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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 613 records · Page 34

Reliability study of an emerging fire suppression system

Self-contained fire extinguishers are a robust, reliable and minimally invasive means of fire suppression for gloveboxes. Plutonium gloveboxes are known to present harsh environmental conditions for polymer materials, these include radiation damage and chemical exposure, both of which tend to degrade the lifetime of engineered polymer components. The primary component of interest in self-contained fire extinguishers is the nylon 6-6 machined tube that comprises the main body of the system.Thermo-mechanical modeling and characterization of nylon 6-6 for use in plutonium glovebox applications has been carried out. Data has been generated regarding property degradation leading to poor, or reduced, engineering performance of nylon 6-6 components. In this study, nylon 6-6 tensile specimens conforming to the casing of self-contained fire extinguisher systems have been exposed to hydrochloric, nitric, and sulfuric acids. This information was used to predict the performance of a load bearing engineering component comprised of nylon 6-6 and designed to operate in a consistent manner over a specified time period. The study provides a fundamental understanding of the engineering performance of the fire suppression system and the effects of environmental degradation due to acid exposure on engineering performance. Data generated help identify the limitations of self-contained fire extinguishers. No critical areas of concern for plutonium glovebox applications of nylon 6-6 have been identified when considering exposure to mineral acid.

36 MATERIALS SCIENCE↗

Laser notching ceramics for reliable fracture toughness testing

A new method for notching ceramics was developed using a picosecond laser for fracture toughness testing of alumina samples. The test geometry incorporated a single-edge-V-notch that was notched using picosecond laser micromachining. This method has been used in the past for cutting ceramics, and is known to remove material with little to no thermal effect on the surrounding material matrix. This study showed that laser-assisted-machining for fracture toughness testing of ceramics was reliable, quick, and cost effective. In order to assess the laser notched single-edge-V-notch beam method, fracture toughness results were compared to results from other more traditional methods, specifically surface-crack in flexure and the chevron notch bend tests. Lastly, the results showed that picosecond laser notching produced precise notches in post-failure measurements, and that the measured fracture toughness results showed improved consistency compared to traditional fracture toughness methods.

36 MATERIALS SCIENCE↗

Expanded graphite for thermal conductivity and reliability enhancement and supercooling decrease of MgCl2⋅6H2O phase change material

Highlights: • MgCl{sub 2}·6H{sub 2}O/EG composite PCMs show the superior thermal transfer ability. • 83.33 wt.% of MgCl{sub 2}·6H{sub 2}O encapsulated in composite PCM was obtained. • EG and nucleating agents decreased the supercooling degree. - Abstract: Expanded graphite (EG) is considered as a promising supporter for phase change material (PCM) due to its unique porous structure and excellent heat transfer ability. In the study, EG with different mass fractions (9 wt.%, 13 wt.%, 16.67 wt.%, and 20 wt.%) was respectively blended with MgCl{sub 2}·6H{sub 2}O. The thermal conductivity data of composite PCMs with 9 wt.%, 13 wt.%, 16.67 wt.%, and 20 wt.% of EG was respectively measured to be 0.942 W/m K, 1.053 W/m K, 1.354 W/m K and 1.658 W/m K. DSC analysis showed that 16.67 wt.% of EG decreased the degree of supercooling by 29.4 °C and that the addition of 3.0 wt.% SrCO{sub 3} further decreased the degree of supercooling by 17.9 °C. The maximum encapsulation weight percentage of MgCl{sub 2}·6H{sub 2}O reached 83.33 wt.% after 30 phase change cycles without significantly reducing its latent heat value, exhibiting the relatively stable thermal reliability.

36 MATERIALS SCIENCE↗

A progressive electrochemical sensor for food quality control: Reliable determination of theobromine in chocolate products using a miniaturized boron-doped diamond electrode

In the present paper, a miniaturized boron-doped diamond electrode (BDDE) is proposed as a progressive electrochemical sensor for simple, fast and reliable quantification of dimethylxanthine alkaloid, theobromine (TB). Using cyclic voltammetry, the studied xanthine provided one well-shaped, irreversible and diffusion-controlled oxidation peak at relatively high potentials (+1.2 V vs. Ag/AgCl/3 M KCl reference electrode) in the presence of 0.1 M H2SO4. After selection of suitable experimental conditions, the linear calibration curves for TB were obtained in the concentration range from 0.99 up to 54.5 μM with the sensitivity of 0.07 μA/μM providing both differential pulse (DPV) and square-wave voltammetric (SWV) techniques, respectively. The elaborated voltammetric protocol yielded low detection limits of 0.42 and 0.51 μM accompanied by adequate intra-day repeatability (relative standard deviation of 2.5 and 1.7%) using DPV and SWV procedure, respectively. The interference study revealed the reasonable selectivity when taking the target food samples into account. The practical applicability of the voltammetric protocol using a miniaturized BDDE was verified in the analysis of six commercially available brands of chocolate products with the determined mass percentages of TB ranging from 0.75 to 2.24% and from 0.69 to 2.15% using DPV and SWV procedure, respectively. The obtained results were also in a good agreement with those achieved by reference titration method with potentiometric indication. The progressive electrochemical sensor based on a miniaturized BDDE has appeared to be an attractive candidate for practical applications in food quality control. Besides, the proposed voltammetric protocol presents advantages when compared to others techniques (e.g. chromatography), concerning simplicity, cost, speed of analysis, waste generation (environmentally friendly) and samples pretreatment (only dilution in electrolyte solution prior to analysis). © 2018 Elsevier B.V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reliable statistics-based detection and investigation of anomalies in a SMART valve system

Reliable anomaly detection and diagnosis are critical for the safe operation of complex engineered systems. This study presents a unified framework that integrates statistical, model-based, and data-driven techniques for anomaly detection and investigation, demonstrated on SMART valve systems in hybrid energy applications. Four detection methods—mean deviation, seasonal extreme studentized deviate, ARIMA forecasting, and matrix profiling—were implemented and compared. Matrix profiling was particularly effective in revealing subtle deviations and hidden relationships among variables. Anomaly investigation was performed by analyzing variable-level and grouped signal profiles, with system topology incorporated to distinguish primary faults from propagated effects. Grouping signals by type enhanced interpretability, enabling accurate localization of anomalies across multi-dimensional datasets. Experimental results confirmed the framework's capability to consistently detect and isolate anomalies while providing actionable insights into system interdependencies. The proposed methodology offers a robust, interpretable, and scalable solution for condition monitoring, with potential applications in safety-critical domains such as nuclear energy, aerospace, and process industries.

ARIMA models↗

Novel design and diagnostics improvements for increased production capacity and improved reliability at the Los Alamos Isotope Production Facility

The Isotope Production Facility (IPF) at Los Alamos National Laboratory (LANL) is used to produce an array of isotopes for medical, global security, and research applications with an intense beam of protons supplied by the linear accelerator at the Los Alamos Neutron Science Center (LANSCE). An Accelerator Improvement Project (AIP) was recently conducted at IPF to improve facility reliability and reduce programmatic risk while increasing general isotope production capacity and flexibility. This was accomplished through the installation of an improved beam window assembly, more robust beam diagnostics, an active and adjustable collimator, and a new beam rastering system. This paper will highlight the four exciting innovations and how they were designed, validated, and installed in parallel as well as the significant operational advantages they provide to IPF. Key experiments and the increased currents achieved in routine production runs demonstrating the enhanced capability from the AIP will be presented. As a result, the most notable capability enhancements include irradiations with beam currents ranging from 100 nA experimental runs up to 300 μA on routine production targets and utilization of a range of cylindrical target diameters.

100 MeV protons↗

Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulations as a part of the standard current practice for designing marine structures to survive extreme sea states. These environmental contours are characterized by combinations of significant wave height (H s ) and either energy period (T e ) or peak period (T p ) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first-order reliability method (I-FORM) is a standard design practice for generating environmental contours. This paper develops enhanced methodologies for data analysis prior to the application of the I-FORM, including the use of principal component analysis (PCA) to create an uncorrelated representation of the variables under consideration as well as new distribution and parameter fitting techniques. As a result, these modifications better represent the measured data and, therefore, should contribute to the development of more realistic representations of environmental contours of extreme sea states for determining design loads for marine structures.

42 ENGINEERING↗

Combined effects of horizontal and vertical resolution on reliable turbulence prediction at tidal energy sites: A systematic study in the Salish Sea, WA

Predicting turbulence characteristics with coastal ocean models is essential for tidal energy converter deployment. While large eddy simulation provides a detailed turbulence representation, computational limitations restrict its use to smaller domains. We systematically evaluate whether well-configured coastal models can provide reliable turbulence prediction through progressive refinement of 3D model representation. We implemented four model configurations (Levels 1–4) using terrain-following coordinates, isolating the impacts of horizontal resolution, vertical resolution, and layer distribution. We validated all configurations against field measurements from the Salish Sea, WA. Results show that tidal current velocity predictions remain unchanged regarding model configuration, but turbulence properties are sensitive to resolution refinement. Increasing vertical resolution alone proved insufficient; even with vertical sigma-levels rising from 11 to 41, significant underprediction persisted until finer horizontal resolution better captured bathymetric variations. The Level 4 configuration, incorporating geometric sigma-levels distribution, achieved turbulence prediction skill scores exceeding 0.90. Turbulence closure comparison revealed Mellor- Yamada 2.5 outperformed k-epsilon in TKE prediction (skill scores 0.84–0.94 versus 0.72–0.81) due to better boundary layer parameterization. This study shows that well-configured coastal models effectively bridge the gap between simplified tools and costly high-fidelity modeling, offering the tidal energy industry practical and cost-effective turbulence data at commercially relevant scales.

Marine Energy↗

Human reliability analysis studies from simulator experiments using Bayesian inference

Probabilistic Safety Assessment (PSA) of complex facilities is performed to arrive at the risk posed by them. PSA also accounts for the contribution of the human errors towards the overall risk through Human Reliability Analysis (HRA) in terms of Human Error Probability (HEP). Human operators are part of the system and do not work in isolation. Their performance is influenced by the context in which the actions are performed. As a result, quantification of HEP requires operator performance data under the given context. Some good sources of operator performance data are plant‘s operation data, simulator data and expert judgement. The plant operation data pertaining to HRA is generally sparse. In this situation, a full scope plant simulator provides a good alternative for operator performance data generation. Many of the currently practiced HRA methods have been developed by combining the empirical evidence with expert judgement and contain a lot of uncertainty in their estimates. Bayesian inference is suitable for updating the prior HRA estimates with the simulator evidence to obtain the posterior HEP. Here, posterior HEP has been calculated for postulated accident scenarios in advanced reactor (first of its kind) at design stage, using plant simulator.

97 MATHEMATICS AND COMPUTING↗

The influence of cloud cover on the reliability of satellite-based solar resource data

Satellite-based solar resource data are often developed and validated by using binary cloudiness categories: clear sky or overcast cloudy sky. To investigate the reliability of solar resource data in partially cloudy conditions, we estimate cloud fraction using two distinct algorithms: a physical retrieval model using surface observed global horizontal irradiance (GHI) and direct normal irradiance (DNI) and a temporal average of cloud mask data estimated by the observed DNI. Our analysis reveals a significant presence of scattered clouds, broken clouds, and mismatches between satellite- and surface-based cloud data at 17 surface sites across the contiguous United States, though confidently clear and cloudy conditions collectively account for more than 70 % of the data. Solar radiation is computed using the National Solar Radiation Database (NSRDB) algorithm and validated using surface observations. Here, our findings suggest that, in the presence of scattered clouds, NSRDB data for clear-sky conditions can be subject to significant overestimation. In cloudy-sky conditions classified by satellite data, DNI computed by the Fast All-sky Radiation Model for Solar applications with DNI (FARMS-DNI) can be underestimated when limited clouds are detected by surface observations. The bias observed in several cloudiness categories indicates that the NSRDB is exceptionally accurate in confidently clear conditions. However, clear-sky conditions with scattered clouds and mismatched cloud data contribute significantly to the overall uncertainties in the NSRDB. Therefore, future improvements in solar resource data should involve development and implementation of satellite-derived cloud fraction and should consider a novel radiative transfer model accounting for amplified cloud reflection. The evaluation within cloudiness categories also provides a physical rationale for the superior performance of FARMS-DNI compared to the Direct Insolation Simulation Code (DISC) in both cloudy-sky and all-sky conditions.

14 SOLAR ENERGY↗

District-Scale Analysis of Electricity Load and Strategies to Improve Energy Reliability Using Prototype District Models

Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impact of dipolar molecules on the reliability of organic photovoltaic cells

Blending two non-fullerene acceptors (NFAs) to form bulk heterojunctions (BHJs) in ternary organic photovoltaics (OPVs) has been shown to lead to an end-capping exchange reaction that results in the generation of several new dipolar species whose impact on OPV operational stability remains uncertain. Here, we investigate the reliability of a ternary OPV system intentionally blended with dipolar NFA molecules. We reveal that an intrinsic contribution to OPV degradation is the reorganization and reorientation of the dipolar molecules during operation, which leads to an increased dielectric constant (ε r ) of the BHJ. Consequently, the electric field across the BHJ with dipolar molecules decreases compared with that of a non-dipolar BHJ under the same applied voltage, leading to a larger reduction in charge collection efficiency over time. This result has implications on the stability of a range of organic electronic devices containing dipolar molecules.

14 SOLAR ENERGY↗

Reliable and versatile immortal muscle cell models from healthy and myotonic dystrophy type 1 primary human myoblasts

Primary human skeletal muscle cells (hSkMCs) are invaluable tools for deciphering the basic molecular mechanisms of muscle-related biological processes and pathological alterations. Nevertheless, their use is quite restricted due to poor availability, short life span and variable purity of the cells during in vitro culture. Here, we evaluate a recently published method of hSkMCs immortalization, relying on ectopic expression of cyclin D1 (CCND1), cyclin-dependent kinase 4 (CDK4) and telomerase (TERT) in myoblasts from healthy donors (n=3) and myotonic dystrophy type 1 (DM1) patients (n=2). The efficacy to maintain the myogenic and non-transformed phenotype, as well as the main pathogenetic hallmarks of DM1, has been assessed. Combined expression of the three genes i) maintained the CD56(NCAM)-positive myoblast population and differentiation potential; ii) preserved the non-transformed phenotype and iii) maintained the CTG repeat length, amount of nuclear foci and aberrant alternative splicing in immortal muscle cells. Moreover, immortal hSkMCs displayed attractive additional features such as structural maturation of sarcomeres, persistence of Pax7-positive cells during differentiation and complete disappearance of nuclear foci following (CAG){sub 7} antisense oligonucleotide (ASO) treatment. Overall, the CCND1, CDK4 and TERT immortalization yields versatile, reliable and extremely useful human muscle cell models to investigate the basic molecular features of human muscle cell biology, to elucidate the molecular pathogenetic mechanisms and to test new therapeutic approaches for DM1 in vitro. - Highlights: • CCND1, CDK4 and TERT efficiently immortalize primary human muscle cells • Healthy and DM1 immortal cells efficiently differentiate after prolonged cell culture • Immortalized cells do not acquire the transformed phenotype in vitro • Immortal DM1 muscle cells maintain the molecular features of the disease.

60 APPLIED LIFE SCIENCES↗

Absorption Correction for Reliable Pair Distribution Functions from Low Energy X-ray Sources

This paper explores the development and testing of a simple absorption correction model for processing powder X-ray diffraction data from Debye−Scherrer geometry laboratory X-ray experiments. This may be used as a preprocessing step before using PDFGETX3 to obtain reliable pair distribution functions (PDFs). Various experimental and theoretical methods for estimating μR were explored, and the most appropriate μR values for correction were identified for different capillary diameters and X-ray beam sizes. We identify operational ranges of μR where a reasonable signal-to-noise ratio is possible after correction. A user-friendly software package, DIFFPY.LABPDFPROC, is presented that can help estimate μR and perform absorption corrections with a rapid calculation for efficient processing.

Absorption↗

Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures

The first important step in a structure-based virtual screening is the judicious selection of a receptor protein. In cases where the holo protein receptor structure is unavailable, significant reduction in virtual screening performance has been reported. In this work, we present a robust method to generate reliable holo protein structure conformations from apo structures using molecular dynamics (MD) simulation with restraints derived from holo structure binding-site templates. We perform benchmark tests on two different datasets: 40 structures from a directory of useful decoy-enhanced (DUD-E) and 84 structures from the Gunasekaran dataset. Our results show successful refinement of apo binding-site structures toward holo conformations in 82% of the test cases. In addition, virtual screening performance of 40 DUD-E structures is significantly improved using our MD-refined structures as receptors with an average enrichment factor (EF), an EF1% value of 6.2 compared to apo structures with 3.5. Docking of native ligands to the refined structures shows an average ligand root mean square deviation (RMSD) of 1.97 Å (DUD-E dataset and Gunasekaran dataset) relative to ligands in the holo crystal structures, which is comparable to the self-docking (i.e., docking of the native ligand back to its crystal structure receptor) average, 1.34 Å (DUD-E dataset) and 1.36 Å (Gunasekaran dataset). On the other hand, docking to the apo structures yields an average ligand RMSD of 3.65 Å (DUD-E) and 2.90 Å (Gunasekaran). These results indicate that our method is robust and can be useful to improve virtual screening performance of apo structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Systematic Improvement of Quantum Monte Carlo Calculations in Transition Metal Oxides: sCI-Driven Wavefunction Optimization for Reliable Band Gap Prediction

Accurate determination of the electronic properties of correlated oxides remains a significant challenge for computational theory. Traditional Hubbard-corrected density functional theory (DFT+U) frequently encounters limitations in precisely capturing electron correlation, particularly in predicting band gaps. We introduce a systematic methodology to enhance the accuracy of diffusion Monte Carlo (DMC) simulations for both ground and excited states, focusing on LiCoO 2 as a case study. By employing a selected configuration interaction (sCI) approach, we demonstrate the capability to optimize wavefunctions beyond the constraints of single-reference DFT+U trial wavefunctions. Here, we show that the sCI framework enables accurate prediction of band gaps in LiCoO 2 , closely aligning with experimental values and substantially improving traditional computational methods. The study uncovers a nuanced mixed state of t 2g and e g orbitals at the band edges that is not captured by conventional single-reference methods, further elucidating the limitations of PBE+U in describing d-d excitations. Our findings advocate for the adoption of beyond-DFT methodologies, such as sCI, to capture the essential physics of excited-state wavefunctions in strongly correlated materials. The improved accuracy in band gap predictions and the ability to generate more reliable trial wavefunctions for DMC calculations underscore the potential of this approach for broader applications in the study of correlated oxides. This work not only provides a pathway for more accurate simulations of electronic structures in complex materials but also suggests a framework for future investigations of the excited states of other challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strategies to Obtain Reliable Energy Landscapes from Embedded Multireference Correlated Wavefunction Methods for Surface Reactions

Embedded correlated wavefunction (ECW) theory is a powerful tool for studying ground- and excited-state reaction mechanisms and associated energetics in heterogeneous catalysis. Several factors are important to obtaining reliable ECW energies, critically the construction of consistent active spaces (ASs) along reaction pathways when using a multireference correlated wavefunction (CW) method that relies on a subset of orbital spaces in the configuration interaction expansion to account for static electron correlation, e.g., complete AS self-consistent field theory, in addition to the adequate partitioning of the system into a cluster and environment, as well as the choice of a suitable basis set and number of states included in excited-state simulations. Here, in this work, we conducted a series of systematic studies to develop best-practice guidelines for ground- and excited-state ECW theory simulations, utilizing the decomposition of NH 3 on Pd(111) as an example. We determine that ECW theory results are relatively insensitive to cluster size, the aug-cc-pVDZ basis set provides an adequate compromise between computational complexity and accuracy, and that a fixed-clean-surface approximation holds well for the derivation of the embedding potential. Additionally, we demonstrate that a merging approach, which involves generating ASs from the molecular fragments at each configuration, is preferable to a creeping approach, which utilizes ASs from adjacent structures as an initial guess, for the generation of consistent potential energy curves involving open-d-shell metal surfaces, and, finally, we show that it is essential to include bands of excited states in their entirety when simulating excited-state reaction pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Reliability of Hybrid Functionals for Accurate Fundamental and Optical Gap Prediction of Bulk Solids and Surfaces

Hybrid functionals have been considered insufficiently reliable for the prediction of band gaps in solids and surfaces. We revisit this issue with a new generation of optimally tuned range-separated hybrid functionals, focusing on the reconstructed Si(111)-(2×1) and Ge(111)-(2×1) surfaces. We show that certain hybrid functionals can accurately predict the surface-state and bulk fundamental and optical gaps, as well as projected band structures of these surfaces, by combining ground-state and time-dependent density functional theory.

Sagredo, Francisca↗