Charting the evolution of the U.S. solar PV installation industry and its bonds with other skilled trades
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O’Shaughnessy, Eric↗
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Results for “CHARTS - INTERCOOLERS”
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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Thixotropic spectra and Ashby-style charts for thixotropy
There is no universal model for thixotropy, and comparing thixotropic effects between different fluids is a subtle yet challenging problem. We introduce a generalized (model-insensitive) framework for comparing thixotropic properties based on thixotropic spectra. A superposition of exponential stress modes distributed over thixotropic time scales is used to quantify buildup and breakdown times and mode strengths in response to step-change input. This mathematical framework is tested with several experimental step-shear rate data on colloidal suspensions. Low-dimensional metrics based on moments of the distribution reveal characteristic average thixotropic properties, which are visualized on Ashby-style diagrams. This method outlines a framework for describing thixotropy across a diverse range of microstructures, supporting scientific studies as well as material selection for engineering design applications.
Mechanics↗
Deep nonparametric estimation of intrinsic data structures by chart autoencoders: Generalization error and robustness
Autoencoders have demonstrated remarkable success in learning low-dimensional latent features of high-dimensional data across various applications. Assuming that data are sampled near a low-dimensional manifold, we employ chart autoencoders, which encode data into low-dimensional latent features on a collection of charts, preserving the topology and geometry of the data manifold. Our paper establishes statistical guarantees on the generalization error of chart autoencoders, and we demonstrate their denoising capabilities by considering n noisy training samples, along with their noise-free counterparts, on a d-dimensional manifold. By training autoencoders, we show that chart autoencoders can effectively denoise the input data with normal noise. We prove that, under proper network architectures, chart autoencoders achieve a squared generalization error in the order of n–$\frac{2}{d+2}$log 4 n, which depends on the intrinsic dimension of the manifold and only weakly depends on the ambient dimension and noise level. We further extend our theory on data with noise containing both normal and tangential components, where chart autoencoders still exhibit a denoising effect for the normal component. As a special case, our theory also applies to classical autoencoders, as long as the data manifold has a global parametrization. Furthermore, our results provide a solid theoretical foundation for the effectiveness of autoencoders, which is further validated through several numerical experiments.
97 MATHEMATICS AND COMPUTING↗
Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance (V.5.0)
The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112(a)-(c)). EV-ChART provides a streamlined data submission process and an integrated set of analytic tools, connects to other data sources, and empowers data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112(a)-(c)). The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow. Per 23 CFR 680.112(a)-(c), the annual and quarterly data submissions are required of all National Electric Vehicle Infrastructure (NEVI) Formula Program projects, as well as projects for the construction of publicly accessible EV chargers that are funded with funds made available under Title 23, United States Code, including any EV charging infrastructure project funded with federal funds that is treated as a project on a federal-aid highway. One-time data submissions are required of both the NEVI Formula Program projects and grants awarded under 23 U.S.C. 151(f) for projects that are for EV charging stations located along and designed to serve the users of designated Alternative Fuel Corridors (AFCs). Other information and data required in 23 CFR 680, such as 23 CFR 680.112(d), 23 CFR 680.116(c), and 23 CFR 680.106(a), are not discussed in this guidance.
33 ADVANCED PROPULSION SYSTEMS↗
Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART): Data Format and Preparation Guidance, Version 2.0
The Joint Office of Energy and Transportation maintains the Electric Vehicle Charging Analytics and Reporting Tool (EV-ChART), which provides a centralized hub for submitting electric vehicle (EV) charging infrastructure data directed by the Federal Highway Administration (23 CFR 680.112) EV-ChART will provide a streamlined data submission process and an integrated set of analytic tools, connect to other data sources, and empower data sharing and access across stakeholders, including the public. Any data shared publicly will be aggregated and anonymized to stay in accordance with 23 CFR 680. This EV-ChART Data Format and Preparation Guidance provides a comprehensive overview of the data reporting requirements as authorized under 23 CFR 680.112. The guidance is intended to be used alongside the EV-ChART Data Input Template, which defines the tabular data structure that these data submissions must follow.
ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
Formal verification and validation of run-to-completion style state charts using Event-B
State chart notations with ‘run to completion’ semantics are popular with engineers for designing controllers that react to environment events with a sequence of state transitions but lack formal refinement and rigorous verification methods. State chart models are typically used to design complex control systems that respond to environmental triggers with a sequential process. The model is usually constructed at a concrete level and verified and validated using animation techniques relying on human judgement. Event-B, on the other hand, is based on refinement from an initial abstraction and is designed to make formal verification by automatic theorem provers feasible. Abstraction and formal verification provide greater assurance that critical (e.g. safety or security) properties are not violated by the control system. In this paper, we introduce a notion of refinement into a ‘run to completion’ state chart modelling notation and leverage Event-B’s tool support for theorem proving. We describe the difficulties in translating ‘run to completion’ semantics into Event-B refinements and suggest a solution. We illustrate our approach and show how models can be validated at different refinement levels using our scenario checker animation tools. We show how critical invariant properties can be verified by proof despite the reactive nature of the system and how behavioural aspects of the system can be verified by testing the expected reactions using a temporal logic, model checking approach. To verify liveness, we outline a proof that the run to completion is deadlock-free and converges to complete the run.
97 MATHEMATICS AND COMPUTING↗
Psychrometric Chart v1.0.0
Psychart is a graphical program developed for NERSC for accurately monitoring air conditions for the air cooled HPC equipment. Psychart will live directly in the OMNI system as a Grafana plugin. It employs the use of Psychrolib and the Grafana Starter Panel to create a front-end program that plots the state of the environmental air on a psychrometric chart. It is highly customizable, allowing the user to modify graph bounds, optionally show ASHRAE data center comfort regions, change the series point color, and more. What sets Psychart apart from other existing psychrometric charts is its ability to plot in real-time. Other psychrometric charts that can be found online require manual input of data and do not seamlessly integrate with Grafana.
Ventura, Nicolas↗
Reaction Evolution Flow Chart - The Critical Path to DDT [Slides]
Purpose (and limitations): The following flow-chart identifies and organizes a generalized, and simplified, sequence of necessary conditions for accidental ignition and reaction growth in a consolidated, polymer-bonded explosive (PBX) charge that has been insulted. A ‘yes’ answer to each question will lead down the critical path and produce violent, explosive reactions, up to and possibly including transition to detonation. Alternatively, any ‘no’ answer will serve as an off-ramp from the path resulting in less violent responses. It is important to note that this flow-chart is a high-level tool to flag potential operational vulnerabilities, but lacks the details needed to stand alone as a sole-source for risk determination. Each question represents a significant area of study and, therefore, the flow chart is intended to be supplemented by subject matter expert elicitations.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Higher-order space-charge stability in anisotropic beams: Vlasov-Poisson derivation, refined dispersion relations, and stability charts
The Hofmann stability chart is used to screen working points in space-charge-dominated linacs. We identify two errors in its published higher-order dispersion relations: missing $(1\mp2\hatη^2/α)$ factors in the third-order $S^4$ coupling residues, and a sign error in the stated isotropic reduction of the fourth-order relation. Both corrections follow from Hofmann's Vlasov-Poisson equations without fitted parameters. They reproduce coherent tune-shift coefficients in the author's later monograph that the printed forms miss by 24% and 127%. Mode-resolved figures from a published application agree with the corrected relations and reject the printed forms, indicating an inconsistency between the 1998 equations and the calculations underlying those tested figures. We quantify the effect on the non-oscillatory stability chart. Inside the adopted $S^2\le10$ comparison domain, printed and corrected forms disagree on 0.73-2.11% of cells, with no preferred direction. Among excluded cells, disagreement reaches 22%, and the printed relation over-predicts instability at every sampled anisotropy. This concentration may help explain why the errors persisted, although it does not establish their historical cause. For PIP-II, the corrected chart flags four of thirty-two evaluable periods, including one on a third-order odd branch missed by a second-order screen. This count covers non-oscillatory modes only and remains conditional on an unresolved factor-five disagreement between two codes on transverse emittance growth.
Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗
Learning nuclear cross sections across the chart of nuclides with graph neural networks
We explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus on the neutron-induced reactions in the fast energy regime. Our approach follows a two-stage learning framework. First, we apply representation learning to encode cross section data into a latent space using either variational autoencoders (VAEs) or implicit neural representations (INRs). Then, we train graph neural networks (GNNs) on the resulting embeddings to predict missing values across the nuclear chart by leveraging the topological structure of neighboring isotopes. We demonstrate accurate cross section predictions within a 9 × 9 block of missing nuclei. We also find that the optimal GNN training strategy depends on the type of latent representation used, with VAE embeddings performing best under end-to-end optimization in the original space, while INR embeddings achieve better results when the GNN is trained only in the latent space. Furthermore, using clustering algorithms, we map groups of latent vectors into regions of the nuclear chart and show that VAEs and INRs can discover some of the neutron magic numbers. These findings suggest that deep-learning models based on the representation encoding of cross sections combined with graph neural networks hold significant potential in augmenting nuclear theory models, e.g., by providing reliable estimates of covariances of cross sections, including cross-material covariances.
Machine learning↗
Primary fission fragment mass yields across the chart of nuclides
In this work, we have calculated a complete set of primary fission fragment mass yields, Y(A), for heavy nuclei across the chart of nuclides, including those of particular relevance to the rapid neutron capture process (r process) of nucleosynthesis. We assume that the nuclear shape dynamics are strongly damped, which allows for a description of the fission process via Brownian shape motion across nuclear potential-energy surfaces. The macroscopic energy of the potential was obtained with the Finite-Range Liquid-Drop Model (FRLDM), while the microscopic terms were extracted from the single-particle level spectra in the fissioning system by the Strutinsky procedure for the shell energies and the BCS treatment for the pairing energies. For each nucleus considered, the fission fragment mass yield, Y(A), is obtained from 50 000 to 500 000 random walks on the appropriate potential-energy surface. The full mass and charge yield, Y(Z,A), is then calculated by invoking the Wahl systematics. With this method, we have calculated a comprehensive set of fission-fragment yields from over 3800 nuclides bounded by 80 ≤ Z ≤ 130 and A ≤ 330; these yields are provided as an ASCII formatted database in the Supplemental Material. We compare our yields to known data and discuss general trends that emerge in low-energy fission yields across the chart of nuclides.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Hofmann Stability Charts Revisited for PIP-II: From Classical Theory to Assumption-Free and ML-Driven Maps
The Hofmann stability chart remains a standard for visualizing parametric resonances in space-charge–dominated linacs, but its use typically relies on non-oscillatory Vlasov dispersion relations with simplifying assumptions (continuous focusing, KV phase space, linear optics, limited transverse–longitudinal coupling). We revisit the chart for the PIP-II linac along three tracks. (1) We reproduce the conventional maps in the (νz/νx, νx/ν0x) plane for relevant εz/εx, providing a validated reference. (2) We remove key assumptions by deriving stability surfaces directly from multi-particle tracking with realistic lattice discreteness, RF defocusing, solenoid/quad optics, and bunched-beam dynamics; local tunes and early-time growth rates are estimated from envelope oscillations and projected to the same coordinates. These assumption-reduced maps recover the canonical stopbands while revealing shifts and broadenings driven by tune modulation, non-KV distributions, and transverse–longitudinal coupling at PIP-II intensities. (3) We train a compact machine-learning surrogate that emulates the growth surface from zero-current optics, tune depression, emittance ratio, bunching factor, and selected lattice descriptors, enabling rapid scans and online working-point selection. We compare the three representations on representative PIP-II sections and discuss implications for commissioning guard bands, resonance avoidance, and routine operations.
Pathak, Abhishek [Fermilab] (ORCID:000000021704208↗
Nuclear Cyber Technical Exchange (March 2025 Charts)
Each month we host a Nuclear-Cyber Technical Exchange with a subset of our Bilat partners to support our risk reduction efforts. This month the topics are cyber test and evaluation and resiliency. This chart deck (12) charts will be used for the three TE's.
99 - GENERAL AND MISCELLANEOUS↗
Evaluation of Digital Nautical Chart data for confirmation and expansion of GeoNames data
Here, this work examines how Digital Nautical Chart (DNC) data may contribute to the evolution and refinement of GeoNames data for near-shore features. GeoNames features are point data with one or more possible place names. DNC Earth Cover Text (ECRText) objects are map labels positioned nearby their real word counterpart. ECRText feature map position strikes a compromise between association with real features and cartographic readability. This work explores whether ECRText features can confirm (or expand names for) existing locations or contribute new locations through data conflation. Due to name variations and spatial position, conflating these data are nontrivial. Previous work engaged in a brief examination using the trigram string matching algorithm under coarse proximity constraints, indicating that ECRText could provide additional value to GeoNames. This work builds on that study, by engaging in a deeper examination of spatial proximity and exploring conflation agreement across an ensemble of string matching approaches. The result finds strong ensemble agreement about ECRText features which already exist in GeoNames but mixed results about which features contribute new information, as well as exploring why some of these matching techniques fail. With an eye toward automation, computational efficiency was found not to be a constraint in sustaining updates.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
First observation of the decay of the 13/2 + isomer in 183 Hg and B(M 2) systematics of neutron transitions across the nuclear chart
The decay of the 13/2 + isomeric state in 183 Hg was observed for the first time following the a decay of the 13/2 + isomer in 187 Pb produced in the 142 Nd( 50 Cr, 2p3n) reaction. Using $\alpha - \gamma$ delayed coincidence measurements, the half-life of this isomer was measured to be 290(30) μs. This isomer is proposed to deexcite by an unobserved low-energy M2 transition to the known 9/2 - member of a strongly prolate-deformed 7/2 - [514] band, followed by a 105-keV M1 transition to the bandhead. A lower limit of B(M2) >= 0.018 W.u. was deduced for the unobserved transition. The presumed retardation is proposed to be due to the notable shape change between the initial, nearly spherical, and the final, strongly deformed, states. A similar scenario is also considered for the 13/2 + isomer in 181 Hg, suggesting both are cases of shape isomers. The B(M2) systematics of neutron transitions across the nuclear chart is discussed.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Charting lattice thermal conductivity for inorganic crystals and discovering rare earth chalcogenides for thermoelectrics
Charting and understanding lattice thermal conductivity of inorganic materials and discovery of REX materials for thermoelectrics.
Zhu, Taishan↗
Systems-chart approach to the design of spin relaxation times in molecular qubits
The paper presents systems design charts for molecular qubits, mapping chemical variables to spin relaxation times for optimized qubit design.
Mullin, Kathleen R.↗
Remote Sensing and AI to Automate Electronic Navigational Chart Updates
Electronic navigational charts (ENCs) are vital for navigation and must be updated frequently as coastal bathymetric conditions change, but the current manual survey approach is costly, time-consuming, and limited in scope by available survey resources.
97 MATHEMATICS AND COMPUTING↗