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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Integrated State Estimation and Contingency Analysis Software Implementation using High Performance Computing Techniques

Power system simulation tools are traditionally developed in sequential mode and codes are optimized for single core computing only. However, the increasing complexity in the power grid models requires more intensive computation. The traditional simulation tools will soon not be able to meet the grid operation requirements. Therefore, power system simulation tools need to evolve accordingly to provide faster and better results for grid operations. This paper presents an integrated state estimation and contingency analysis software implementation using high performance computing techniques. The software is able to solve large size state estimation problems within one second and achieve a near-linear speedup of 9,800 with 10,000 cores for contingency analysis application. The performance evaluation is presented to show its effectiveness.

Chen, Yousu↗
DOE OSTI2025

Adaptive Algebraic Derivative Estimation for Battery Electric Buses Energy Consumption Forecasting

The limited service life of onboard batteries for EVs is a challenge, underscoring the need for real-time battery usage prediction. This paper proposes an adaptive Algebraic Derivative Estimation (ADE) approach for forecasting the energy consumption of battery electric buses. By dynamically adjusting the sliding window length, the adaptive ADE retains the fixed-length ADE’s key advantage—namely, operating online without reliance on extensive historical datasets—while substantially bolstering forecast accuracy by actively trading estimation bias off estimation variance. Comparative experiments against both the conventional ADE with a fixed length and a representative machine learning algorithm, XGBoost, were conducted, with performance evaluated via root mean square error, mean absolute error, and the coefficient of determination. The results demonstrate that the proposed approach significantly outperforms baseline methods.

Cui, Tianyang [The University of Texas at Dallas]↗
DOE OSTI2025

Deep-learning-enhanced assessment of wellbore barrier effectiveness in geologic storage systems with intermediate aquifers

For geologic systems where carbon dioxide (CO 2 ) is injected underground, existing wells represent potential pathways for fluid migration. Here, this study introduces a novel deep learning model to quantify the likelihood and potential magnitude of fluid migration through wellbores at sites with intermediate aquifers or thief zones between the injection units and underground drinking water sources. Synthetic datasets, generated using reservoir simulations, captured a wide range of subsurface conditions, well attributes, operational parameters, and fluid migration scenarios. Among the regression models developed to predict brine and CO 2 leakage rates and CO 2 saturations along leaky wellbores, convolutional neural network (CNN) outperformed both Light Gradient Boosting Machine and deep neural network. Additionally, a CNN-based classification model was created to predict whether brine and CO 2 would leak along a wellbore, further improving performance over regression alone. The best models were integrated into the National Risk Assessment Partnership Open-source Integrated Assessment Model for rapid, stochastic assessment of storage system containment and leakage risks. A case study demonstrated the model’s ability to simulate fluid migration through existing wells with multiple intermediate aquifers. This computationally efficient wellbore model offers value in support of site performance evaluation and risk-informed decision making by stakeholders.

CO2 leakage↗
DOE OSTI2024

Investigation of precooling unit design options in hydrogen refueling station for heavy-duty fuel-cell electric vehicles

Precooling gaseous hydrogen fuel to a cold temperature before refueling a heavy-duty (HD) hydrogen fuel cell electric vehicle (HFCEV) is essential to avoid overheating the vehicle tank, as well as achieving a high state of charge (SOC). Because a large volume of hydrogen is dispensed during each fill, the need for a shorter fill time amplifies the need to precool each load for refueling a HFCEV. Thus, the design and operation of a precooling unit (PCU), as well as the associated capital and operating costs, plays a pivotal role in any plans for heavy-duty hydrogen refueling stations. Here, in this paper, we present a thermodynamic and technoeconomic analysis of a PCU in a gaseous hydrogen refueling station (HRS) for HD HFCEVs. By employing Argonne National Laboratory's hydrogen station cost optimization and performance evaluation (H2SCOPE) model, the refueling of 50 kg of hydrogen on-board type IV tank at ambient temperatures of 15–45 °C and varying fill rates is simulated. The required degree of precooling temperature to obtain either 100% or the maximum possible SOC is obtained from the simulation. Additionally, the simulation results demonstrate that the average flow rate of hydrogen is approximately 40% lower than the maximum flow rate during a typical fill; which motivates further evaluation of the instantaneous hydrogen mass flow rate profile and suggests the scope of improving precooling unit design. Accordingly, a hybrid strategy of precooling hydrogen has been proposed to address the cooling load by sizing the refrigeration unit for the average flow rate of hydrogen, while supplementing the above average peak hydrogen flow cooling load through thermal buffering. The combined technique enables the downsizing of the original PCU capacity by 25–40% and demonstrates a potential cost reduction of the PCU by approximately 30%, which translates to an installed cost reduction of ∼$125,000 per dispenser.

25 ENERGY STORAGE↗
DOE OSTI2019

Aminated poly(ethylene glycol) methacrylate resins as stable heterogeneous catalysts for the aldol reaction in water

Amine functionalized silicas have frequently been investigated as potential aldol reaction catalysts. However, active site leaching due to hydrolysis cannot be avoided, limiting the long-term stability of these catalysts in aqueous aldol reactions. Therefore, novel catalysts based on an organic resin have been developed starting from a suspension polymerized poly(ethylene glycol) methacrylate (PEGMA) hydrogel with poly(ethylene glycol) dimethacrylate (PEGDMA) as cross-linker. Amine functionalization was performed by chlorination of the terminal hydroxyl groups in the resulting PEGMA resin and subsequent nucleophilic substitution with an amine precursor, i.e., ethylenediamine (EDA), N,N'-dimethylethylenediamine (DED), or methylamine (MA). Additionally, the successful synthesis of the catalysts was confirmed by 13C NMR, FT-IR, and elemental CHN analysis. Performance evaluation in a batch reactor for the aqueous aldol reaction of acetone with 4-nitrobenzaldehyde resulted in a turnover frequency (TOF) of the PEGMA-EDA catalyst amounting to 6.3 ± 0.4 · 10 -4 s -1 , which is of the same order of magnitude as that of the corresponding state-of-the-art amine functionalized silica evaluated using hexane as solvent. The PEGMA-DED catalyst exhibited a somewhat lower TOF of 3.1 ± 0.2 · 10 -4 s -1 , while the PEGMA-MA catalyst did not exhibit any turnover, indicating that the secondary amine in the backbone of the active site in the PEGMA-EDA catalyst is inactive. Continuous-flow evaluation of the PEGMA-EDA catalyst in a packed-bed reactor indicated that, as opposed to a primary amine functionalized silica catalyst, a stable catalytic activity as a function of time on stream could be achieved for at least 8 h and, hence, that no deactivation has occurred in this timeframe.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Evaluating the Rheo-electric Performance of Aqueous Suspensions of Oxidized Carbon Black

Here, the macroscopic properties of carbon black suspensions are primarily determined by the agglomerate microstructure built of primary aggregates. Conferring colloidal stability in aqueous carbon black suspensions should thus have a drastic impact on their viscosity and conductivity. Carbon black was treated with strong acids following a wet oxidation procedure. An analysis of the resulting particle surface chemistry and electrophoretic mobility was performed in evaluating colloidal stability. Changes in suspension microstructure due to oxidation were observed using small-angle X-ray scattering. Utilizing rheo-electric measurements, the evolution of the viscosity and conductivity of the carbon black suspensions as a function of shear rate and carbon content was thoroughly studied. The carboxyl groups installed on the carbon black surface through oxidation increased the surface charge density and enhanced repulsive interactions. Electrostatic stability inhibited the formation of the large-scale agglomerates in favor of the stable primary aggregates in suspension. While shear thinning, suspension conductivities were found to be weakly dependent on the shear intensity regardless of the carbon content. Most importantly, aqueous carbon black suspensions formulated from electrostatically repulsive primary aggregates displayed a smaller rise in conductivity with carbon content compared to those formulated from attractive agglomerates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

HRSSA – Efficient hybrid stochastic simulation for spatially homogeneous biochemical reaction networks

This paper introduces HRSSA (Hybrid Rejection-based Stochastic Simulation Algorithm), a new efficient hybrid stochastic simulation algorithm for spatially homogeneous biochemical reaction networks. HRSSA is built on top of RSSA, an exact stochastic simulation algorithm which relies on propensity bounds to select next reaction firings and to reduce the average number of reaction propensity updates needed during the simulation. HRSSA exploits the computational advantage of propensity bounds to manage time-varying transition propensities and to apply dynamic partitioning of reactions, which constitute the two most significant bottlenecks of hybrid simulation. A comprehensive set of simulation benchmarks is provided for evaluating performance and accuracy of HRSSA against other state of the art algorithms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

On the performance of exponential integrators for problems in magnetohydrodynamics

Exponential integrators have been introduced as an efficient alternative to explicit and implicit methods for integrating large stiff systems of differential equations. Over the past decades these methods have been studied theoretically and their performance was evaluated using a range of test problems. While the results of these investigations showed that exponential integrators can provide significant computational savings, the research on validating this hypothesis for large scale systems and understanding what classes of problems can particularly benefit from the use of the new techniques is in its initial stages. Resistive magnetohydrodynamic (MHD) modeling is widely used in studying large scale behavior of laboratory and astrophysical plasmas. In many problems numerical solution of MHD equations is a challenging task due to the temporal stiffness of this system in the parameter regimes of interest. In this paper we evaluate the performance of exponential integrators on large MHD problems and compare them to a state-of-the-art implicit time integrator. Both the variable and constant time step exponential methods of EPIRK-type are used to simulate magnetic reconnection and the Kevin–Helmholtz instability in plasma. Performance of these methods, which are part of the EPIC software package, is compared to the variable time step variable order BDF scheme included in the CVODE (part of SUNDIALS) library. We study performance of the methods on parallel architectures and with respect to magnitudes of important parameters such as Reynolds, Lundquist, and Prandtl numbers. We find that the exponential integrators provide superior or equal performance in most circumstances and conclude that further development of exponential methods for MHD problems is warranted and can lead to significant computational advantages for large scale stiff systems of differential equations such as MHD.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Advanced high-performance large diameter Cs 2 HfCl 6 (CHC) and mixed halides scintillator

This paper reports on successful growth and performance evaluation of two large diameter Cs 2 HfCl 6 (CHC) and Cs 2 HfCl 4 Br 2 (CHCB), both recently developed scintillator crystals. The discovery of Cs 2 HfCl 6 (CHC) as a scintillator has lately generated much interest in this material and its family, which belongs to the K 2 PtCl 6 cubic crystal structure. CHC is an intrinsic scintillator that is non-hygroscopic (slightly deliquescent, i.e., slightly moisture sensitive but does not deteriorate much when left in air), has no self-radioactivity, provides excellent energy resolution, and has excellent non-proportionality. CHC has a moderate density of 3.9 g/cm 3 and an effective atomic number of 58. Reported in this paper are transparent crack-free single crystal CHC and CHCB boules of one inch in diameter, both grown using the vertical Bridgman method. Samples retrieved from the boules, sized 23 mm × 30 mm and 23 mm × 26 mm, respectively, are characterized for their optical and scintillation properties. Energy resolutions of 3.5% and 3.7% (FWHM) at 662 keV, respectively, are reported. Light yields of 23,000 ph/MeV and 20,000 ph/MeV have been calculated for the large diameter CHC and CHCB crystals, respectively. Results comparable to previously reported results for smaller crystals have been obtained. Studies on decay time, non-proportionality, as well as detector characterization are also reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Orientation-selected micro-pillar compression of additively manufactured 316L stainless steels: Comparison of as-manufactured, annealed, and proton-irradiated variants

In this work, irradiation response and deformation mechanisms of additively manufactured (AM) 316L stainless steel were studied by atomic scale characterization and micro-pillar compression. The AM 316L stainless steels were fabricated by direct energy deposition, a laser-based additive manufacturing process. Irradiation with 2 MeV protons at 360°C was performed to create ~1.8 displacements-per-atom (dpa) damage in AM 316L. Deformation behaviors of the as-manufactured, annealed, and proton-irradiated variants were studied, focusing on the effects of manufacturing-induced pores, residual stress, and irradiation-introduced defects (dislocation loops and voids). Micro-pillars were prepared from grains of pre-selected orientation, avoiding contributions of grain boundaries and allowing determination of resolved shear stress on {111} glide planes. Transmission electron microscopy was used to characterize the pre- and post-deformation microstructure. It was found that in the as-manufactured alloy variant, moving dislocations were the major deformation carrier, with noticeable blocking by fabrication-induced pores, In the annealed variant, hardness was reduced, and deformation was also accomplished by dislocation gliding. In the proton-irradiated variant, significant twinning was observed. Comparing measured resolved shear stress and predicted critical stress for dislocation dissociation, we conclude that irradiation hardening became high enough to activate twinning. Therefore, the deformation mechanism changes from dislocation gliding to twinning. The study is important for both processing optimization and performance evaluation of AM alloys for reactor applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Characterization of the radial microstructural evolution in LWR UO 2 using electron backscatter diffraction

Studies on high burnup UO 2 subjected to loss-of-coolant accident conditions have shown that restructured regions of the fuel are susceptible to pulverization and eventual dispersal. Due to a lack of pre-test characterization, the distinct microstructural features rendering the fuel prone to fragmentation remain ambiguous. Four samples of commercially irradiated light-water reactor UO 2 have been characterized utilizing electron backscatter diffraction to assess the susceptible microstructure. The microscopy focused on determining the burnup and temperature conditions responsible for the formation of the different microstructural regions where the regions were denoted as the high-burnup structure (HBS), HBS transition, mid-radial, restructured central, and central region. Previous works have outlined the specific conditions required for the restructuring of the microstructure into the HBS, but the conditions responsible for the restructuring in the central region of the fuel are not well understood. The four analyzed samples confirm a burnup threshold of 61 GWd/tU, and an unknown temperature range is needed to facilitate the formation of the restructured central region. In conclusion, additional fuel performance evaluations are needed to quantify the temperature range promoting restructuring in the central region.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Electrical edge effect induced photocurrent overestimation in low-light organic photovoltaics

In many literatures, the short-circuit current (J SC ) of indoor organic photovoltaics is overestimated, leading to severely wrong device performance evaluation and analysis. In this work, based on the equivalent circuit model, we demonstrate that electrical edge effect is sensitive to both transverse surface resistance and light intensity. At low light intensity, the electrical edge effect could lead to J SC being significantly overestimated, i.e., by 100% and even more. We show that for a PM6:Y6 device capped with a MoOX layer, when measured under 0.01 sun, the usually overlooked interface doping mechanism would lead to J SC and PCE overestimation by 51% and 15%, respectively. Besides, we show that the magnitude of J SC overestimation drastically increases with high photoactive-layer surface roughness. This work emphasized the significant electrical edge effect on J SC evaluations for low-light solar cells and is conducive to understanding the intrinsic mechanism of edge effect, promoting a healthier development of organic photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2015

Advances in Patch-Based Adaptive Mesh Refinement Scalability

Patch-based structured adaptive mesh refinement (SAMR) is widely used for high-resolution simu- lations. Combined with modern supercomputers, it could provide simulations of unprecedented size and resolution. A persistent challenge for this com- bination has been managing dynamically adaptive meshes on more and more MPI tasks. The dis- tributed mesh management scheme in SAMRAI has made some progress SAMR scalability, but early al- gorithms still had trouble scaling past the regime of 105 MPI tasks. This work provides two critical SAMR regridding algorithms, which are integrated into that scheme to ensure efficiency of the whole. The clustering algorithm is an extension of the tile- clustering approach, making it more flexible and efficient in both clustering and parallelism. The partitioner is a new algorithm designed to prevent the network congestion experienced by its prede- cessor. We evaluated performance using weak- and strong-scaling benchmarks designed to be difficult for dynamic adaptivity. Results show good scaling on up to 1.5M cores and 2M MPI tasks. Detailed timing diagnostics suggest scaling would continue well past that.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Optically connected memory for disaggregated data centers

Recent advances in integrated photonics enable the implementation of reconfigurable, high-bandwidth, and low energy-per-bit interconnects in next-generation data centers. We propose and evaluate an Optically Connected Memory (OCM) architecture that disaggregates the main memory from the computation nodes in data centers. OCM is based on micro-ring resonators (MRRs), and it does not require any modification to the DRAM memory modules. We calculate energy consumption from real photonic devices and integrate them into a system simulator to evaluate performance. Here, our results show that (1) OCM is capable of interconnecting four DDR4 memory channels to a computing node using two fibers with 1.02 pJ energy-per-bit consumption and (2) OCM performs up to 5.5× faster than a disaggregated memory with 40G PCIe NIC connectors to computing nodes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Radial feature descriptors for cell classification and recommendation

This paper introduces computational tools for cell classification into normal and abnormal, as well as content-based-image-retrieval (CBIR) for cell recommendation. It also proposes the radial feature descriptors (RFD), which define evenly interspaced segments around the nucleus, and proportional to the convexity of the nuclear boundary. Experiments consider Herlev and CRIC image databases as input to classification via Random Forest and bootstrap; we compare 14 different feature sets by means of False Negative Rate (FNR) and Kappa (κ), obtaining FNR =0.02 and κ=0.89 for Herlev, and FNR =0.14 and κ=0.78 for CRIC. Next, we sort and rank cell images using convolutional neural networks and evaluate performance with the Mean Average Precision (MAP), achieving MAP =0.84 and MAP =0.82 for Herlev and CRIC, respectively. Finally, cell classification show encouraging results regarding RFD, including its sensitivity to intensity variation around the nuclear membrane as it bypasses cytoplasm segmentation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Comparison of calculated dose distributions reported as dose-to-water and dose-to-medium for intensity-modulated radiotherapy of nasopharyngeal cancer patients

Advanced dose calculation algorithms for radiation therapy treatment planning can report external beam photon dose 2-sided, in terms of dose-to-medium (D{sub m}) and dose-to-water (D{sub w}). The purpose of our study was to determinate the effect of D{sub w} and D{sub m} reporting modes built in Elekta Monaco treatment planning system on intensity-modulated radiotherapy dose distributions for patients with nasopharyngeal cancer. For 13 patients involved in this retrospective study, 2 plans were created: 1 using D{sub w} and another according to D{sub m} reporting mode. Treatment plans were normalized such that 100% planning target volume should be covered by 95% of prescribed dose. Dose-volume constraints were assigned according to international standards. The comparison between dose distributions was performed evaluating quantities important for respective volumes of interest. For target volumes, heterogeneity index and conformity index methodology were used along with the maximum dose concept. Also, for the comparisons over particular organ at risk, maximum dose or mean dose as well as dose-volume concepts were used. For all target volumes and majority of organs at risk, the differences between 2 reporting modes are statistically insignificant, but this is not the case for bony structured organs at risks: mandible and cochlea. It was observed that D{sub w} is higher than D{sub m} with mean difference of 9.91% (p = 0.000009) of the mandible volume covered with 70 Gy. The same trend was observed for left and right cochlea with difference in mean dose of 8.74% (p = 0.037) and 6.87% (p = 0.029), respectively. The comparative analysis of dosimetric parameters in this study shows that the selection of reporting modes in Monaco treatment planning system can produce dose differences up to 15% in high-density volumes such as mandible and cochlea, which might have clinical consequences.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Edge-cloud computing performance benchmarking for IoT based machinery vibration monitoring

Advances in low cost and reliable sensing, connectivity (Internet of Things), computational power, and advanced analytics, are leading to a new wave of innovation in machinery status sensing and condition monitoring. Significant research efforts are directed towards cloud computing architectures. However, given the latency, bandwidth, cost, security, and privacy concerns, further supported by the ever-increasing capabilities of edge computing devices, there is a need to consider both edge and cloud computing together to make informed decisions based upon context and performance. In this work, we present an edge-cloud performance evaluation for IoT based machinery vibration monitoring, to foster deployment for the contexts considered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Insights into enhanced sodium ion storage mechanism in Fe 3 S 4 : The coupling of surface chemistry, microstructural regulation and 3D electronic transport

Sodium ion batteries (SIBs) are considered a potential energy storage technology due to their low cost and the abundance of sodium resources. Numerous strategies have been made to address the remaining challenges such as low electronic conductivity, huge volume change, and sluggish sodium ions kinetics. In spite of impressive advances, a comprehensive understanding of the microstructure-stability correlation remains elusive. Here, the three-dimensional (3D) Fe 3 S 4 flower-like hierarchical materials constructed from two-dimensional (2D) nanosheet building units were synthesized via a facile and cost-effective method. Instead of materials synthesis and performance evaluation, more attentions have been paid on the underlying coupling mechanism between microstructure design, surface chemistry and 3D electronic/ionic transport pathways. It found that the thin and stable SEI layer generated by ether-based electrolytes contributes to the stable surface chemistry and fast interfacial Na + ion transport, while 3D hierarchical structure enables short diffusion distance, volume change accomodation as well as stabilizing SEI layer. Taking advantage of the inherent high electronic conductivity in Fe 3 S 4 , we have demonstrated the paramount importance of the synergistic strategy to improve the stability of SIBs through X-ray nanotomography. In conclusion, this work explicitly illuminate the electrochemical stability mechanisms of 3D hierarchitectures and resolves new strategies to rational design SIBs anodes.

77 NANOSCIENCE AND NANOTECHNOLOGY↗