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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Automating Traffic Microsimulation from SYNCHRO UTDF to SUMO

Modern transportation research relies on seamlessly integrating traffic signal data with robust network representation and simulation tools. This study presents utdf2gmns, an open-source Python tool that automates conversion of the Universal Traffic Data Format, including network representation, signalized intersections, and turning volumes into the General Modeling Network Specification (GMNS) Standard. The resulting GMNS-compliant network can be converted for microsimulation in SUMO. By automatically extracting intersection control parameters and aligning them with GMNS conventions, utdf2gmns minimizes manual preprocessing and data loss. utdf2gmns also integrates with the Sigma-X engine to extract and visualize key traffic control metrics, such as phasing diagrams, turning volumes, volume-tocapacity ratios, and control delays. This streamlined workflow enables efficient scenario testing, accurate model building, and consistent data management. Validated through case studies, utdf2gmns reliably models complex urban corridors, promoting reproducibility and standardization. Documentation is available on GitHub and PyPI, supporting easy integration and community engagement.

Luo, Roy [ORNL] (ORCID:0009000312909983)↗
DOE OSTI2022

Lepto-axiogenesis in minimal $\mathrm{SUSY}$ $\mathrm{KSVZ}$ model

We study the lepto-axiogenesis scenario in the minimal supersymmetric KSVZ axion model. Only one Peccei-Quinn (PQ) field and vector-like fields are introduced besides the MSSM with the type-I see-saw mechanism. The PQ field is stabilized by the radiative correction induced by the Yukawa couplings with the vector-like fields introduced in the KSVZ model. We develop a way to follow the dynamics of the PQ field, in particular we found a semi-analytical solution which describes the rotational motion under the log-arithmic potential with including the thermalization effect via the gluon scattering which preserves the PQ symmetry. Based on the solution, we studied the baryon asymmetry, the effective number of neutrino, and the dark matter density composed of the axion and the neutralino. We found that the baryon asymmetry is successfully explained when the mass of PQ field is $\mathcal{O}$(10 6 GeV) ($\mathcal{O}$(10 5 GeV)) with the power of the PQ breaking term being 10 (8).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Probing Dark Sectors with Neutron Stars

Tensions in the measurements of neutron and kaon weak decays, such as of the neutron lifetime, may speak to the existence of new particles and dynamics not present in the Standard Model (SM). In scenarios with dark sectors, particles that couple feebly to those of the SM appear. We offer a focused overview of such possibilities and describe how the observations of neutron stars, which probe either their structure or dynamics, limit them. In realizing these constraints, we highlight how the assessment of particle processes within dense baryonic matter impacts the emerging picture—and we emphasize both the flavor structure of the constraints and their broader connections to cogenesis models of dark matter and baryogenesis.

baryon number↗
DOE OSTI2022

Nuclear Energy in Long-Term System Models: A Multi-Model Perspective

Long-term energy system models–including electric sector capacity expansion models–are widely used tools for informing planning, technology assessment, and policy analysis. Recent decarbonization goals and rapid technological change have increased the need to appropriately represent economic characteristics and technical details of energy system resources, including variable renewable energy, energy storage technologies, carbon-capture-equipped capacity, and nuclear energy. Nuclear power represents about 20% of electricity generation and 50% of carbon-free electricity in the United States as of 2021. However, there are many perspectives on the role of existing and new nuclear in the future U.S. energy system, which is reflected in the broad range of potential contributions reported in the literature. This project aims to understand how issues central to nuclear energy are represented in long-term energy models. Building on earlier collaborations that focused on variable renewable energy and energy storage, this project convenes four modeling teams that use national-scale long-term energy system models from the Electric Power Research Institute, the National Renewable Energy Laboratory, the U.S. Energy Information Administration, and the U.S. Environmental Protection Agency to share methods and data, update models, run coordinated scenarios, and identify research needs. Improving tools can provide more insightful analyses and ensure that methods are more transparent.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Manufacturing Full-Scale High Gradient Copper Accelerators: Electron Beam Welding and Allied Processes

This DOE ARDAP-funded study examines the technical and business feasibility of manufacturing high-gradient normal conducting RF (NCRF) copper accelerating structures using electron beam welding (EBW) instead of conventional high-temperature brazing. The core motivation is material performance: brazing softens copper significantly, while hard copper alloys have demonstrated ~75% higher operational gradients in SLAC tests, making cold-joining techniques highly attractive. EBW, applied to split-cell (half or quadrant) structure designs, preserves copper hardness away from the weld joint and simplifies machining — but industrial process optimization remains immature and a substantial learning curve is expected. The business case was modeled for two scenarios: a greenfield EBW linac company (> $10M upfront costs, viable above ~30 units/year) and an EBW division added to an existing accelerator firm to reduce risk and upfront costs, at the expense of being less optimal structure for the higher volume production. The study concludes that without a significant increase in demand, private investment alone cannot sustain this capability, and recommends federal support through R&D grants, procurement incentives, and CAPEX cost-sharing to incubate domestic EBW-NCRF manufacturing — with the existing-company model.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

User’s Manual for RESRAD-BUILD Code V.4: Vol. 1 – Methodology and Models Used in RESRAD-BUILD Code

The RESRAD-BUILD computer code models radionuclide release and transport in indoor environments and performs pathway analyses to evaluate the potential radiological dose and risk incurred by an individual who works or lives in a building contaminated with radioactive material or housing radioactively contaminated furniture or equipment. The code provides four geometries to characterize a radiation source: point, line, area, and volume, in which radionuclides are homogeneously distributed. Radionuclides contained in a source are considered to be released to the indoor air due to various processes including erosion (mechanically or weathering), diffusion (for tritium and radon in a volume source), or emanation (radon in a point, line, or area source). The release can proceed through different time phases with different rates. In RESRAD-BUILD Version 4.0, a dynamic ventilation model is implemented to simulate the fate and transport of source material particles and radionuclides after their releases. This dynamic ventilation model considers (1) air exchange between rooms in the building and between the rooms and the outdoor environment, (2) deposition from air to floor, (3) resuspension from the floor to the air, and (4) periodical vacuuming that reduces the floor deposition. The fate and transport modeling provides estimates of radionuclide concentrations in the source, in the air, and on the floor at different times, which are then integrated over the exposure duration for the calculation of radiation doses and cancer risks. A single run of the RESRAD-BUILD code can model a building with up to 9 rooms, 10 sources, and 10 receptors. The potential radiation dose and cancer risk incurred by each receptor are calculated for seven exposure pathways: (1) external radiation directly from the sources (accounting for shielding), (2) external radiation from radioactive particles deposited on the floors, (3) external radiation from airborne radionuclides, (4) inhalation of airborne radionuclides, (5) inhalation of radon and radon progenies, (6) inadvertent ingestion of radioactive particles directly from the source, and (7) ingestion of radioactive particles deposited on the floors. Various exposure scenarios can be modeled with RESRAD-BUILD, including but are not limited to, office worker, renovation worker, decontamination worker, building visitor, and resident. Both deterministic and probabilistic analyses can be performed to obtain results in both text reports and graphic displays.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Reserve Model of Energy Storage in Day-ahead Joint Energy and Reserve Markets: A Stochastic UC Solution

With many favorable advantages including fast response ability in particular, utility-level energy storage systems (ESS) are being integrated into energy and reserve markets to help mitigate uncertain renewable resources and fluctuant demands. This paper discusses a stochastic unit commitment (UC) model to explore capabilities of ESSs in providing valuable grid services by simultaneously joining energy and reserve markets. The proposed reserve model of ESSs presents the following features: (i) two constraints are proposed to formulate ESS’s reserve provision ability in each hour via six operation modes, namely increasing/reducing the level of charge, switching to discharge, increasing/reducing the level of discharge, switching to charge; (ii) as an energy-limited asset, constraints on ESS’s reserve deliverability across multiple hours is introduced to hold enough state of charge (SOC) headroom and floor room, guaranteeing that reserves cleared in individual hours are continuously deliverable over multiple successive hours without violating operation limits. Furthermore, a scenario-based UC model, which addresses uncertainties of renewables and demands, is adopted to evaluate reserves provided by ESSs and generators. To effectively solve the stochastic UC problem, the progressive hedging algorithm with heuristic approaches is discussed. A 6-bus system and a modified IEEE 118-bus system are used to illustrate effectiveness of the proposed approaches.

25 ENERGY STORAGE↗
DOE OSTI2019

Dynamical axion misalignment with small instantons

We present a new mechanism to relax the initial misalignment angle of the QCD axion and raise the cosmological bound on the axion decay constant. The QCD axion receives a contribution from small UV instantons during inflation, which raises its mass to the inflationary Hubble scale. This makes the axion start rolling down its potential early on. In the scenario, the standard model Yukawa couplings of quarks are dynamical, being of order one during the inflationary era and reducing to their standard model values once it ends. This means that after inflation the contribution of the small instantons is suppressed, and the axion potential reduces to the standard one from the usual IR instantons. As a result, when the axion starts to oscillate again after inflation, the initial misalignment angle is suppressed due to the dynamics during inflation. While the general idea of dynamical axion misalignment has been discussed in the literature before, we present in detail the major bottleneck on the mismatching between the minima of the axion potentials during and after inflation, and how it is circumvented in our scenario via the Froggatt-Nielsen mechanism. Taking into account of all the constraints, we find that the axion decay constant could be raised to the GUT scale, 10 15 GeV, in our scenario.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Emergent Constrained Projections of Mean and Extreme Warming in China

Reliable regional temperature projections including heat extremes are essential for climate change adaptation and mitigation. Taking China as an example, simple averages from Coupled Model Intercomparison Project Phase 6 (CMIP6) models project high warming due to sampling many high climate sensitivities in the ensemble. Here, we develop an emergent constraint (EC) framework to obtain constrained mean and daily maximum temperature (TXx) warming over China by using observed global warming and local residual warming. The constrained annual mean and TXx warming over China (2.33°C [1.61–3.05°C] and 2.31°C [1.21–2.99°C]) are 0.65°C [0.04–1.76°C] and 0.63°C [–0.50–2.39°C], respectively, lower than raw projections (2.98°C [1.85–4.22°C] and 2.94°C [2.04–4.39°C]) for 2080–2099 under the intermediate-emission scenario. Approximately half model uncertainty is reduced after constraint. The land area (population) experiencing temperature extremes in our metric is 78% (85%) of the raw projections. Our results imply a lower impact of extreme heat than implied by current raw CMIP6 projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

State-Space Model to Estimate Salmon Escapement Using Multiple Data Sources

Abstract Accurate estimates of salmonids passing Lower Granite Dam on the Snake River, by species and origin, are a critical input to assessing the status and trends of various populations as well as successful management of fisheries in the Snake River basin. Here, we describe a state-space model that estimates such escapement past a dam by using window counts, PIT tag observations, and data from an adult fish trap, accounting for issues such as nighttime passage, fallback and reascension, potential observation error at the window, and uncertainty in the adult trap rate. We tested the approach using a simulation framework that mimicked several levels of observation error, differences between nighttime passage and reascension rates, and the possibility of the adult trap being closed for some period of time. Our results demonstrate that the model produced unbiased estimates across all tested scenarios. We also applied this model to empirical data from Lower Granite Dam to produce estimates of wild, clipped hatchery, and unclipped hatchery spring/summer-run Chinook Salmon Oncorhynchus tshawytscha and steelhead O. mykiss from spawn years 2010–2019.

See, Kevin E. (ORCID:0000000297626442)↗
DOE OSTI2021

Search for lepton-flavor-violating tau-lepton decays to ℓγ at Belle

Charged lepton flavor violation is forbidden in the Standard Model but possible in several new physics scenarios. In many of these models, the radiative decays τ ± → ℓ ± γ (ℓ = e, μ) are predicted to have a sizeable probability, making them particularly interesting channels to search at various experiments. An updated search via τ ± → ℓ ± γ using full data of the Belle experiment, corresponding to an integrated luminosity of 988 fb –1 , is reported for charged lepton flavor violation. No significant excess over background predictions from the Standard Model is observed, and the upper limits on the branching fractions, B(τ ± → μ ± γ) ≤ 4.2 × 10 –8 and B(τ ± → e ± γ) ≤ 5.6 × 10 –8 , are set at 90% confidence level.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Toward real-time optimization through model reduction and model discrepancy sensitivities

Optimization problems arise in a range of scenarios, from optimal control to model parameter estimation. In many applications, such as the development of digital twins, it is essential to solve these optimization problems within wall-clock-time limitations. However, this is often unattainable for complex systems, such as those modeled by nonlinear partial differential equations. One strategy for mitigating this issue is to construct a reduced-order model (ROM) that enables more rapid optimization. In particular, the use of nonintrusive ROMs—those that do not require access to the full-order model at evaluation time—is popular because they facilitate the computation of optimization solutions within the wall-clock time requirements. However, the optimization solution will be unreliable if the iterates move outside the ROM training data. This article proposes the use of hyper-differential sensitivity analysis with respect to model discrepancy (HDSA-MD) as a computationally efficient tool to augment ROM-constrained optimization and improve its reliability. The proposed approach consists of two phases: (i) an offline phase where several full-order model evaluations are computed to train the ROM, and (ii) an online phase where a ROM-constrained optimization problem is solved, a limited number of full-order model evaluations are computed, and HDSA-MD is used to enhance the optimization solution. Numerical results are demonstrated for two examples, atmospheric contaminant control and wildfire ignition location estimation, in which a ROM is trained offline using inaccurate atmospheric data. In conclusion, the HDSA-MD update yields a significant improvement in the ROM-constrained optimization solution using only one full-order model evaluation online with corrected atmospheric data.

PDE-constrained optimization↗
DOE OSTI2023

A comparison of Eulerian and semi-Lagrangian approaches for modeling stream water quality

This paper describes and compares some of the advantages and limitations of Eulerian and Lagrangian approaches to water quality modeling and introduces a mixed Eulerian-Lagrangian (or semi-Lagrangian) methodology that captures the strengths of both approaches. The semi-Lagrangian modeling approach is applied to advection-dominated rivers, and flexibly ensures unconditional stability for all time step durations and grid segmentations. The semi-Lagrangian modeling approach is demonstrated by applying it to estimate the dissolved oxygen concentrations in the Sava River in Slovenia, focusing on aspects of the methodology and findings that would be of broad interest to managers of water quality in fluvial water bodies. Results of comparisons of the semi-Lagrangian model with the Eulerian-based QUAL2K model in steady and non-steady scenarios demonstrate that while both models are fully capable of producing satisfactory results when optimally configured, the semi-Lagrangian approach offers accuracy and stability without sensitivity to the interaction of time step size and computational grid segmentation scheme.

Sava River↗
DOE OSTI2024

Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations

Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in the field of signal classification and detection; however, these methods aren't designed to handle the low signal-to-noise ratios inherent within non-vision signal processing tasks. While they are powerful, they are currently not the method of choice in the inherently noisy and dynamic critical infrastructure domain, such as smart-grid sensing, anomaly detection, and non-intrusive load monitoring. Currently, these models can be brittle, which makes them susceptible to noisy input. This also means they have sub-optimal stability of explanation outputs. Experts and technicians using these models to make decisions in real world scenarios need assurance that a model is performing as it is supposed to. The classification or prediction outputs it generates should be sound and grounded, not likely to change in the presence of shifting noise landscapes. In this work, we explore the idea of Neural Stochastic Differential Equations (NSDE's) to improve the robustness of models trained to classify time series data and the effect of NSDE's on the explainability of outputs. We then test the effectiveness of these approaches by applying them to a non-intrusive load monitoring (NILM) dataset that consists of simulated harmonic signals injected into a real building.

Brogan, Joel↗
DOE OSTI2021

Projected land ice contributions to twenty-first-century sea level rise

The land ice contribution to global mean sea level rise has not yet been predicted using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models, but primarily used previous-generation scenarios and climate models, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios using statistical emulation of the ice sheet and glacier models. In this work, we find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Pronounced and unavoidable impacts of low-end global warming on northern high-latitude land ecosystems

Arctic ecosystems are particularly vulnerable to climate change because of Arctic amplification. Here, we assessed the climatic impacts of low-end, 1.5 °C, and 2.0 °C global temperature increases above pre-industrial levels, on the warming of terrestrial ecosystems in northern high latitudes (NHL, above 60 °N including pan-Arctic tundra and boreal forests) under the framework of the Inter-Sectoral Impact Model Intercomparison Project phase 2b protocol. We analyzed the simulated changes of net primary productivity, vegetation biomass, and soil carbon stocks of eight ecosystem models that were forced by the projections of four global climate models and two atmospheric greenhouse gas pathways (RCP2.6 and RCP6.0). Our results showed that considerable impacts on ecosystem carbon budgets, particularly primary productivity and vegetation biomass, are very likely to occur in the NHL areas. The models agreed on increases in primary productivity and biomass accumulation, despite considerable inter-model and inter-scenario differences in the magnitudes of the responses. The inter-model variability highlighted the inadequacies of the present models, which fail to consider important components such as permafrost and wildfire. The simulated impacts were attributable primarily to the rapid temperature increases in the NHL and the greater sensitivity of northern vegetation to warming, which contrasted with the less pronounced responses of soil carbon stocks. The simulated increases of vegetation biomass by 30–60 Pg C in this century have implications for climate policy such as the Paris Agreement. Comparison between the results at two warming levels showed the effectiveness of emission reductions in ameliorating the impacts and revealed unavoidable impacts for which adaptation options are urgently needed in the NHL ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Critical Role Of Conversion Cost And Comparative Advantage In Modeling Agricultural Land Use Change

The difference in land use modeling approaches is an important uncertain factor in evaluating future climate scenarios in global economic models. We compare five widely used land use modeling approaches: constrained optimization, constant elasticity of transformation (CET), the additive form of constant elasticity of transformation (ACET), logit, and Ricardian. We demonstrate that the approaches differ not only by the extent of parameter uses but also by the definition of conversion cost and the consideration of comparative advantage implied by land heterogeneity. We develop a generalized hybrid approach that incorporates ACET/logit and Ricardian to account for both conversion cost and comparative advantage. We use this hybrid approach to estimate future climate impacts on agriculture. We find a welfare loss of about 0.38–0.46% of the global GDP. We demonstrate that ignoring land heterogeneity or land conversion costs underestimates climate impacts on agricultural production and welfare.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Extended Low Load Boiler Operation to Improve Performance and Economics of an Existing Coal Fired Power Plant (Final Report)

The overall goal is to improve the performance and economics of existing coal fired power plants by extending low load boiler operation to lower loads than is currently achievable. The objective of this program is to develop and validate sensor hardware and analytical algorithms to lower plant operating expenses (OPEX) for the currently operating pulverized coal utility boiler fleet. Coal fired utility boilers are increasingly under grid dispatch pressure. In some cases, the coal fired cost of generation is noncompetitive with respect to natural gas generation and subsidized renewable sources. To remain profitable and remain fully compliant with existing environmental regulations, the installed coal fired fleet must find technologies which allow it to move into a more flexible cyclic load dispatch model. Today the installed coal fired utility fleet must be cost of generation competitive, fully emissions compliant, and responsive to the variability inherent in renewable energy generation sources. In the Phase I of the project, GE Steam Power, Inc. (GE) performed modeling of different operating scenarios for low load operation using an existing full plant dynamic model developed for a 660MW steam power plant. Sensors and analytic algorithms to enable a stable and steady coal supply for low load pulverizer operation were identified and tested at the Pulverizer Development Facility (PDF) at GE’s Clean Energy Center in Bloomfield, Connecticut. Sensors and analytic algorithms to enable stable combustion for low load operation were identified and tested at the 15 MWth Industrial Scale Burner facility (ISBF) at GE’s Clean Energy Center. A concept was developed to test the sensors and control algorithms, down selected after testing, at a full-scale coal fired power plant. A budget estimate was then developed, and the concept was implemented at an existing utility power plant. The specific objectives of the experimental work were to: • Identify and select sensors and analytic algorithms for monitoring coal pulverizer operation at lower loads to provide stable operation and appropriate coal fineness at lower coal throughput; Identify and select sensors and analytic algorithms for a Boiler Flame Stability Monitor to better balance air and fuel at each burner. This enables a reduction in a coal boiler’s safe low load power level while maintaining stable flame characteristics; Develop a concept in Phase I for low load operation of a full-scale power plant and develop a budget estimate for testing and execute the test plan at an existing plant in Phase II; Validate the capability of the extended low load boiler system to extend the minimum load operating point in a safe and reliable manner on an existing full-scale utility boiler. At the completion of this experimental study, GE has developed a set of sensors and analytic algorithms, down selected after testing, that have the potential to enable safe low load operation of a utility boiler. GE has also identified a host site for testing these identified sensors and analytic algorithms. GE has generated a full set of deliverables that provide sufficient information to proceed with the next step of testing at a host site. This includes a potential host site and budget estimate for concept testing at host site. In the Phase II of the project, a series of field tests were completed to validate the extended low load boiler operation, which consisted of detailed engineering, installation, commissioning, and testing the additional sensors and analytics for the coal-fired combustion system on an existing full-scale utility boiler. The optimization work has been supported by the host plant and endorsed by their engineering and operation staff.

01 COAL, LIGNITE, AND PEAT↗