESS) integration with multiport configuration. The HT has a partially-rated converter for fractional controllability and can integrate a small BESS. Fast grid-edge voltage fluctuations from increased solar photovoltaic (PV) and electric vehicle (EV) penetration are difficult to manage for mechanical load tap changers. Hence, along with the trend towards more BESS in the grid, the controllability and the storage integration capability of the SST and HT are of strong interest. However, a review of literature shows existing SST and HT research is mostly at converter level, while system-level assessments are scarce. Assessing technical and economic impacts is critical to understanding the benefits and role of the SST and HT to guide future research, which is presented for the first time in this article. Experimental results from medium-voltage (MV) SST and MV HT prototypes are shown to confirm equipment-level feasibility, where the voltage controllability waveforms of a MV HT prototype are reported for the first time. Comparative simulations are performed on a modified IEEE 34-bus system. Here, a grid-model-less decentralized grid-edge voltage control method and a day-ahead BESS dispatch method are proposed for the SST and HT. The simulations show that the SST and HT with integrated storage can host more PV, achieve peak shaving, mitigate voltage fluctuation and reverse power flow, and support energy arbitrage for operational cost reduction, as compared to the LFT. Moreover, comprehensive analyses of net present value (NPV) and internal rate of return (IRR) are performed under different installed PV capacities, HT’s partial converter ratings, and BESS capacities. Sensitivities to future cost reductions of the PV and BESS are studied. Although the NPV and IRR are currently negative, 60% capital cost reduction or 150% revenue increase will make the SST and HT economically viable in the use case studied.

14 SOLAR ENERGY↗
DOE OSTI2022

Operational Probabilistic Tools for Solar Uncertainty (OPTSUN) (Final Project Report for DOE Solar Forecasting II Project)

Increasing levels of solar PV can challenge system operations and may require novel methods to operate the power system reliably and efficiently. Power system operating plans generally use deterministic forecasts, in which the variable energy resources are represented by the expected value for each interval of the decision horizon. Probabilistic forecasts are relatively new but have the potential to address the shortfalls of deterministic forecasts. However, understanding how best to use such forecasts is still a key gap in industry and was the focus of this project. The project had three workstreams. In a forecasting workstream, improvements were made to baseline probabilistic forecasts using a number of new approaches such as machine learning methods and improved input data. In a design workstream, advanced simulation tools used these forecasts to investigate newly proposed reserve determination methods. Lastly, in a demonstration workstream a scheduling management platform (SMP) was developed to leverage probabilistic forecasts in a modular and customizable manner. In order to study the benefits that could be accrued, the project team collaborated with three utility partners (Duke Energy, Southern Company and Hawaiian Electric) to deliver improved probabilistic forecasts for each region and to model each region in case studies using advanced production cost modeling tools. Different methods to determine operating reserve requirements from probabilistic forecasts were developed, simulated, and tested across each region. The benefits of using these newly proposed methods varied by utility, but, in general, using probabilistic forecasts as well as historical data to set the reserve requirements seems to improve reliability related results, with less risk of reserve or supply shortfalls. The cost implications were not always straightforward; in some cases the new methods could show a reduction in expected operating costs, but often the increase in reserves associated with better risk mitigation using probabilistic forecasts could result in an increase in operating costs in the simulations. The SMP tool was developed to process probabilistic forecasts from their initial receipt through to scheduling decisions. This open-source tool consists of several modules for scenario development, reserve requirements calculation, and visualization. The SMP tool was demonstrated to a wide range of operators and stakeholders at all three utilities and further improved based on their feedback. The tool will be available on www.epri.com/optsun. The proposed probabilistic information-based reserve determination approaches have the potential to be implemented by different regions to ensure an economic and reliable power system operation on power systems integrating increasing levels of variable renewable resources. The innovative yet practical methods developed in this project demonstrated tangible benefits from using probabilistic forecasts beyond just study-based assessments to include three unique balancing areas. The demonstrated benefits across the multiple utility environments, are expected to provide system operators in all regions the confidence required and a platform to adopt the new forecasting and operating methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Parabolic Trough Collector Cost Update for Industrial Process Heat In The United States

Despite great potential, the worldwide adoption of concentrating solar thermal (CST) collectors for solar industrial process heat (SIPH) is modest. Industrial process heat (IPH) demands for heat and steam are typically below 300 degrees C, where CST collectors can provide the needed heat. Parabolic trough collectors (PTCs) are the most deployed CST technology for SIPH applications. This paper is focused on the United States, and a summary of known operating parabolic trough plants is shown. A previous analysis of a modern PTC in 2016 found that for SIPH applications, the installed solar field cost could be $200/m2 (2016$). Recent advances in PTC design and manufacturing have led to reduced cost per square meter of aperture area, and for a field of 510 solar collector assemblies (SCAs), the installed cost was $120/m2 (2020$). On one hand, the results from this study showed that the solar field cost for large solar fields (510 SCAs or ~804,000 m2) would increase to $184/m2 (2023$) due to post pandemic inflation and increase in metal prices. On the other hand, medium SIPH sized fields (90 SCAs or ~142,000 m2) cost analysis indicated an installed cost could be $197/m2 (2023$). When small SIPH fields (12 SCAs or ~19,000 m2) are considered, this jumps to $297/m2 (2023$). These are cost estimates for the Installed Cost of the solar fields using the United States 2023$ steel prices. When Chinese steel is used for comparison, the installed cost could be between $162 - $210/m2 for the range of SIPH sizes.

concentrating solar thermal↗
DOE OSTI2023

Advanced Fuel Cycle Cost Basis Report: Module D1-4 and Module D1-5 Ceramic Pelletized Sodium-Cooled Fast Reactor (SFR) Fuel Fabrication Ceramic Vibrocompacted Fuel Fabrication

This is a cost module that is part of the Advanced Fuel Cycle -- Cost Basis Report. Module D1-4: Nature of this module update (Rev 1) from previous advanced fuel cycle cost basis reports (AFCCBRs): new life cycle cost data on U,Pu SFR mixed oxide (MOX) fuels is derived from the Nonproliferation Assessment Systems Analysis Program (NASAP) conducted in the late 1970s. Highassay low-enriched uranium (HALEU) ceramic fuel is also discussed in more detail compared to earlier AFC-CBRs, since some advanced SFR concepts currently under development will require this HALEU fuel type for startup. Module D1-5: Nature of this FY-21 module update from previous AFC-CBRs: this module includes a few new references and a somewhat expanded discussion of vibrocompaction fuel fabrication technology. The WIT values for VIPAC are pegged directly to those for conventional LWR and SFR pelletized U,Pu MOX (note that this module now includes VIPAC MOX fuel for LWRs in addition to SFRs). Based on information from Russia, where VIPAC has been studied extensively, the unit costs are expressed as a percentage of those in the new updated Module D1-2 (pelletized U,Pu MOX) and new updated Module D1-4 (pelletized U,Pu MOX) for large NOAK fabrication facilities of the same production capacity. Since both ceramic pelletized MOX Modules D1-2 and D1-4 benefitted from analysis of 1970s NASAP data, by extension this Module D1-5 also benefits.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗