Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Strain mapping”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 847 records · Page 47

Ice velocity at the ice front of the Filchner-Ronne Ice Shelf, Antarctica, as observed with ERS interferometry

ERS images of the two ends of the ice front of the Filchner-Ronne ice shelf (Antarctica) were utilized interferometrically to study the deformation rate of the ice shelf in response to viscous creep. On the western bank of Berkner Island (BI), near Hemmen Ice Rise (HIR), a time series of ERS data acquired in February 1992, in both ascending and descending mode, and with a three-day time interval, were utilized to map the ice velocity in two dimensions. Finite-element ice-shelf flow simulations are compared with the ERS interferograms to interpret the ice motion in terms of the physical constraints on ice-shelf flow. The efforts to fit artificial interferograms generated with model velocity output suggest that the flow regime is strongly influenced by three processes. First, a void-creation process responsible for rifts at coastal margins tends to uncouple the ice shelf from the ice rise and neighboring coast of BI. Secondly, sea ice within the void space appears to act as a binding agent between discrete ice-shelf fragments, allowing rigid-body rotations of these fragments. Third, strain rates appear to be enhanced in a narrow zone adjacent to HIR, implying significant strain softening along the boundary. It is believed that synthetic aperture radar (SAR) interferogram/model intercomparison represents a powerful impetus towards the development of better, more physically realistic ice-shelf flow models.

Rignot, Eric↗

High Energy Physics Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and High Energy Physics, June 10-12, 2015, Bethesda, Maryland

The U.S. Department of Energy (DOE) Office of Science (SC) Offices of High Energy Physics (HEP) and Advanced Scientific Computing Research (ASCR) convened a programmatic Exascale Requirements Review on June 10–12, 2015, in Bethesda, Maryland. This report summarizes the findings, results, and recommendations derived from that meeting. The high-level findings and observations are as follows. Larger, more capable computing and data facilities are needed to support HEP science goals in all three frontiers: Energy, Intensity, and Cosmic. The expected scale of the demand at the 2025 timescale is at least two orders of magnitude — and in some cases greater — than that available currently. The growth rate of data produced by simulations is overwhelming the current ability of both facilities and researchers to store and analyze it. Additional resources and new techniques for data analysis are urgently needed. Data rates and volumes from experimental facilities are also straining the current HEP infrastructure in its ability to store and analyze large and complex data volumes. Appropriately configured leadership-class facilities can play a transformational role in enabling scientific discovery from these datasets. A close integration of high-performance computing (HPC) simulation and data analysis will greatly aid in interpreting the results of HEP experiments. Such an integration will minimize data movement and facilitate interdependent workflows. Long-range planning between HEP and ASCR will be required to meet HEP’s research needs. To best use ASCR HPC resources, the experimental HEP program needs (1) an established, long-term plan for access to ASCR computational and data resources, (2) the ability to map workflows to HPC resources, (3) the ability for ASCR facilities to accommodate workflows run by collaborations potentially comprising thousands of individual members, (4) to transition codes to the next-generation HPC platforms that will be available at ASCR facilities, (5) to build up and train a workforce capable of developing and using simulations and analysis to support HEP scientific research on next-generation systems.

97 MATHEMATICS AND COMPUTING↗

Influence of Phase-Change Materials and Operating Periods on Load Shifting for Thermal Storage Heat Pumps in European Climate Zones

As the reliance on heat pumps (HPs) for space conditioning increases worldwide, ex-tensive grid strains during utility peak hours are expected. Significant research efforts focus on investigating the use of integrated thermal energy storage (TES) systems to reduce peak energy demands. Conventionally, TES systems are often integrated to store and provide either cooling or heating, but not both. In this work, a single room-temperature phase-change material (PCM)-TES was integrated for dual-mode opera-tion with an R290 air-to-water 10.5 kW (3-Ton) HP. Two PCM melting temperatures (17°C, 22°C) were assessed to investigate their impact on system performance and cost reductions for Milan, Italy (4A); Barcelona, Spain (3A); and Oslo, Norway (6A). HP and HP-TES performance maps were generated using Modelica-based transient models and co-simulated with a prototype residential building using the Spawn of En-ergyPlusTM with simple rule-based controls. Our simulations indicate that PCM-17°C provided annual cost savings at higher peak-to-off-peak cost ratios, as the demand re-duction dominated the savings potential. The recharge energy costs and requirements became more dominant at lower cost ratios, making PCM-22°C more beneficial at lower cost ratios. Finally, despite Oslo's heating-dominated climate, the utility peak hours favor cooling demand reductions, making PCM-17°C more appealing. In all cases, the cost savings potential stabilized between 4 – 10% regardless of cost ratio, suggesting that system-level component and operation control optimization is required to maximize cost savings further.

25 ENERGY STORAGE↗

Brittle failure analysis and modeling of high-burnup PWR fuel cladding alloys

The aim of this research is the development of methods for predicting mechanical behavior and identification of limiting conditions to prevent brittle failure of high-burnup (HBU) pressure water reactor (PWR) fuel cladding alloys. A finite element (FE) model of the ring compression test (RCT) was created to analyze the failure behavior of zirconium-based alloys with radial hydrides during the RCT. An elastic-plastic material model describes the zirconium alloy. The stress-strain curve needed for the elastic-plastic material model was derived by inverse finite element analyses. Cohesive zone modeling is used to reproduce sudden load drops during RCT loading. Based on the failure mechanism in non-irradiated ZIRLO (R) claddings, a micro-mechanical model was developed that distinguishes between brittle failure along hydrides and ductile failure of the zirconium matrix. Two different cohesive laws representing these types of failure are present in the same cohesive interface. The key differences between these constitutive laws are the cohesive strength, the stress at which damage initiates, and the cohesive energy, which is the damage energy dissipated by the cohesive zone. Statistically generated matrix-hydride distributions were mapped onto the cohesive elements and simulations with focus on the first load drop were performed. Computational results are in good agreement with the RCT results conducted on high-burnup M5 (R) samples. It could be shown that crack initiation and propagation strongly depend on the specific configuration of hydrides and matrix material in the fracture area.

Simbruner, Kai↗

Exploring Domain-Wall Pinning in Ferroelectrics via Automated High-Throughput Atomic Force Microscopy

Domain-wall dynamics in ferroelectric materials are strongly position-dependent, since each polar interface is locked into a unique local microstructure. This necessitates spatially resolved studies of wall pinning using scanning-probe microscopy techniques. The pinning centers and pre-existing domain walls are usually sparse within the image plane, precluding the use of dense hyperspectral imaging modes and requiring time-consuming human experimentation. Here, a large-area epitaxial PbTiO 3 film on cubic KTaO 3 was investigated to quantify the electric-field-driven dynamics of the polar–strain domain structures using ML-controlled automated piezoresponse force microscopy. Analysis of 1500 switching events reveals that domain-wall displacement depends not only on field parameters but also on the local ferroelectric–ferroelastic configuration. For example, twin boundaries in polydomains regions, like a 1 – /c+ ∥ a 2 – /c – , stay pinned up to a certain level of bias magnitude and change only marginally as the bias increases from 20 to 30 V, whereas single-variant boundaries, like the a 2 + /c + ∥ a 2 – /c – stack, are already activated at 20 V. These statistics on the possible ferroelectric and ferroelastic wall orientations, together with the automated high-throughput AFM workflow, can be distilled into a predictive map that links domain configurations to pulse parameters. Here, this microstructure-specific rule set forms the foundation for the design of ferroelectric memories.

automated scanning probe microscopy↗

Validation of finite-element models using full-field experimental data: Levelling finite-element analysis data through a digital image correlation engine

Full-field data from digital image correlation (DIC) provide rich information for finite-element analysis (FEA) validation. However, there are several inherent inconsistencies between FEA and DIC data that must be rectified before meaningful, quantitative comparisons can be made, including strain formulations, coordinate systems, data locations, strain calculation algorithms, spatial resolutions and data filtering. As such, in this paper, we investigate two full-field validation approaches: (1) the direct interpolation approach, which addresses the first three inconsistencies by interpolating the quantity of interest from one mesh to the other, and (2) the proposed DIC-levelling approach, which addresses all six inconsistencies simultaneously by processing the FEA data through a stereo-DIC simulator to ‘level’ the FEA data to the DIC data in a regularisation sense. Synthetic ‘experimental’ DIC data were generated based on a reference FEA of an exemplar test specimen. The direct interpolation approach was applied, and significant strain errorswere computed, even though therewas no model form error, because the filtering effect of theDIC enginewas neglected. In contrast, the levelling approach provided accurate validation results, with no strain error when no model form error was present. Next, model form error was purposefully introduced via a mismatch of boundary conditions. With the direct interpolation approach, the mismatch in boundary conditions was completely obfuscated, while with the levelling approach, it was clearly observed. Finally, the ‘experimental’ DIC datawere purposefully misaligned slightly fromthe FEA data. Both validation techniques suffered from the misalignment, thus motivating continued efforts to develop a robust alignment process. In conclusion, direct interpolation is insufficient, and the proposed levelling approach is required to ensure that the FEA and the DIC data have the same spatial resolution and data filtering. Only after the FEA data have been ‘levelled’ to the DIC data can meaningful, quantitative error maps be computed.

42 ENGINEERING↗

Terahertz Nano-Imaging of Electronic Strip Heterogeneity in a Dirac Semimetal

Emerging topological semimetals offer promise of realizing topological electronics enabled by terahertz (THz) current persistent against impurity scattering. Yet most fundamental issues remain on how to image nanoscale conductivity inhomogeneity. Here in this paper we show noninvasive and contactless conductivity mapping at THz-nm limit of electronic heterogeneity and nanostrip junctions in a Dirac material ZrTe 5 . A clear Dirac Fermion density transition, manifested as the exclusive THz conductivity contrast, is quantitatively analyzed and profiled on both sides of the junction. This also allows the determination of variable junction width of ~25–220 nm, depending on the THz conductivity contrast of adjacent strips. The unique THz-nm contrast is absent in mid-infrared nano-imaging measurements since topological semimetals with small Fermi pockets exhibit a better matching of their plasma frequency and scattering rate to the THz spectral region. The first-principles calculations provide two compelling implications: the conductivity nanocontrast can be induced by a small anisotropic strain, even less than 0.5%, due to an extreme strain sensitivity in ZrTe 5 ; A nanoscale topological phase transition is realized across some junctions induced by the strain, between strong topological insulators (TIs) and weak TIs/Dirac semimetals (DSMs).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ISOFINEL: Isoparametric finite element code for elastic analysis of two-dimensional bodies

A formulation is presented for the development of a finite element program for the elastic analysis of two-dimensional bodies using the eight-node isoparametric quadrilateral. The program solves for both plane stress and plane strain problems. The finite element formulation based on the isoparametric displacement functions is presented. The program structure is given in the form of flow diagrams with descriptions of the numerical procedure used to obtain the element stiffness matrix, and the solution method employed to solve for nodal displacements. Three numerical examples (a plate under uniaxial tension, a plate under pure shear, and a beam under pure bending) are presented to illustrate the capability and limitations of the element implementation. The first problem is solved exactly by the element, as predicted by the form of its displacement functions. In the other two problems the accuracy of the solution is highly dependent upon the slenderness of the element, the number of elements in the map, and the numerical integration scheme used to build the element stiffness matrix.

Marino, C.↗

ERTS Applications in earthquake research and mineral exploration in California

Examples that ERTS imagery can be effectively utilized to identify, locate, and map faults which show geomorphic evidence of geologically recent breakage are presented. Several important faults not previously known have been identified. By plotting epicenters of historic earthquakes in parts of California, Sonora, Mexico, Arizona, and Nevada, we found that areas known for historic seismicity are often characterized by abundant evidence of recent fault and crustal movements. There are many examples of seismically quiet areas where outstanding evidence of recent fault movements is observed. One application is clear: ERTS-1 imagery could be effectively utilized to delineate areas susceptible to earthquake recurrence which, on the basis of seismic data alone, may be misleadingly considered safe. ERTS data can also be utilized in planning new sites in the geophysical network of fault movement monitoring and strain and tilt measurements.

Abdel-Gawad, M.↗

Distributed Temperature Sensing within a 19-pin Wire-Wrapped Fuel Bundle Model

It has always been difficult to measure local temperature and flow velocity within fuel bundle geometries because of their complex and compact layouts. High-resolution mapping of the flow field is especially challenging. High-resolution data is typically obtained using optical instruments but optical access to the interior regions of a bundle is severely limited. Velocity fields within fuel bundle models have been mapped with particle image velocimetry (PIV), an optical technique that employs lasers and cameras. Optical access to the bundle interior is obtained using transparent materials and matching the refractive index of the physical structures with that of the fluid. Testing is necessarily isothermal because refractive indices vary with temperature. However, the ultimate aim of such studies is understanding fluid dynamics and heat transfer within real reactors and so flow field mapping under nonisothermal conditions is of particular interest. Temperature fields can be mapped at high-resolution using laser-induced fluorescence (LIF). However, as an optical technique it is unsuitable for nonisothermal liquid flows. This is due to the same sort of optical distortion that restricts PIV. It is also unsuitable for opaque fluids and setups with restricted optical access. Fiber optic distributed temperature sensing (DTS) offers a high-resolution alternative that does not rely upon imaging. A single sensor can map temperature fields at resolutions far exceeding that achievable with conventional sensors such as thermocouples. Though fiber optic sensors cannot match the spatial resolution and bandwidth of LIF, they are suitable for nonisothermal and opaque flows. And though fibers are physical probes that perturb the flow, they can be strung across complex geometries to provide data in regions lacking the optical access necessary for techniques like LIF. Distributed temperature sensing has the potential to provide fuel bundle temperature data of a type that cannot be obtained with optical methods or conventional sensors. This paper reports on preliminary results of efforts to use fiber optic distributed temperature sensors in a fuel bundle model. We are conducting a feasibility study exploring implementation issues such as strain control in the mounting configuration and signal noise associated with flow-induced vibration. We describe here the setup and present preliminary data from our first phase testing with stagnant flow. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

3D characterization of a Great Basin geothermal system: Astor Pass, NV

The Great Basin exhibits both anomalously high heat flow (~75±5 mWm-2) and active faulting and extension resulting in robust geothermal activity. There are ~430 known geothermal systems in the Great Basin, with evidence suggesting that undiscovered blind geothermal systems may actually represent the majority of geothermal activity. These systems employ discrete fault intersection/interaction areas as conduits for geothermal circulation. Recent studies show that steeply dipping normal faults with step-overs, fault intersections, accommodation zones, horse-tailing fault terminations and transtensional pull-aparts are the most prominent structural controls of Great Basin geothermal systems. These fault geometries produce sub-vertical zones of high fault and fracture density that act as fluid flow conduits. Structurally controlled fluid flow conduits are further enhanced when critically stressed with respect to the ambient stress conditions. The Astor Pass blind geothermal system, northwestern Nevada, lies along the boundary between the Basin and Range to the east and the Walker Lane to the west. Along this boundary, strain is transferred from dextral shear in the Walker Lane to west-northwest directed extension in the Basin and Range. As such, the Astor Pass area lies in a transtensional setting consisting of both northwest-striking, left-stepping dextral faults and more northerly striking normal faults. The Astor Pass tufa tower implies the presence of a blind geothermal system. Previous studies suggest that deposition of the Astor Pass tufa was controlled by the intersection of a northwest-striking dextral normal fault and north-northwest striking normal fault. Subsequent drilling (to ~1200 m) has revealed fluid temperatures of ~94°C, confirming the presence of a blind geothermal system at Astor Pass. Expanding upon previous work and employing additional detailed geologic mapping, interpretation of 2D seismic reflection data and analysis of well cuttings, a 3-dimensional geologic model of the Astor Pass blind geothermal system was constructed. The 3D structural framework indicates that the Pleistocene tufa is associated with three discrete fault zones whose intersections plunge moderately to steeply NW-NNW. These critically stressed fault intersections act as conduits for upwelling geothermal fluids.

15 GEOTHERMAL ENERGY↗

Kinetic Deep Learning v0.1

Here, we present a method that uses protein levels to predict times series of metabolite concentrations. Understanding this type of pathway dynamics is important in order to predict the behavior of the pathway and, more pragmatically, to be able to design biological systems (such as strains bioengineered to produce chemical products) reliably. Typically, for this purpose, kinetic models consisting of differential equations based on the Michaelis-Menten dynamics have been used in the past. However, these methods can rarely produce good fits to measured data time series. Possibly, this happens because the kinetic constants are unknown or are different from the ones measured in vivo, or perhaps because Michaelis-Menten dynamics is not a satisfactory description. In order to improve the predictive nature of these kinetic models we have eliminated the Michaelis-Menten description of pathway dynamics and we have substituted it by algorithms that automatically learn these dynamics from previously obtained metabolomics and proteomics data using machine learning approaches. Specifically, kinetic deep learning uses deep learning to map proteomics time series to metabolite concentration time series, instead of learning the first metabolite derivative and integrating in (as in the first version of kinetic learning). This approach is shown to provide good to excellent results with a data set specifically collected for this purpose.

Garcia Martin, Hector [Joint BioEnergy Institute (↗

Experimental and Numerical Characterization of High Temperature Deformation Behavior of 347H Stainless Steel

This study investigates how temperature affects the plasticity and thermal creep behavior of 347H stainless steel under uniaxial tension. The research combined experimental testing with advanced computational modeling. Two types of experiments were conducted: uniaxial tensile tests at temperatures from 100°C to 750°C using strain rates of ~10⁻⁴ s⁻¹, and creep tests at temperatures between 600°C and 750°C under various stress levels. These experimental results were used to develop and validate a new integrated mechanistic model that can predict material behavior under any loading condition while accounting for both stress and temperature effects. The model was implemented using a polycrystalline microstructure simulation framework based on elasto-viscoplastic Fast Fourier Transform (EVPFFT). It incorporates three key deformation mechanisms: thermally activated dislocation glide, dislocation climb, and vacancy diffusional creep. The model accounts for internal stress distribution within single crystals and considers how precipitates and solute atoms (both interstitial and substitutional) affect dislocation movement. After validation against experimental data, the model was used to generate Ashby-Weertman deformation mechanism maps for 347H steel, providing new insights into how microstructure influences the activation of different creep mechanisms.

Joy, Jobin K.↗

4D Characterization of Metals by 3DXRD

The status of 3DXRD microscopy is reviewed, with a special view to applications in metallurgy. Various approaches are compared in terms of performance. In addition several recent advances are presented, such as a 3D grain map with an unprecedented spatial resolution of 500 nm, first results from the commissioning of a novel 3D detector set-up and a validation of the box-scan procedure. Three-Dimensional X-Ray Diffraction (3DXRD) is a novel technique, aiming at a fast and nondestructive characterization of the individual crystalline elements within mm-sized polycrystalline specimens. It is based on two principles: the use of highly penetrating hard X-rays from a synchrotron source (x-ray energies in the range 20-100 keV) and the application of 'tomographic' reconstruction algorithms for the analysis of the diffraction data. In favourable cases, the position, morphology, phase, and crystallographic orientation can be derived for hundreds of elements simultaneously as well as their elastic strains. Furthermore, the dynamics of the individual elements can be monitored during typical processes such as deformation or annealing. Hence, for the first time information on the interaction between elements can be obtained directly. The provision of such data is vital in order to extend beyond state-of-art structural models.

36 MATERIALS SCIENCE↗

Role of Fluorine in Chemomechanics of Cation-Disordered Rocksalt Cathodes

The role of nanoscale chemomechanical behavior in the macroscopic performance of functional materials is well recognized. For lithium-ion battery cathodes, tremendous effort has been devoted to the development of new chemistry and structure, yet fundamental understanding of the correlation between redox processes and mechanical properties of the novel materials lags behind. In the present study, we prepare large discrete single grains of Li-excess cation-disordered rocksalts (DRX) and investigate their chemomechanical behavior at the particle level, using nanoresolution X-ray and electron-based spectro-imaging and chemical mapping techniques. While irregular cracking upon lithium extraction leads to the eventual breakdown of the baseline DRX oxide (Li 1.2 Ti 0.4 Mn 0.4 O 2 ) particles at a high delithiation state, the fluorinated-DRX (Li 1.3 Ti 0.3 Mn 0.4 O 1.7 F 0.3 ) clearly displays aligned cracking along the <001> direction. The resulting periodicity in the cracking pattern enables the particles to retain their integrity and, consequently, improved electrochemical stability. Density functional theory (DFT) calculations showed that fluorination leads to increased concentration of Li+ on the (001) planes and preferential Li movements along the <001>-family directions, revealing the underlying mechanism for directional cracking. Overall, our study demonstrates the unique role of fluorine in modulating nanoscale chemomechanics, which in turn influences the evolution of charge and strain heterogeneity at the particle level. These insights provide important design guidelines in further improving DRX cathode materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗