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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Transportation Energy Analytics Dashboard (TEAD)

The investment decisions within the nation’s transportation sector have traditionally been prioritized and measured against safety and travel efficiency goals. Increasingly, federal, state, and local policies are requiring consideration of energy use and emissions in the design of our transportation infrastructure. Yet the processes, analytics, and knowledge to include these new metrics into transportation decisions are lacking. Although targeted studies and before and after analysis are performed from time to time, no comprehensive real-time monitoring systems provide energy and emissions to the same level as congestion and safety. To address this gap, the Center for Advanced Transportation Technology (CATT Lab) and the Maryland Transportation Institute (MTI) at the University of Maryland (UMD), in partnership with the National Renewable Energy Laboratory (NREL), have developed a Transportation Energy Analytics Dashboard, or TEAD, to raise awareness of the energy and emission impacts to the same level of observability as that of safety and mobility concerns. The overall goal of this project was to develop and demonstrate an online tool to monitor transportation energy use and emissions in real-time and to archive this data for retrospective analysis. By combining surface transportation energy and emissions evaluation capability with more traditional safety, mobility and reliability system evaluation, our goal is for TEAD to create a dynamic new paradigm in transportation systems management and performance analyses, for both real-time traffic operations, and longer-term planning for project and program investment decision-making.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units

Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes. Performance improvements of 5–10x in total application runtime were observed in LASSCF calculations for multimetallic catalyst systems up to 1200 AOs and an active space of (22e,40o) using up to four NVIDIA A100 GPUs. Furthermore, written with performance portability in mind, a comparable performance is also observed in early runs on the Aurora exascale system using Intel Max Series GPUs.

Algorithms↗
DOE OSTI2021

Sequential Bayesian inference of transition rates in the hidden Markov model for multi-state system degradation

The more easily available system performance data and advances in data analytics have provided us with opportunities to optimize maintenance programs for engineered systems, for example nuclear power plants. One key task in maintenance optimization is to obtain an accurate model for system degradation. Here, in this research, we propose a Bayesian method to address this problem. Noting that systems usually exhibit multiple states and that the actual state of a system usually is not directly observable, in the method we first model the system degradation process and the observation process based on a hidden Markov model. Then we develop a sequential Bayesian inference algorithm based on importance sampling and the forward algorithm to infer the posterior distributions of the transition rates in the hidden Markov model based on available observations. The proposed Bayesian method allows us to take advantage of evidence from multiple sources, and also allows us to perform Bayesian inference sequentially, without the need to use the entire history of observations every time new observations are collected. We demonstrate the proposed method using both synthetic data for a nuclear power plant feedwater pump and realistic data for a nuclear power plant chemistry analytical device.

42 ENGINEERING↗
DOE OSTI2023

Data-driven modeling to enhance municipal water demand estimates in response to dynamic climate conditions

Altered precipitation and temperature patterns from a changing climate will affect supply, demand, and overall municipal water system operations throughout the arid western U.S. While supply forecasts leverage hydrological models to connect climate influences with surface water availability, demand forecasts typically estimate water use independent of climate and other externalities. Stemming from an increased focus on seasonal water demand management, we use the Salt Lake City, Utah municipal water system as a test bed to assess model accuracy versus complexity trade-offs between simple climate-independent econometric-based models and complex climate-sensitive data-driven models to average to extreme wet and dry climate conditions—representative of a new climate normal. Here, the climate-independent model displayed low performance during extreme dry conditions with predictions exceeding 90% and 40% of the observed monthly and seasonal volumetric demands, respectively, which we attribute to insufficient model complexity. The climate-sensitive models displayed greater accuracy in all conditions, with an ordinary least squares model demonstrating a measurable reduction in prediction bias (3.4% vs. -27.3%) and RMSE (74.0 lpcd vs. 294 lpcd) compared to the climate-independent model. The climate-sensitive workflow increased model accuracy and characterized climate-demand interactions, demonstrating a novel tool to enhance water system management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Application of BISON to UO 2 MiniFuel fission gas release analysis

There has been a recent push to accelerate fuel qualification by developing revolutionary capabilities to reduce irradiation periods, and thereby, reduce the time required to qualify a new fuel system. One such capability is the MiniFuel irradiation capsule designed to miniaturize fuel samples and irradiate “mini” fuel samples under isothermal temperature conditions. MiniFuel allows steady-state irradiations to decouple the traditionally coupled fission rate (i.e., power) and temperature parameters to understand and generate microstructures observed in fuel operated in a commercial reactor. Furthermore, this process offers the possibility to gather in situ data as well as postirradiation or transient data such as thermal conductivity, specific heat, fission gas diffusion and release, etc. However, accelerating fuel qualification is not solely reliant on generating large amounts of data but also on developing an informed test matrix designed to rapidly generate impactful data. Additionally, this process is reliant on fuel performance codes, such as BISON, to evaluate MiniFuel irradiations using existing material models. This process pinpoints model/data gaps, identifies desired irradiation conditions, and subsequently supports model validation and development. This work describes the use of BISON to perform a number of sensitivity studies designed to understand conditions that lead to fission gas release (FGR) under steady-state isothermal irradiation conditions and temperature transient conditions. The model is applied to a UO 2 MiniFuel example and shows an overall good qualitative agreement with experimental FGR annealing tests under different temperature conditions. It also accounts well for microstructural effects on FGR. When quantitatively compared with FGR data from previously irradiated 103 MWd/kgU UO 2 discs under thermal annealing, the model shows a less satisfactory agreement with the experimental data. Finally, a UO 2 MiniFuel test matrix is proposed to help to extend the model's operational range and validate the new FGR model capabilities to higher burnups and transient conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Model Predictive Fault-Tolerant Tracking Control for PDF Control Systems With Packet Losses

In this article, a fault-tolerant tracking control strategy is investigated for nonlinear probability density function (PDF) control systems with the actuator fault, uncertainties, unknown disturbance, and random packet losses. The control input signal dropout and measurement signal dropouts are described as the independent Bernoulli distribution. An adaptive fault diagnosis (FD) observer based on the Lyapunov function is given to simultaneously estimate the fault, disturbance, and state with packet losses. Furthermore, different from the traditional robust fault-tolerant control (FTC), a new active fault-tolerant tracking controller is designed based on the model predictive control framework, which has better adaptive fault-tolerant performance. Finally, the validity of the proposed FTC method has been proved by a simulation study of a papermaking process.

42 ENGINEERING↗
DOE OSTI2021

Coupling Surface Flow with High-performance Subsurface Reactive Flow and Transport Code PFLOTRAN

Water exchange between the surface and subsurface is important for both water resource management and environmental protection. In this paper, we develop coupled surface and subsurface flow simulation capability in a parallel subsurface flow and reactive transport code PFLOTRAN. We sequentially couple the diffusion wave-based surface flow with the subsurface flow governedby the Richards equation in PFLOTRAN. These two flow domains are linked with a boundary condition switching method that ensures continuity of pressure and flux at the surface-subsurface interface. We verify the coupled code against other existing hydrologic models and observation data using a number of numerical experiments. The coupled hydrological model exhibits good performance in strong parallel scaling tests. The new coupled surface and subsurface simulator significantly advance community simulation capability towards improving integrated hydrologic and biogeochemical understanding of complex systems such as watersheds and river corridors. Keywords: Surface flow, Integrated hydrological modeling, Boundary condition switching, Parallel computing

Wu, Runjian↗
DOE OSTI2022

Folded network and structural transition in molten tin

The fundamental relationships between the structure and properties of liquids are far from being well understood. For instance, the structural origins of many liquid anomalies still remain unclear, but liquid-liquid transitions (LLT) are believed to hold a key. However, experimental demonstrations of LLTs have been rather challenging. Here, we report experimental and theoretical evidence of a second-order-like LLT in molten tin, one which favors a percolating covalent bond network at high temperatures. The observed structural transition originates from the fluctuating metallic/covalent behavior of atomic bonding, and consequently a new paradigm of liquid structure emerges. The liquid structure, described in the form of a folded network, bridges two well-established structural models for disordered systems, i.e., the random packing of hard-spheres and a continuous random network, offering a large structural midground for liquids and glasses. Our findings provide an unparalleled physical picture of the atomic arrangement for a plethora of liquids, shedding light on the thermodynamic and dynamic anomalies of liquids but also entailing far-reaching implications for studying liquid polyamorphism and dynamical transitions in liquids.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The influence of Hickson-like compact group environment on galaxy luminosities

Compact groups of galaxies are devised as extreme environments where interactions may drive galaxy evolution. In this work, we analysed whether the luminosities of galaxies inhabiting compact groups differ from those of galaxies in loose galaxy groups. We computed the luminosity functions of galaxy populations inhabiting a new sample of 1412 Hickson-like compact groups of galaxies identified in the Sloan Digital Sky Survey Data Release 16. We observed a characteristic absolute magnitude for galaxies in compact groups brighter than that observed in the field or loose galaxy systems. We also observed a deficiency of faint galaxies in compact groups in comparison with loose systems. Our analysis showed that the brightening is mainly due to galaxies inhabiting the more massive compact groups. In contrast to what is observed in loose systems, where only the luminosities of Red (and Early) galaxies show a dependency with group mass, luminosities of Red and Blue (also Early and Late) galaxies in compact groups are affected similarly as a function of group virial mass. When using Hubble types, we observed that elliptical galaxies in compact groups are the brightest galaxy population, and groups dominated by an elliptical galaxy also display the brightest luminosities in comparison with those dominated by spiral galaxies. Moreover, we show that the general luminosity trends can be reproduced using a mock catalogue obtained from a semi-analytical model of galaxy formation. These results suggest that the inner extreme environment in compact groups prompts a different evolutionary history for their galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Using statistical modeling to predict and understand fusion experiments

Over 300 cryogenic layered direct-drive inertial confinement fusion implosions have been successfully executed on the OMEGA Laser System in the last decade. However, extracting sufficient understanding from these experiments to develop new designs or to identify or mitigate degradation sources remains challenging. Recently, a statistical modeling approach was developed to successfully design and predict improved implosion experiments on OMEGA. Here, we show that one-dimensional simulations can be used to predict the outcomes of systematically perturbed three-dimensional simulations and that this statistical modeling approach can be used to identify or rule out physical mechanisms for some of the degradation sources observed on the OMEGA Laser System for direct-drive cryogenic inertial confinement fusion. In this instance, we investigate the fusion yield dependencies on the ion temperature asymmetries and laser beam size observed in experiments by comparing with trends in three-dimensional synthetic simulation databases. Using the statistical model on these systematically perturbed simulations, we find that the statistically inferred dependency on the measured ion temperature asymmetries is well explained by imposed ℓ =1 modes. However, we find that the dependency on the laser beam size is only dominated by the illumination non-uniformity for some extreme cases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Gemini Planet Imager Spectroscopy of the Dusty Substellar Companion HD 206893 B

We present new near-infrared Gemini Planet Imager (GPI) spectroscopy of HD 206893 B, a substellar companion orbiting within the debris disk of its F5V star. The J, H, K1, and K2 spectra from GPI demonstrate the extraordinarily red colors of the object, confirming it as the reddest substellar object observed to date. The significant flux increase throughout the infrared presents a challenging atmosphere to model with existing grids. Best-fit values vary from 1200 to 1800 K for effective temperature and from 3.0 to 5.0 for log(g), depending on which individual wavelength band is fit and which model suite is applied. The extreme redness of the companion can be partially reconciled by invoking a high-altitude layer of submicron dust particles, similar to dereddening approaches applied to the peculiar red field L dwarf population. However, reconciling the HD 206893 B spectra with even those of the reddest low-gravity L dwarf spectra still requires the contribution of additional atmospheric dust, potentially due to the debris disk environment in which the companion resides. Orbit fitting from 4 yr of astrometric monitoring is consistent with a ∼30 yr period, an orbital inclination of 147°, and a semimajor axis of 10 au, well within the estimated disk inner radius of ∼50 au. As one of a very few substellar companions imaged interior to a circumstellar disk, the properties of this system offer important dynamical constraints on companion–disk interaction and provide a benchmark for substellar and planetary atmospheric study.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

How Improved Forecasting Can Increase the Bulk Power System Value of Price-Responsive Electric Vehicle Managed Charging

Personal light-duty vehicle (LDV) electric vehicle managed charging (EVMC) can reduce power system costs by better aligning electric vehicle (EV) charging with locations and times of low energy cost or infrastructure use. The need to coordinate charging demand across thousands to millions of vehicles while preserving mobility service is a barrier to realizing the value of EVMC. Price-responsive dispatch mechanisms like time-of-use rates (TOU) and hourly real-time prices (RTP) are attractive compared to direct load control (DLC) because they only require one-way communications and local controls. However, increasing participation in price responsive mechanisms can induce costly-to-serve spikes in load and otherwise increase, rather than decrease, production costs. We quantify the ability of improved EVMC forecasting to sustain savings from price responsive mechanisms beyond the limit of 14% of LDVs actively participating observed in previous work. Perfect forecasting of price-responsive EV load makes TOU and RTP value-competitive with a low-error DLC formulation with up to 27% (within-week flexibility) to 45% or more (within-session flexibility) of LDVs participating in EVMC in an envisioned New England power system with 84% clean energy. Additional costs of implementing DLC should be no more than tens of dollars per vehicle-year if DLC is to be value-competitive with accurately forecast price-responsive EVMC for double-digit percentage shares of LDVs participating.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

X-Ray Diffraction and Electron Microscopy Studies of the Size Effects on Pressure-Induced Phase Transitions in CdS Nanocrystals

In recent years, investigations of the phase transition behavior of semiconducting nanoparticles under high pressure has attracted increasing attention due to their potential applications in sensors, electronics, and optics. However, current understanding of how the size of nanoparticles influences this pressure-dependent property is somewhat lacking. In particular, phase behaviors of semiconducting CdS nanoparticles under high pressure have not been extensively reported. Therefore, in this work, CdS nanoparticles of different sizes are used as a model system to investigate particle size effects on high-pressure-induced phase transition behaviors. In particular, 7.5, 10.6, and 39.7 nm spherical CdS nanoparticles are synthesized and subjected to controlled high pressures up to 15 GPa in a diamond anvil cell. Analysis of all three nanoparticles using in-situ synchrotron wide-angle X-ray scattering (WAXS) data shows that phase transitions from wurtzite to rocksalt occur at higher pressures than for bulk material. Bulk modulus calculations not only show that the wurtzite CdS nanomaterial is more compressible than rocksalt, but also that the compressibility of CdS nanoparticles depends on their particle size. Furthermore, sintering of spherical nanoparticles into nanorods was observed for the 7.5 nm CdS nanoparticles. Our results provide new insights into the fundamental properties of nanoparticles under high pressure that will inform designs of new nanomaterial structures for emerging applications.

Meng, Lingyao↗
DOE OSTI2020

Artificial Intelligence for Digital Security and Protections

Proper functioning of nuclear power plants relies on a mix of well-regulated human and machine-driven workflows. This regulation supports nuclear safety through a series of processes and many of the tasks that support these processes have a repetitive nature that make artificial intelligence (AI) informed by machine learning (ML) a potential aid in a variety of tasks. AI is being evaluated for activities that include inspections, fuel processing, monitoring, and other activities. The introduction of any new technology presents a potential new attack vector. In the case of AI/ML, there are many attacks that have already been discovered and over time the attacks can be expected to follow the growth pattern observed in cyber security. While future planning is necessary, current efforts need to be established now to predict the threat emergence over the next year 10 years and mitigate potential threats. Based on these observations, AI/ML will need to become trustworthy, which corresponds to techniques and procedures that emphasize AI explainability along with resilience techniques to data, algorithms, models, and systems. This kind of system robustness is the foundation for defenses against AI/ML-specific attacks. Attempting to look forward and take a broad view of capabilities provides input to research roadmaps and the ability to distill vulnerabilities into specific use cases may provide greater assistance in understanding the technology benefits while introducing new risks. The impact of current and future AI in three areas—capabilities, challenges, and recovery strategies—represents an initial attempt at balancing both.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

A Framework to Assess Advanced Reactor Spent Fuel Management Facility Deployment

Advanced nuclear reactors offer various operational advantages over existing light water reactors but could produce types of spent nuclear fuel (SNF) with a wide variety of forms and characteristics depending on how many different concepts are deployed. Each advanced reactor SNF type potentially poses unique management challenges. New planning efforts will be necessary to anticipate how the management requirements of advanced reactor SNF will affect the deployment of an integrated waste management system. This paper applies a framework of high-level facility deployment milestones to a generic SNF management system, reviewing them together with the advanced reactor SNF characteristics and management requirements. This allows for the investigation of factors that influence facility and system deployment, and ultimately, the identification of challenges facing the deployment of different kinds of SNF management facilities. Here, the back end of the once-through fuel cycle is examined for four advanced reactor system technology types: sodium-cooled fast reactors, high-temperature gas-cooled reactors, liquid-fuel molten salt reactors, and lead-cooled fast reactors. It is observed that milestones earlier in the facility deployment process (e.g., siting and facility design) are more impacted by the uniqueness of advanced reactor SNF characteristics than others (e.g., construction and testing). Ultimately, none of the differences are seen as fundamentally disqualifying in a technical sense; however, they should be considered early, potentially as part of reactor design, to avoid issues in the future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Achieving Highly Reproducible Results in Graphite-based Li-ion Full Coin Cells

Electrode materials, cathodes or anodes, are mostly evaluated in half coin cells where lithium (Li) metal is used. However, due to the instability nature of Li metal, the cycling performances of the half cells is more likely reflecting Li anode stability instead of the coupled electrodes, questioning the conclusions. Full coin cells utilizing graphite as the anode effectively assesses materials. But the key factors of preparing full coin cells with reproducible performances have rarely been discussed and overlooked leading to many inconsistent results. This work discusses the scientific gap between cell preparation and observed electrochemical performances to unveil the key parameters for achieving consistent and reliable results in full coin cells, critical for effective evaluation of any new materials tested under relevant conditions. The knowledge from this work is broadly applicable in other full cells systems such as Si-based full cells or Na-ion batteries.

Hu, Jiangtao↗
DOE OSTI2022

The Mu2e experiment — Searching for charged lepton flavor violation

The Mu2e experiment will search for a Standard Model violating rate of neutrinoless conversion of a muon into an electron in the presence of an aluminum nucleus. Observation of this charged lepton flavor violating process would be an unambiguous sign of new physics. Mu2e will improve upon previous searches for this process by four orders of magnitude. This requires the world’s highest-intensity muon beam, a detector system capable of efficiently reconstructing the 105 MeV/c conversion electron signal, and minimizing sensitivity to background events. A pulsed 8 GeV proton beam strikes a target, producing pions that decay into muons. Beam outside the pulse must be suppressed to < 1 0 – 10 to reduce beam-related backgrounds. The muon beam is guided from the production target along the transport system and onto the aluminum stopping target. Conversion electrons leave the stopping target and propagate inside a solenoidal magnetic field to the tracker and electromagnetic calorimeter. The tracker is a system of straw tube panels filled with Ar/CO 2 at 1 atm that tracks particles inside of a solenoidal B-field and measures their momenta with ~ 100 keV/c resolution to resolve signal events from decay-in-orbit backgrounds. The CsI calorimeter provides E / p and is used to seed the track reconstruction algorithm with σ E / E ~ 10 % and σ t < 500 ps . Additionally, a novel cosmic ray veto with greater than 99.99% efficiency brings the expected number of background events to fewer than one over three years of running. Finally, to normalize the experiment, the stopping target monitor measures the rate of capture photons from muons incident on the stopping target by using a system of high-purity germanium and lanthanum bromide scintillators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗