Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “computational structural mechanics”

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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Convergence of micro-geochemistry and micro-geomechanics towards understanding proppant shale rock interaction: A Caney shale case study in southern Oklahoma, USA

As a direct outcome of economic development coupled with an increase in population, global energy demand will continue to rise in the coming decades. Although renewable energy sources are increasingly investigated for optimal production, the immediate needs require focus on energy sources that are currently available and reliable, with a minimal environmental impact; the efficient exploration and production of unconventional hydrocarbon resources is bridging the energy needs and energy aspirations, during the current energy transition period. The main challenges are related to the accurate quantification of the critical rock properties that influence production, their heterogeneity and the multiscale driven physico-chemical nature of rock–fluid interactions. A key feature of shale reservoirs is their low permeability due to dominating nanoporosity of the clay-rich matrix. As a means of producing these reservoirs in a cost-effective manner, a prerequisite is creation of hydraulic fracture networks capable of the highest level of continued conductivity. Fracturing fluid chemical design, formation brine geochemical composition, and rock mineralogy all contribute to swelling-induced conductivity damage. The Caney Shale is an organic-rich, often calcareous mudrock. Many studies have examined the impact that clay has on different kinds of shale productivity but there is currently no data reported on the Caney Shale in relation to horizontal drilling; all reported data on the Caney Shale is on vertical wells which are shallow, compared to an emerging play that is at double the depth. Here, in this work we develop geochemical–geomechanical integration of rock properties at micro-and nanoscales that can provide insights into the potential proppant embedment and its mitigation. The novel methodology amalgamates the following: computed X-ray tomography, scanning electron microscopy, energy dispersive spectroscopy, micro-indentation, and Raman spectroscopy techniques. Here, our results show that due to the multiscale heterogeneity in the Caney Shale, these geochemical and structural properties translate into a variation in mechanical properties that will impact interaction between the proppant and the host shale rock.

03 NATURAL GAS↗
DOE OSTI2023

High-Strength, High-Ductility, High Entropy Alloys with High-Efficiency Native Oxide Solar Absorbers for Concentrating Solar Power Systems

This EPSCoR Project has been investigating the synergy between the excellent high-temperature mechanical behavior of FeMnNiAlCr high entropy alloys (HEA) and the high solar absorptance of their native oxides for high efficiency concentrated solar thermal power (CSP) systems working at >700°C. While HEAs have attracted substantial interest in recent years, most investigations have focused on their applications as structural materials rather than functional materials. This EPSCoR project discovered that FeMnNiAlCr HEAs can potentially be applied synergistically as both a structural and functional material for high-efficiency concentrating solar thermal power (CSP) systems working at >700°C. The HEA itself would be used in high-temperature tubing to carry molten salts or supercritical CO 2 , while its surface oxide would act as a high-efficiency solar thermal absorber. With Fe and Mn being the major components in these HEAs (adding up to ~70 at.% of the alloy), these materials are much more cost-effective than the Ni-based superalloys currently being investigated for high-temperature CSP systems. Through this research, these Fe-Mn based HEAs have demonstrated yield strengths 2-3x greater than that of stainless steel at 700°C and a creep lifetime >800 h at 700ºC under a typical CSP tubing mechanical load of 35 MPa. Their Mn-rich surface oxides maintain a high optical-to-thermal conversion efficiency of ~87% under 1000x solar concentration ratio for 20 simulated day-night thermal cycles between 750ºC and room temperature. In preliminary corrosion studies, these HEAs have sustained immersion in unpurified bromide molten salts for 14 days at 750°C with <2% weight loss, in contrast to 70% weight loss from a 316 stainless steel reference. The simultaneous achievement of promising mechanical, optical, and thermochemical properties in this FeMnNiAlCr system opens the door to new applications of HEAs in solar energy harvesting. Partnerships with Ames Laboratory and Oak Ridge National Laboratory (ORNL) also advanced our understanding of the fundamental structure-property relationships through atomic scale material characterization and first-principles computational modeling. The key research results in this project can potentially be extended to other HEAs and their native oxides. In terms of applications, the proposed FeMnNiAlCr HEA/native oxide system could potentially exceed the mechanical and the optical performance of existing tubing and solar coating materials under EERE’s CSP program at lower cost, which also aligns well with the EPSCoR Science and Technology strategies of New Hampshire in boosting the deployment of renewable energy.

14 SOLAR ENERGY↗
DOE OSTI2025

Coefficient-to-Basis Network: a fine-tunable operator learning framework for inverse problems with adaptive discretizations and theoretical guarantees

We propose a Coefficient-to-Basis Network (C2BNet), a novel framework for solving inverse problems within the operator learning paradigm. C2BNet efficiently adapts to different discretizations through fine-tuning, using a pre-trained model to significantly reduce computational cost while maintaining high accuracy. Unlike traditional approaches that require retraining from scratch for new discretizations, our method enables seamless adaptation without sacrificing predictive performance. Furthermore, we establish theoretical approximation and generalization error bounds for C2BNet by exploiting low-dimensional structures in the underlying datasets. Our analysis demonstrates that C2BNet adapts to low-dimensional structures without relying on explicit encoding mechanisms, highlighting its robustness and efficiency. To validate our theoretical findings, we conducted extensive numerical experiments that showcase the superior performance of C2BNet on several inverse problems. The results confirm that C2BNet effectively balances computational efficiency and accuracy, making it a promising tool to solve inverse problems in scientific computing and engineering applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Discovery of multimechanisms of screw dislocation interaction in bcc iron from open-ended saddle point searches

Dislocation motion and interactions determine mechanical properties in body-centered cubic (bcc) metallic materials. However, studying mechanisms for the screw dislocation interaction is fundamentally challenging since many underlying processes involve mesotimescales and atomistic resolution, currently inaccessible by either experimental techniques or continuum theoretical methods. Here, in this paper, we develop a computational capability based on self-evolving atomistic kinetic Monte Carlo (SEAKMC) to sample the critical events and saddle point energies related to screw dislocations and their junctions. The method is first validated by calculating the stress dependence of Peierls barriers and formation energies of kink pairs and cross-slip kink pairs on a single screw dislocation in bcc iron. Then the method is applied to a binary junction of a pair of intersecting screw dislocations, the structure of which is crucial for low-temperature plastic deformation. We identify three important mechanisms: coplanar cross-slipping, jog-pinning, and a previously unknown unzipping mechanism during the evolution of the binary junction. The mechanisms are then further validated using classical molecular dynamics simulations. The computational capability developed in this paper provides an effective tool to evaluate screw dislocation related thermally activated events in complex stress conditions. The mechanisms discovered in this paper provide critical insights into temperature dependence of the anomalous slip, a breakdown of the Schmidt law, during the plastic deformation in bcc iron and can be generalized to other bcc metals.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Atomic-Scale Computational and Experimental Investigation of Twinning Mechanisms in HCP Systems

One of the major goals of the Materials Science and Engineering community is to achieve a fundamental understanding of how alloying affects the mechanical properties of structural materials. Titanium (Ti) and its alloys are particularly in demand due to their relatively lightweight, high strength and corrosion resistance. The low-temperature ductility of hexagonal close-packed (hcp) Ti known as α- Ti is linked to twinning. The addition of alloying elements can affect the deformation mechanisms leading to the change in macro-scale mechanical properties. To understand these effects, our objective is to study and quantify the energetics and kinetics of substitutional and interstitial solutes on the deformation mechanisms of hcp alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

CASM — A software package for first-principles based study of multicomponent crystalline solids

CASM is a software package that enables first-principles based studies of crystalline materials. It has been designed to treat coupled chemical, mechanical, vibrational, and magnetic degrees of freedom to determine ground state and finite temperature properties of crystals. The symmetry of the underlying parent crystal structure is used to enumerate perturbations of the parent crystal structure and generate derivative structures which can be input to first-principles calculations in order to explore the ground state energy landscape. CASM algorithmically constructs cluster expansions that fully couple discrete and continuous degrees of freedom, and generates highly efficient code to evaluate the cluster expansion basis functions. Widely used machine learning methods are integrated for fitting expansion coefficients to first-principle calculations. The fully parameterized cluster expansions can be combined with (kinetic) Monte Carlo methods to calculate finite temperature thermodynamic and kinetic properties. CASM Alloy Manager identifies distinct parent crystal structures in an alloy system, creating individual projects for each, and integrating the results. The integrated infrastructure facilitates the linkage between first-principles statistical mechanics predictions with higher length scale computational methods, such as phase field simulations. In conclusion, CASM projects are designed to be easy to share in repositories, to re-use, and to extend to include additional chemical species or types of degrees of freedom.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Experimental observation of open structures in elemental magnesium at terapascal pressures

Investigating how solid matter behaves at enormous pressures, such as those found in the deep interiors of giant planets, is a great experimental challenge. Over the past decade, computational predictions have revealed that compression to terapascal pressures may bring about counter-intuitive changes in the structure and bonding of solids as quantum mechanical forces grow in influence. Although this behavior has been observed at modest pressures in the highly compressible light alkali metals, it has not been established whether it is commonplace among high-pressure solids more broadly. We used shaped laser pulses at the National Ignition Facility to compress elemental Mg up to 1.3 TPa, which is approximately four times the pressure at the Earth’s core. By directly probing the crystal structure using nanosecond-duration X-ray diffraction, we found that Mg changes its crystal structure several times with non-close-packed phases emerging at the highest pressures. Our results demonstrate that phase transformations of extremely condensed matter, previously only accessible through theoretical calculations, can now be experimentally explored.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Hydrogen ejection from hydrocarbons: Characterization and relevance in soot formation and interstellar chemistry

Polycyclic aromatic hydrocarbons (PAHs) play a major role in the chemistry of combustion, pyrolysis, and the interstellar medium. Production (or activation) of radical PAHs and propagation of their resulting reactions require efficient dehydrogenation, but the preferred method of hydrogen loss is not well understood. Unimolecular hydrogen ejection (i.e., direct C─H bond fission) and bimolecular radical abstraction are two main candidate pathways. We performed a computational study to characterize the role of H ejection, particularly as a driver for radical-centric hydrocarbon-growth mechanisms and particle formation. Electronic structure calculations establish that C─H bond strengths span a broad range of energies, which can be weaker than 30 kcal/mol in some C 9 and C 13 PAH radicals. At T > 1200 K, calculated thermal rates for hydrogen ejection from weak C─H bonds at zigzag sites on PAH radicals are significantly larger than typical H-abstraction rates. These results are highly relevant in the context of chain reactions of radical species and soot inception under fuel-rich combustion conditions. Furthermore, calculated microcanonical rates that include the additional internal energy released by bond formation (e.g., ring closure to yield C 9 H 9 ) yield significantly higher rates than those associated with full thermalization. These microcanonical considerations are relevant to the astrochemical processes associated with hydrocarbon growth and processing in the low-density interstellar environment.

08 HYDROGEN↗
DOE OSTI2023

High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones.

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

Development and Validation of a Simulation Tool to Predict the Combined Structural, Electrical, Electrochemical and Thermal Responses of Automotive Batteries

Battery safety is one of the most important design factors of electrified vehicles (EVs) since battery failure may lead to a catastrophic consequence. To improve the safety of battery systems in EVs, battery behaviors under various abuse conditions should be well understood. One way to examine battery response under extreme conditions is to conduct abuse tests in different scenarios. They can provide first-hand pass/fail information on battery safety, but they are usually expensive and time-consuming, which is inconvenient during design iterations and optimization. On the other hand, computational modeling can predict the battery behaviors in a more efficient and cost-effective way, which becomes an important tool to evaluate battery safety. Modeling battery responses and failure is challenging since it involves multiple coupled physical processes, needs to consider complex material properties and is computationally intensive. This project aims to develop a practical simulation tool to predict the combined structural, electrical, electrochemical, and thermal responses of automotive batteries to crash-induced crush and short circuit and validate it for conditions relevant to automotive crash. Advanced material constitutive models will be utilized to capture the mechanical response of cell components. Moreover, methods will be developed to reduce computational complexity of the model and allow battery safety simulations to extend from cell-level to module/pack level with affordable computational resources.

25 ENERGY STORAGE↗
DOE OSTI2020

Structural insights into the mechanism of oxidative activation of heme-free H-NOX from Vibrio cholerae

Bacterial heme nitric oxide/oxygen (H-NOX) domains are nitric oxide (NO) or oxygen sensors. This activity is mediated through binding of the ligand to a heme cofactor. However, H-NOX from Vibrio cholerae (Vc H-NOX) can be easily purified in a heme-free state that is capable of reversibly responding to oxidation, suggesting a heme-independent function as a redox sensor. This occurs by oxidation of Cys residues at a zinc-binding site conserved in a subset of H-NOX homologs. Remarkably, zinc is not lost from the protein upon oxidation, although its ligation environment is significantly altered. Using a combination of computational and experimental approaches, we have characterized localized structural changes that accompany the formation of specific disulfide bonds between Cys residues upon oxidation. Furthermore, the larger-scale structural changes accompanying oxidation appear to mimic those changes observed upon NO binding to the heme-bound form. Thus, Vc H-NOX and its homologs may act as both redox and NO sensors by completely separate mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Three-dimensional modeling of hyphal fusion, branching, and nutrient transport in filamentous fungi

Fungi exhibit behaviors distinct from other microbes. Filamentous fungi grow by extending complex networks of branched filaments collectively referred to as the mycelium. These networks can expand over large distances and traverse low-nutrient areas by translocating nutrients through the filament network. This spatial characteristic makes filamentous fungi crucial for soil ecosystems, supporting stable microbial communities and promoting plant growth. However, simulating these behaviors is complex. The elongated nature of fungal compartments results in different mechanical interactions compared to the commonly modeled spherical bacteria. These detailed hyphal mechanics require specialized consideration and are often excluded from conventional fungal simulation packages. Additionally, the extensive fungal networks in nature demand computationally intensive simulations, necessitating high-performance algorithms. Therefore, realistic fungi simulations require specialized software. Here, we introduce a fungal modeling expansion to the high-performance biological modelling and interface exchange (bmx) software suite. bmx leverages adaptive mesh refinement in AMReX for chemical diffusion and incorporates a full mechanical model for bacterial cells, accelerated by GPUs. By extending bmx to model filamentous particles, we demonstrate the formation of complex filament networks through interactions like hyphal branching and fusion (anastomosis). We show that the networks produced match real-world fungal structures through various metrics. This work supports computational studies of fungal growth dynamics and can be adapted to investigate the growth of other filamentous structures in biology or materials science. The expanded-BMX package is open-sourced and is available online.

Cell mechanics↗
DOE OSTI2025

Machine Learning‐Augmented Molecular Dynamics Simulations (MD) Reveal Insights Into the Disconnect Between Affinity and Activation of ZTP Riboswitch Ligands

Abstract The challenge of targeting RNA with small molecules necessitates a better understanding of RNA–ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand‐induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure‐informed design, crystallography, and machine learning‐augmented all‐atom molecular dynamics simulations (MD), we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the 5‐aminoimidazole–4–carboxamide ribonucleotide triphosphate (ZTP) riboswitch, a ligand‐binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on‐rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.

Chemistry↗
DOE OSTI2020

Understanding the metal-to-insulator transition in La1−xSrxCoO3−δ and its applications for neuromorphic computing

Abstract Transition metal oxides that exhibit a metal-to-insulator transition (MIT) as a function of oxygen vacancy concentration are promising systems to realize energy-efficient platforms for neuromorphic computing. However, the current lack of understanding of the microscopic mechanism driving the MIT hinders the realization of effective and stable devices. Here we investigate defective cobaltites and we unravel the structural, electronic, and magnetic changes responsible for the MIT when oxygen vacancies are introduced in the material. We show that, contrary to accepted views, cooperative structural distortions instead of local bonding changes are responsible for the MIT, and we describe the subtle interdependence of structural and magnetic transitions. Finally, we present a model, based on first principles, to predict the required electric bias to drive the transition, showing good agreement with available measurements and providing a paradigm to establish design rules for low-energy cost devices.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Detection of Monoclinic Zirconia and Non-Uniform 3D Crystallographic Strain in a Re-Oxidized Ni-YSZ Solid Oxide Fuel Cell Anode

The solid oxide fuel cell (SOFC) anode is often composed of nickel (Ni) and yttria-stabilized zirconia (YSZ). The yttria is added in small quantities (e.g., 8 mol %) to maintain the crystallographic structure throughout the operating temperatures (e.g., room-temperature to >800 °C). The YSZ skeleton provides a constraining structural support that inhibits degradation mechanisms such as Ni agglomeration and thermal expansion miss-match between the anode and electrolyte layers. Within this structure, the Ni is deposited in the oxide form and then reduced during start-up; however, exposure to oxygen (e.g., during gasket failure) readily re-oxidizes the Ni back to NiO, impeding electrochemical performance and introducing complex structural stresses. In this work, we correlate lab-based X-ray computed tomography using zone plate focusing optics, with X-ray synchrotron diffraction computed tomography to explore the crystal structure of a partially re-oxidized Ni/NiO-YSZ electrode. These state-of-the-art techniques expose several novel findings: non-isotropic YSZ lattice distributions; the presence of monoclinic zirconia around the oxidation boundary; and metallic strain complications in the presence of variable yttria content. This work provides evidence that the reduction–oxidation processes may destabilize the YSZ structure, producing monoclinic zirconia and microscopic YSZ strain, which has implications upon the electrode’s mechanical integrity and thus lifetime of the SOFC.

25 ENERGY STORAGE↗
DOE OSTI2021

Location and characterization of heterogeneous phases within Mary Rose wood

Preserving the Mary Rose oak hull for future generations is a major challenge due to the highly heterogeneous nature of waterlogged wooden artifacts, which contain polycrystalline, amorphous, and nanostructured materials that test traditional characterization methods. Effective conservation requires detailed knowledge of the distribution and chemical nature of these species to develop strategies for preventing multiple chemo-mechanical degradation pathways. Here, we apply synchrotron-based computed tomography total scattering methods to the Mary Rose keelson wood that provides valuable position-resolved structural information on multiple embedded species of different length and concentration scales. We identify 5 nm zinc sulfide nanoparticles in the wood, presumably deposits from bacteria operating on the sulfur energy cycle under the anaerobic conditions on the seabed. These are identified as precursors to acid attack on the wood upon removal to an aerobic environment. These insights inform not only next-generation conservation strategies, but also the efficacy and unforeseen issues of previous treatments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Volumetric analysis and mesh generation of real and artificial microstructural geometries

Producing a viable finite element mesh of realistic microstructural structural geometry is a critical step in analyzing the thermo-mechanical behavior of complex multi-material composites. Advancements in imaging technology such as micro computed tomography have allowed modelers to access high resolution mesoscale geometries for direct numerical simulation. However, converting from voxel based 3D images to usable finite element meshes has been challenging. A robust method including algorithms and software scripts for generating finite element meshes from 3D imaged microstructures is presented in this paper. It includes a routine for inserting cohesive elements around material interfaces to enable modeling of interface properties including delamination and damage. The algorithms and procedures presented in this method leverage currently available software packages for processing surface based geometry into volume based meshes. In addition to converting real geometry from physical imaging systems, algorithms for producing numerically generated and statistically equivalent microstructural geometry are also included. These artificial microstructures can be a valuable resource for modelers when physical specimens do not exist or are limited in quantity: Method establishes a workflow from voxel data to viable finite element mesh including interface information, and Includes a method for synthetic geometry generation based on metrics from real microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Conductivity and size quantization effects in semiconductor $$\delta$$-layer systems

Abstract We present an open-system quantum-mechanical 3D real-space study of the conduction band structure and conductive properties of two semiconductor systems, interesting for their beyond-Moore and quantum computing applications: phosphorus $$\delta$$ δ -layers and P $$\delta$$ δ -layer tunnel junctions in silicon. In order to evaluate size quantization effects on the conductivity, we consider two principal cases: nanoscale finite-width structures, used in transistors, and infinitely-wide structures, electrical properties of which are typically known experimentally. For devices widths $$W<10$$ W < 10 nm, quantization effects are strong and it is shown that the number of propagating modes determines not only the conductivity, but the distinctive spatial distribution of the current-carrying electron states. For $$W>10$$ W > 10 nm, the quantization effects practically vanish and the conductivity tends to the infinitely-wide device values. For tunnel junctions, two distinct conductivity regimes are predicted due to the strong conduction band quantization.

36 MATERIALS SCIENCE↗