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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Impact of cyber attacks on distributed compressive sensing based state estimation in power distribution grids

Modern power distribution grids suffer from multiple vulnerabilities due to the tight integration between the physical system and the cyber infrastructure. Sophisticated and malicious cyber attacks continue to adversely impact the grid operation leading to performance degradation, service interruption, and grid failure. State estimation plays an essential role in grid monitoring and advancing cyber-attack situational awareness. In this regard, this paper first proposes a distributed compressive sensing (CS) state estimation approach for an unobservable distribution grid. Further, the proposed distributed CS approach divides the distribution grid into sub-areas to perform local state estimation. Then an alternating direction method of multipliers (ADMM) based iterative information exchange among neighboring areas is employed to complete the estimation process. In this estimation process, the impact of loss of measurement data, false data injection (FDI), replay, and neighborhood cyber-attacks is analyzed. Extensive simulations are performed on the IEEE 37-bus and IEEE 123-bus standard networks to demonstrate the algorithm’s robustness to the aforementioned cyber-attacks. A quantitative analysis of computational complexity and simulation time of the distributed CS based approach is also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Simulations of the effects of proppant placement on the conductivity and mechanical stability of hydraulic fractures

Here, we generate a wide range of models of proppant-packed fractures using discrete element simulations, and measure fracture conductivity using finite element flow simulations. This allows for a controlled computational study of proppant structure and its relationship to fracture conductivity and stress in the proppant pack. For homogeneous multi-layered packings, we observe the expected increase in fracture conductivity with increasing fracture aperture, while the stress on the proppant pack remains nearly constant. This is consistent with the expected behavior in conventional proppant-packed fractures, but the present work offers a novel quantitative analysis with an explicit geometric representation of the proppant particles. In single-layered packings (i.e. proppant monolayers), there is a drastic increase in fracture conductivity as the proppant volume fraction decreases and open flow channels form. However, this also corresponds to a sharp increase in the mechanical stress on the proppant pack, as measured by the maximum normal stress relative to the side crushing strength of typical proppant particles. We also generate a variety of computational geometries that resemble highly heterogeneous proppant packings hypothesized to form during channel fracturing. In some cases, these heterogeneous packings show drastic improvements in conductivity with only moderate increase in the stress on the proppant particles, suggesting that in certain applications these structures are indeed optimal. We also compare our computer-generated structures to micro computed tomography imaging of a manually fractured laboratory-scale shale specimen, and find reasonable agreement in the geometric characteristics.

58 GEOSCIENCES↗
DOE OSTI2015

Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective

Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both prognostic and therapeutic purposes has exploded thanks to increasing availability of electronic data and genomics. One promising direction that medical modeling is moving toward is adopting the same machine learning methods used by companies such as Google and Facebook to combat disease. Broadly defined, machine learning is a branch of computer science that deals with making predictions from complex data through statistical models. These methods serve to uncover patterns in data and are actively used in areas such as speech recognition, handwriting recognition, face recognition, “spam” filtering (junk email), and targeted advertising. Although multiple radiation oncology research groups have shown the value of applied machine learning (ML), clinical adoption has been slow due to the high barrier to understanding these complex models by clinicians. Here, we present a review of the use of ML to predict radiation therapy outcomes from the clinician's point of view with the hope that it lowers the “barrier to entry” for those without formal training in ML. We begin by describing 7 principles that one should consider when evaluating (or creating) an ML model in radiation oncology. We next introduce 3 popular ML methods—logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN)—and critique 3 seminal papers in the context of these principles. Although current studies are in exploratory stages, the overall methodology has progressively matured, and the field is ready for larger-scale further investigation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Large balancing areas and dispersed renewable investment enhance grid flexibility in a renewable-dominant power system in China

Renewable energy is poised to play a major role in achieving China's carbon neutrality goal by 2060; however, reliability and flexibility is a big concern of a renewable-dominant power system. Various strategies of enhancing flexibility are under discussion to ensure the reliability of such a system, but no detailed quantitative analysis has been reported yet in China. We combine the advantages of a capacity expansion model, SWITCH-China, with a production simulation model, PLEXOS, and analyze flexibility options under different scenarios of a renewable-dominant power system in China. We find that a larger balancing area offers direct flexibility benefits. Regional balancing could reduce the renewable curtailment rate by 5-7%, compared with a provincial balancing strategy. National balancing could further reduce the power cost by about 16%. However, retrofitting coal power plants for flexible operation would only improve the system flexibility marginally.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Towards the next generation of Geospatial Artificial Intelligence

Geospatial Artificial Intelligence (GeoAI), as the integration of geospatial studies and AI, has become one of the fastest-developing research directions in spatial data science and geography. This rapid change in the field calls for a deeper understanding of the recent developments and envision where the field is going in the near future. In this work, we provide a quantitative analysis of the GeoAI literature from the spatial, temporal, and semantic aspects. We briefly discuss the history of AI and GeoAI by highlighting some pioneering work. Then we discuss the current landscape of GeoAI by selecting five representative subdomains including remote sensing, urban computing, Earth system science, cartography, and geospatial semantics. Finally, we highlight several unique future research directions of GeoAI which are classified into two groups: GeoAI method development challenges and GeoAI Ethics challenges. Topics include heterogeneity-aware GeoAI, knowledge-guided GeoAI, spatial representation learning, geo-foundation models, fairness-aware GeoAI, privacy-aware GeoAI, as well as interpretable and explainable GeoAI. We hope our review of GeoAI’s past, present, and future is comprehensive and can enlighten the next generation of GeoAI research.

58 GEOSCIENCES↗
DOE OSTI2018

3D microstructure reconstruction of casting aluminum alloy based on serial block-face scanning electron microscopy

In this work, the inner microstructure of aluminum-silicon casting alloy was experimentally investigated to reveal the spatial morphology and phase distribution. Its industrial use is as a light-weight structural material. As a powerful three-dimensional (3D) imaging tool at the nano-scale, the serial block-face scanning electron microscopy (SBFSEM) was employed to investigate the specimens. After being 3D reconstructed, the images were visualized to identify preference for several specific intermetallics by quantitative analysis. It was found that these phases have certain relationships in spatial distribution and differences in spatial shapes. In conclusion, the spatial distribution of cracks was studied to understand their propagation and growth.

3D microstructure reconstruction↗
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 OSTI2016

Dynamical behaviors of structural, constrained and free water in calcium- and magnesium-silicate-hydrate gels

We present the hypothesis that the mechanical properties of cement pastes depend strongly on their porosities. In a saturated paste, the porosity links to the free water volume after hydration. Structural water, constrained water, and free water have different dynamical behavior. Hence, it should be possible to extract information on pore system by exploiting the water dynamics. With our experiments we investigated the slow dynamics of hydration water confined in calcium- and magnesium-silicate-hydrate (C-S-H and M-S-H) gels using high-resolution quasi-elastic neutron scattering (QENS) technique. C-S-H and M-S-H are the chemical binders present in calcium rich and magnesium rich cements. We measured three M-S-H samples: pure M-S-H, M-S-H with aluminum-silicate nanotubes (ASN), and M-S-H with carboxyl group functionalized ASN (ASN-COOH). A C-S-H sample with the same water content (i.e. 0.3) is also studied for comparison. We found that structural water in the gels contributes to the elastic component of the QENS spectrum, while constrained water and free water contribute the quasi-elastic component. The quantitative analysis suggests that the three components vary for different samples and indicate the variance in the system porosity, which controls the mechanical properties of cement pastes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Enhancing low-temperature sintering in the MgO-LiF system: Mechanistic insights

In the present article, we provide compelling evidence that minor (1 wt%) additions of micron and nanometre-sized LiF particles in MgO decompose leading to free Li diffusing into MgO surfaces enhancing vacancy production during direct current sintering. The addition of nanometre-sized LiF particles leads to a > 500 °C reduction in the sintering temperature and over 99 % theoretical density of final consolidated compacts. Correlating differential scanning calorimetry with in-situ x-ray diffraction, together with Schottky calculations, post sintering electron microscopy and laser induced breakdown spectroscopy, we uncover critical insights into this impressive reduction in sintering temperature. Our quantitative analysis reveals that MgO and LiF interact at low temperatures with the diffusion of Li into the surface of MgO particles due to the intrinsic structural disorder of the LiF and MgO crystallites. Nanometre-sized LiF particles were found to react the most at low temperatures due to their increased structural disorder. Our multimodal characterization points to a Li-promoted densification and sintering mechanism. This impressive reduction in sintering temperature can be harnessed to promote low-temperature fabrication of MgO-based composites for technological applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Blending low-carbon hydrogen with natural gas: Impact on energy and life cycle emissions in natural gas pipelines

In this article, hydrogen (H 2 ) is considered an alternative energy carrier to reduce greenhouse gas (GHG) emissions related to power and heat generation. A quantitative analysis was conducted to estimate the energy intensity and GHG emissions associated with the transportation of NG/H 2 mixture in high-pressure transmission pipeline, considering blending ratios up to 100% of low-carbon H 2 . The life cycle emissions were obtained by including upstream supply chain emissions, compression and transportation emissions, and end use combustion emissions of the NG/ H 2 blend. This study accounts for global warming potential of fugitive methane and H 2 emissions associated with pipeline transportation of the blend in the life cycle analysis. A significant reduction in the overall life cycle GHG emissions can be achieved when delivering the same volume throughput but at a reduced energy flow to end users. However, to maintain the nominal energy throughput of the pipeline regardless of the H 2 mole fraction, a maximum reduction of about 6% is obtained as the H 2 mole fraction in the blend will be practically limited to approximately 30% H 2 when the pipeline operates at capacity.

03 NATURAL GAS↗
DOE OSTI2018

Evolution of ion damage at 773K in Ni- containing concentrated solid-solution alloys

Quantitative analysis of the impact of the compositional complexity in a series of Ni-containing concentrated solid-solution alloys, Ni, NiCo, NiFe, NiCoCr, NiCoFeCr, NiCoFeCrMn and NiCoFeCrPd, on the evolution of defects produced by 1 MeV Kr ion irradiation at 773 K is reported in this paper. The dynamics of the evolution of the damage structure during irradiation to a dose of 2 displacements per atom were observed directly by performing the ion irradiations in electron transparent foils in a transmission electron microscope coupled to an ion accelerator. The defect evolution was assessed through measurement of the defect density, defect size and fraction of perfect and Frank loops. These three parameters were dependent on the alloying element as well as the number of elements. The population of loops was sensitive to the ion dose and alloy composition as faulted Frank loops were observed to unfault to perfect loops with increasing ion dose. Finally, these dependences are explained in terms of the influence of each element on the lifetime of the displacement cascade as well as on defect formation and migration energies.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Combined effect of injected interstitials and He implantation, and cavities inside dislocation loops in high purity Fe-Cr alloys

High purity Fe-Cr alloys with Cr content ranging from 3 to 14 wt% were irradiated by self-ions at 500 °C in dual-beam mode up to 157 displacements per atom (dpa), 17 appm He/dpa. Transmission electron microscopy (TEM) on focused ion beam foils revealed the depth distribution of irradiation induced cavities and dislocation loops. A detailed quantitative analysis of cavity microstructure was performed on Fe14%Cr, while Fe(3, 5, 10, 12)%Cr were analyzed qualitatively. A homogeneous distribution of small cavities were observed up to the damage peak. From surface to the damage peak, cavity number density increased almost linearly. The cavity microstructure changed drastically at and after the damage peak, where the size increased and number density decreased. Most notably, the microstructure consisted of a striking mixture of heterogeneously nucleated cavities inside dislocation loops and freely nucleated cavities in the matrix. Further, the depth-dependent void swelling increased continuously along the damage depth. This contrasts with most ion irradiation results where suppression of void swelling occurs adjacent to the damage peak due the injected interstitial effect. We hypothesize a plausible mechanism of the observed swelling variation based on a combined effect of the injected interstitials and helium implantation near the damage peak by comparing the results with those in pure iron irradiated under same conditions. This synergistic effect may develop cavity microstructures which do not necessarily reflect microstructures expected due to injected interstitial effect and can be easily wrongly interpreted. The depth dependent dislocation loop microstructure was studied qualitatively in Fe14%Cr sample. Up to the damage peak, a complex dense network of dislocations formed due to the interaction/impingement of the dislocation loops. Individually resolvable loops were only observed after the damage peak, where their association with cavities was noted. Furthermore helium also induced heterogeneous cavity nucleation on dislocations constituting a grain boundary and on pre-existing dislocation lines.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Plasticity of irradiated materials at the nano and micro-scales

Here, we review here our recent work on plastic deformation in irradiated materials at the nano- and micro-scales, as revealed by Discrete Dislocation Dynamics (DDD) simulations. Two methods of including irradiation effects in the DDD framework are presented. The first directly captures the atomistic interaction mechanisms, while the second can effectively study high-dose irradiation. Computer simulations lead to new understanding of the dynamics of collective dislocation-irradiation defect interactions, as well as the quantitative analysis of the temporal and spatial characteristics associated with plastic instabilities. Based on these insights, theoretical models are developed to predict the critical conditions for dislocation channel formation. A simple probability model is proposed and demonstrated to predict the width of dislocation channels in bulk irradiated materials with good agreement with experimental data. The fundamental understanding of the origins of plastic flow localization in irradiated materials sheds light on the design of future generations of radiation-resistant materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Microstructure of irradiated AGR TRISO particle buffer layers as measured by X-ray computed tomography

Shrinkage of the initially low-density buffer layer in tristructural isotropic (TRISO) coated fuel particles during irradiation is a well-known phenomenon with potential implications for fission product and actinide transport, as well as potential pyrocarbon fracture that in some cases has been observed to impact particle performance. During post-irradiation examination, the buffer layer's structure is commonly determined using 2D microscopy of a particle cross section or a series of particle cross sections at staggered depths. Although these methods provide a general idea of the irradiated buffer microstructure, they do not provide a full picture of the TRISO coating microstructure. By contrast, x-ray computed tomography (XCT) provides full 3D imaging of the TRISO particle. Particles from various compacts irradiated for the Advanced Gas Reactor Fuel Development and Qualification Program were imaged using XCT. Some of these particles were selected because of abnormal fission product inventories (e.g., low 137 Cs), whereas others were randomly selected from the center of the fission product inventory distribution. Qualitative and quantitative analysis techniques were applied to the randomly selected particles as representatives of typical TRISO behavior to study the post-irradiation structure of the buffer layer. These results showed that, while separation of the buffer and inner pyrolytic carbon layers was a common behavior during the radiation-induced shrinkage of the buffer, a portion of the original buffer/inner pyrolytic carbon interface remained intact throughout irradiation in nearly all cases. Furthermore, these results also indicated clear trends in the degree of buffer densification with irradiation temperature and fluence.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Through-thickness fracture behavior of neutron-irradiated nuclear graphite NBG-17 Using X-ray micro-CT

Achieving precise control over crack propagation in nuclear graphite and conducting quantitative analysis remain challenging. In this study, the through-thickness fracture behavior of pristine and neutron-irradiated (700 °C, ∼7 dpa) NBG-17 nuclear graphite was investigated using split-disc testing coupled with micro-computed tomography (micro-CT). A notably lower number of micropores was observed in the neutron-irradiated specimen. The fracture toughness of neutron-irradiated NBG-17 was measured to be 1.45 MPa√m, compared to 1.17 ± 0.05 MPa√m for the pristine specimen. In both materials, cracks were found to initiate at the filler–binder interface, and often correlated with microstructural features such as pores and thermal cracks. Crack bridging and deflections emerged as the primary toughening mechanisms in both unirradiated and irradiated NBG-17. However, compared with the pristine specimen, the cracks in the neutron-irradiated specimen were more likely to grow trans granularly, resulting in less deflected crack paths. The reduced micro-porosity and strengthened filler–binder boundaries were considered to be the cause of the observed differences in crack morphologies. In conclusion, this study provides a qualitative analysis of the fracture behavior of neutron-irradiated nuclear graphite in the absence of radiolytic oxidation.

36 - MATERIALS SCIENCE↗