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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Qualitative trend analysis based on a mixed-integer representation

Shape constrained spline fitting is a useful method to impose prior knowledge onto flexible semi-parametric models during parameter estimation. Most typically, the function shape is imposed through order restrictions on the regression coefficients. The intended shape is considered known or selected based on heuristic rules. In this study, we present a method to estimate the optimal set of order restrictions to segment a univariate data series into episodes with distinct shapes. This is also known as the qualitative trend analysis (QTA) problem. The obtained solution uses a trade-off between lack-of-fit and model complexity. Further, our practical implementation takes inspiration from the generalized order restricted information criterion (GORIC) for inequality-constrained model selection. From this, one learns (a) that QTA can be formulated as a mixed-integer quadratic program (MIQP) and (b) that the newly proposed mixed order restricted information criterion (MORIC) enables optimal segmentation. This is illustrated through didactic case studies.

42 ENGINEERING↗
DOE OSTI2021

An accurate, non-empirical method for incorporating decoherence into Ehrenfest dynamics

In mixed quantum-classical nonadiabatic molecular dynamics methods, the anchoring of the electronic wave function to a single nuclear geometry results in both quantitative and qualitative errors in the dynamics. In the context of both Ehrenfest and trajectory surface hopping methods, methods for incorporating decoherence are widely used to eliminate these errors. However, the accuracy of these methods often depends strongly on the parameterization of the decoherence time and/or other related quantities. Here, we present a refinement of the recently introduced collapse to a block (TAB) scheme for incorporating decoherence into Ehrenfest dynamics. The proposed approach incorporates an approximation to the history of the population dynamics and treats the coherence decay as Gaussian, rather than exponential. This method uses parameters that can be obtained from first principles, rather than empirical fitting. Application to one-dimensional models indicates excellent agreement with numerically exact simulations. We also introduce a second refinement to the TAB method: a robust linear least-squares algorithm for determining collapse probabilities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Starting-point-independent quantum Monte Carlo calculations of iron oxide

Quantum Monte Carlo (QMC) methods are useful for studies of strongly correlated materials because they are many body in nature and use the physical Hamiltonian. Typical calculations assume as a starting point a wave function constructed from single-particle orbitals obtained from one-body methods, e.g., density functional theory. However, mean-field-derived wave functions can sometimes lead to systematic QMC biases if the mean-field result poorly describes the true ground state. In this study, we examine the accuracy and flexibility of QMC trial wave functions using variational and fixed-node diffusion QMC estimates of the total spin density and lattice distortion of antiferromagnetic iron oxide (FeO) in the ground state B1 crystal structure. We found that for relatively simple wave functions the predicted lattice distortion was controlled by the choice of single-particle orbitals used to construct the wave function, rather than by subsequent wave function optimization techniques within QMC. By optimizing the orbitals with QMC, we then demonstrate starting-point independence of the trial wave function with respect to the method by which the orbitals were constructed by demonstrating convergence of the energy, spin density, and predicted lattice distortion for two qualitatively different sets of orbitals. The results suggest that orbital optimization is a promising method for accurate many-body calculations of strongly correlated condensed phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Powder diffraction

Powder diffraction is a non-destructive technique, which is experimentally simple in principle. Because the physics behind diffraction is well understood, an exceptionally large amount of information can be obtained from a single measurement. The positions and relative intensities of the peaks yield a fingerprint that can be used for qualitative phase analysis. Quantitative phase analysis can be obtained by detailed analysis of the intensities. Unit cells can be derived from the peak positions. Crystal structures can be solved using powder diffraction data and refined by the Rietveld method. The peak profiles contain information about crystallite size, strain and nanostructure. Non-idealities in the intensities give information on texture. Abandoning the crystallographic model provides information about local structure, by pair distribution function analysis. For powder diffraction, everything is a sample; the technique is commonly applied to characterize minerals, ceramics, metals and alloys, catalysts, polymers, pharmaceuticals, organic compounds, environmental and forensic samples, among others. The major features of contemporary laboratory powder diffractometers are described. Methods for obtaining suitable powder specimens are summarized. Major applications of qualitative and quantitative phase analysis, structure solution, size/strain/nanostructure analysis using peak profiles, texture analysis and pair distribution function analysis are introduced.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

EVALUATION OF HRA METHODOLOGIES FOR APPLICATION IN SDP WORK

This study critically evaluates human reliability analysis (HRA) methodologies applicable to regulatory probabilistic safety assessment (PSA) model, with a particular focus on their role in supporting the significance determination process (SDP) in nuclear safety assessment. Firstly, three widely utilized HRA methods – IDHEAS-ECA, SPAR-H, and ASEP/THERP – were qualitatively and quantitatively assessed. Qualitative assessments were conducted using attributes from the NEA/CSNI/R(2015)1 report, while quantitative evaluations employed regression and correlation analyses to compare predicted human error probabilities (HEPs) against empirical data. Results reveal distinct strengths, for example, IDHEAS-ECA’s robust predictive accuracy and K-HRA’s alignment with operational practices. In addition, dependency analysis and recovery analysis were critically evaluated. For dependency analysis, the methods’ handling of inter-task dependencies and their impact on HEPs were examined, while recovery analysis highlighted strategies for mitigating failure events. Furthermore, strategies were proposed to evaluate performance-shaping factors under conditions of reduced human performance, such as stress, fatigue, or cognitive overload, addressing specific challenges faced in SDP evaluations. Human errors from KINS’s operational performance information system event reports were evaluated as a case study. This study identifies gaps and provides actionable insights to ensure their validity and applicability in SDP HRA applications. This paper is a part of research conducted by KINS, and it should be noted that this result does not represent the regulatory position of KINS.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Reviewing and Exploring the Qualitative Impacts That Different Market and Regulatory Measures Can Have on Encouraging Energy Communities Based on Their Organizational Structure

The emergence of energy communities represents a promising option to democratize the energy system by empowering consumers to take a more active role. This can aid in achieving energy and environmental goals as well as encouraging more equitable distribution of costs and revenues between all parties on the energy system. Despite this potential, energy communities are still a nascent solution, the success of which is heavily influenced by regulations. As a result, there are a wide variety of organizational structures for energy communities at this time. This paper provides a review of the policy landscape in Spain as it relates to energy communities. This work also presents a formalized method for characterizing different energy community structures and provides a qualitative assessment of the impacts of different measures to encourage energy communities with respect to their organizational structure. Findings suggest that many market-focused measures, including wholesale, local flexibility, capacity, and multisector market measures favor larger, more integrated communities, while regulatory, legal, and organizational measures, including peer-to-peer trading, aggregation, and self-consumption favor smaller, more distributed communities. Additionally, when developing policies to encourage the growth of energy communities, policymakers should be cognizant of the progression of policies in the context of the desired outcomes for energy community growth specific to the region or country and its goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A closer look at corrosion of steel reinforcement bars in concrete using 3D neutron and X-ray computed tomography

Corrosion of reinforcing bars constitutes the largest threat to the durability of concrete structures. Thus, several studies have investigated the nature of the corrosion products, most using post-mortem analyses. However, corrosion products evolve when in contact with oxygen, hindering result interpretation. This work presents instead a state-of-the-art, non-destructive 3D method for the assessment of corrosion of embedded reinforcements. Multimodal neutron and X-ray tomography was used to observe, non-destructively, the characteristics of the corrosion products in two concrete samples, with the aim of investigating possible benefits of the use of this technique for reinforced concrete structures. One sample was naturally corroded, extracted from an 81-year-old bridge, the other was corroded via the galvanostatic method, resulting in corrosion-induced cracks. Quantitative and qualitative data was acquired, including the iron-to-rust volumetric ratio in macroscopic interfacial voids and the thickness of the corrosion layer at the steel concrete interface. The iron-to-rust volumetric ratio corresponded to large, soluble, corrosion products, forming in environments with low availability of oxygen for both samples.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Azimuthal correlation anisotropies in p + p collisions simulated using Pythia

Stimulated by a keen interest in possible collective behavior in high-energy proton-proton and proton-nucleus collisions, we study two-particle angular correlations in pseudorapidity and azimuthal differences in simulated p + p interactions using the Pythia 8 event generator. Multi-parton interactions and color connection are included in these simulations, which have been perceived to produce collectivity in final-state particles. Meanwhile, contributions from genuine few-body nonflow correlations, not of collective flow behavior, are known to be severe in these small-system collisions. We present our Pythia correlation studies pedagogically and report azimuthal harmonic anisotropies analyzed using several methods. We observe anisotropies in these Pythia simulated events qualitatively and semi-quantitatively, similar to experimental data. Furthermore, our findings highlight the delicate nature of azimuthal anisotropies in small-system collisions and provide a benchmark that can aid in improving data analysis and interpreting experimental measurements in small-system collisions.

Pythia↗
DOE OSTI2022

Monitoring accelerated alkali-silica reaction in concrete prisms with petrography and electrical conductivity measurements

We report deterioration of concrete due to alkali-silica reaction (ASR) involves a reaction between alkaline ions in the cement pore solution and non-crystalline silica found in many aggregates. Diagnosing and quantifying deterioration due to ASR in concrete currently requires destructive testing for microscopy examinations. In this paper, electrical conductivity is investigated qualitatively as an alternative non-destructive evaluation (NDE) method of ASR in hardened concrete. The study was performed using an unrestrained set of small concrete prism specimens made with highly reactive small aggregates, and kept in an environmental chamber according to ASTM C1293 standard. In a companion study, destructive petrography and damage rating index (DRI) assessment, and pore solution extraction and analysis were performed on the same set of accelerated ASR specimens. The results show that temporal evolution of nondestructive bulk resistivity is linearly correlated with destructive DRI score.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Feasibility Analyses for the Microgrid of the Mountain in the Cordillera Central Region of Puerto Rico

Distributed energy resource (DER) development can benefit communities through improvement of access to reliable electricity and a resilient energy system. Many place-specific considerations must be accounted for when designing electrical systems with co-located generation and loads. This paper presents an overview of four studies focusing on different aspects for regional DER development in the Cordillera Central region of Puerto Rico, including a grid and load stability study with the introduction of solar energy generation, microgrid design based on the solar resource in the area, resilience considerations during power outage scenarios, and qualitative risk aspects for components in the microgrid. Additionally, a conceptual substation microgrid analysis is conducted using the Microgrid Design Toolkit (MDT) to evaluate trade-offs between cost and energy availability, providing insights into optimal design strategies. A microgrid resilience assessment is performed using the Resilient Nodal Cluster Analysis Tool (ReNCAT) to identify critical loads and evaluates their accessibility during outages, emphasizing the importance of community needs. Finally, a qualitative risk assessment utilizing Hazard and Operability Analysis (HAZOP) methods highlights potential hazards and mitigations for microgrid components, ensuring robust system design and operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Simplification of the purification of heat stable recombinant low molecular weight proteins and peptides from GST-fusion products

The synthesis and purification of peptides of importance in the fields of research and medicine continue to be a challenging task. Chemical synthesis of oligopeptides, especially those greater than 25 amino acids, is cost prohibitive. On the other hand, several bottlenecks exist in the production of recombinant short peptides in heterologous expression hosts such as Escherichia coli (E. coli). In this paper, a rapid, cost-effective, and reliable method for the production and singlestep-purification of peptides and small proteins was developed. Five peptides and small proteins were overexpressed in E. coli as GST-fusion products in high yields. The recombinant peptides or proteins were successfully purified after enzymatic cleavage with selective heat-induced precipitation of the GST-affinity tag. Qualitative and quantitative analysis using SDS-PAGE and mass spectrometric methods suggest that the recombinant peptides/ proteins were purified to >95% homogeneity. Results of biophysical experiments, including multi-dimensional NMR spectroscopy, show that the purified proteins/ peptides retain their native conformation. Isothermal titration calorimetry studies indicate no significant change in the binding affinity of the heattreated purified product to their interacting partner(s) compared to the recombinant peptides purified by conventional chromatographic procedures without subjecting to heat treatment. In our opinion, the results reported render the purification of recombinant proteins/ peptides of biomedical relevance using our proposed method easy and reliable.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Evaluation of the Self Retrieval Augmented Generation Technique on Common Security Advisory Framework Data

This small experimental report evaluates a variation of Retrieval Augmented Generation (RAG), called Self-RAG. This method uses a generative language model that incorporates retrieved facts into its generation and is explicitly trained to be able to determine whether retrieved information is enough to answer the input query, with a user-defined threshold for confidence. We performed an experiment using data from the publicly available CISA Common Security Advisory Framework (CSAF) repository (https://github.com/cisagov/CSAF) as the database of facts to be used in retrieval. Qualitative results from the experiment demonstrate that the Self-RAG method has some ability to provide reasonable answers to queries that are in the dataset and will often ignore irrelevant information when asked outside of domain questions (e.g., general facts). In settings with deliberately confusing questions (the question is within domain, but asks about a fabricated advisory), it was able to refuse 40% of the time without further adjustments to the original framework. While this performance is not sufficient for current practical use, further improvements to data formatting, disambiguating results, and leveraging threshold values could improve performance significantly. However, evaluating this will require more extensive evaluations on larger datasets and potentially better models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Automated Gold Nanorod Spectral Morphology Analysis Pipeline

The development of a colloidal synthesis procedure to produce nanomaterials with high shape and size purity is often a time-consuming, iterative process. This is often due to quantitative uncertainties in the required reaction conditions and the time, resources, and expertise intensive characterization methods required for quantitative determination of nanomaterial size and shape. Absorption spectroscopy is often the easiest method for colloidal nanomaterial characterization. However, due to the lack of a reliable method to extract nanoparticle shapes from absorption spectroscopy, it is generally treated as a more qualitative measure for metal nanoparticles. This work demonstrates a gold nanorod (AuNR) spectral morphology analysis tool, called AuNR-SMA, which is a fast and accurate method to extract quantitative structural information from colloidal AuNR absorption spectra. To demonstrate the practical utility of this model, we apply it to three distinct applications. First, we demonstrate this model's utility as an automated analysis tool in a high-throughput AuNR synthesis procedure by generating quantitative size information from optical spectra. Second, we use the predictions generated by this model to train a machine learning model to predict the resulting AuNR size distributions under specified reaction conditions. Third, we apply this model to spectra extracted from the literature where no size distributions are reported and impute unreported quantitative information on AuNR synthesis. This approach can potentially be extended to any other nanocrystal system where absorption spectra are size dependent, and accurate numerical simulation of absorption spectra is possible. In addition, this pipeline could be integrated into automated synthesis apparatuses to provide interpretable data from simple measurements, help explore the synthesis science of nanoparticles in a rational manner, or facilitate closed-loop workflows.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Galvanostatic Intermittent Titration Technique Reinvented: Part I. A Critical Review

The galvanostatic intermittent titration technique (GITT), introduced in 1977 by Weppner and Huggins, provided a readily accessible means to measuring the chemical diffusion coefficient of electrochemical electrode materials. The method continues to be widely used today, but the reported diffusivity values are highly inconsistent, ranging as much as four orders of magnitude for some Li layered oxide compositions. Even qualitative trends of diffusivity are inconsistent, suggesting significant flaws in the implementation of the method. Other variants of the GITT method also suffer from similar inconsistency problems. Here we identify numerous sources of significant error including composition-dependent reaction overpotentials, mathematical flaws in the relaxation analysis methods, finite-size and non-planar geometry effects, inter-particle inhomogeneity issues, early transient effects, and surface area uncertainties. We propose a simple relaxation analysis scheme using the time variable t relax + τ - t relax , where t relax is relaxation time and τ is the galvanostatic pulse duration. We also propose to use dense diffusion-limited samples to isolate the bulk-diffusion process in the time domain. Chemical diffusivity can be extracted much more reliably with this improved implementation of the GITT method.

25 ENERGY STORAGE↗
DOE OSTI2021

Latent map Gaussian processes for mixed variable metamodeling

Gaussian processes (GPs) are ubiquitously used in sciences and engineering as metamodels. Standard GPs, however, can only handle numerical or quantitative variables. Here we introduce latent map Gaussian processes (LMGPs) that inherit the attractive properties of GPs and are also applicable to mixed data which have both quantitative and qualitative inputs. The core idea behind LMGPs is to learn a continuous, low-dimensional latent space or manifold which encodes all qualitative inputs. To learn this manifold, we first assign a unique prior vector representation to each combination of qualitative inputs. We then use a low-rank linear map to project these priors on a manifold that characterizes the posterior representations. As the posteriors are quantitative, they can be directly used in any standard correlation function such as the Gaussian or Matern. Hence, the optimal map and the corresponding manifold, along with other hyperparameters of the correlation function, can be systematically learned via maximum likelihood estimation. Through a wide range of analytic and real-world examples, we demonstrate the advantages of LMGPs over state-of-the-art methods in terms of accuracy and versatility. In particular, we show that LMGPs can handle variable-length inputs, have an explainable neural network interpretation, and provide insights into how qualitative inputs affect the response or interact with each other. We also employ LMGPs in Bayesian optimization and illustrate that they can discover optimal compound compositions more efficiently than conventional methods that convert compositions to qualitative variables via manual featurization.

42 ENGINEERING↗
DOE OSTI2025

Review of High-Throughput Surface Treatments for Microlens Arrays

Microlenses are increasingly being integrated into modern manufactured devices. From printed security devices and screens to solar panels and microscopes, these optical materials offer high control over light focusing. Thus, understanding how to treat the surfaces of these fragile, transparent devices on an integrated manufacturing line is essential. Here, in this study, we review the surface treatments for the following application categories: cleaning, increasing surface energy, decreasing surface energy, and tunable surface modifications. This overview describes methods available for the large-scale manufacturing of microlens arrays and the potential impact of those treatments on common optical surfaces. Objectives and qualitative compatibility parameters are compared, and outlooks are provided for further study to aid in streamlining the method selection and process optimization for microlenses and similar optical components.

lens manufacturing↗
DOE OSTI2024

What to expect when you're expecting engagement: Delivering procedural justice in large-scale solar energy deployment

Community engagement in the planning process to build large-scale solar (LSS) projects can win local support and advance procedural justice. However, an understanding of community engagement in current LSS development is lacking. Using responses from a U.S. nationwide survey (n = 979) of residential neighbors living within 3 miles (4.8 km) of completed LSS projects (i.e. “solar neighbors”) and project details from the U.S. Large-Scale Solar Photovoltaic Database (USPVDB), this study seeks to answer the following questions: How are solar neighbors' perceptions of community engagement associated with their attitudes toward their LSS projects? How do solar neighbors' perceptions of community engagement compare to their expectations? And, how do neighbors explain what they perceived about the planning process? We answer these questions using mixed methods, including regression modeling, a new gap analysis technique, and qualitative coding. We find that higher perceived engagement is associated with more positive attitudes toward the project, even when controlling for respondents who acted in opposition. Supporters and opponents alike expect more engagement than they perceived and information about projects both before construction and after operation is lacking. Awareness and engagement expectations increase at certain project size and proximity thresholds. However, most neighbors expect the public to offer input during engagement, but not make decisions. We contextualize these findings with explanatory comments from respondents.

14 SOLAR ENERGY↗
DOE OSTI2025

Online collection of LC effluent as droplets for automatic injection into ICP-MS

A sample introduction technique was developed to allow for online, dropwise injection of effluent into a mass spectrometer (MS). This allowed for the coupling of chromatography systems that were not driven by pumps without altering the set-up or separation performance. This capability combined the benefits of coupling separation and measurement while also enabling accurate chromatographic evaluation that would generally be performed offline. The incorporation of a flowing rinse into the system made dropwise resolution possible for any liquid capable of forming drops under ambient conditions. The technique was demonstrated utilizing gas pressurized extraction chromatography (GPEC) and inductively coupled plasma-time-of-flight mass spectrometry (ICP-TOFMS) to illustrate the qualitative applications for rapid separation development and procedure evaluation. This method's quantitative applications were evaluated using single and double isotope dilution mass spectrometry (IDMS) with an external mass bias correction to measure analytes across entire elutions including volumes as small as single drops. In conclusion, the total neodymium values afforded by both single and double IDMS were within the uncertainty of the calculated value for evaluation of full elution peaks and for most of the single drops analyzed that reached above 10k cps Nd-144.

GPEC↗