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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Analysis of autogenous shrinkage-induced microcracks in concrete from 3D images

A new image analysis procedure for quantifying microcracks from three-dimensional (3D) X-ray microCT images of concrete is presented. The method separates microcracks from air voids and aggregates by combining filtering and morphological operations. It was applied to study the effects of supplementary cementitious materials (SCMs) and curing age on autogenous shrinkage-induced microcracks in low w/b ratio concretes, and to determine the representative elementary volume (REV) for various properties of microcracks and air voids. Results showed that slag and silica fume significantly increased autogenous shrinkage and related microcracking. These SCMs increased volume fraction, width, length, dendritic density, anisotropy, and connectivity of microcracks, but decreased specific surface and tortuosity. Similar trends were observed with age. Comparison between 3D and 2D measurements was made. REV analysis showed that a sampling volume of ~20 × 20 × 25 mm{sup 3} is sufficient for characterising most parameters of autogenous shrinkage microcracks and air voids in concrete.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Joint inversion of electromagnetic measurements for the determination of water saturation profiles in concrete structures

Highlights: • DC-electrical and dielectric data are combined to estimate concrete saturation degree. • A joint inversion approach of the electromagnetic measurements is proposed. • The sensitivity of the measurements to the saturation model parameters is analysed. • The new joint approach was developed and is applied to synthetic and real data. • The benefits of the joint approach over the inversion of one data type are highlighted. Water saturation profiles in concrete are essential to assess its durability and can be determined using non-destructive techniques, especially the electric and the capacitive methods. In this paper, we propose a new inversion scheme where both resistivity and permittivity measurements are inverted jointly to retrieve the saturation profile. The finite element method is used to model the measurements in 3D, the concrete having a saturation profile with depth, represented by a continuous model taking the form of a Weibull curve with four parameters. A non-linear least-squares optimization based on the Levenberg-Marquardt scheme is developed for the inversion of measurements. Results show that information gathered from both measurements enriches the reconstructed profile, leading to a more reliable estimation of saturation profiles. We believe that the joint inversion method herein developed could lead to the study of more complex phenomena, such as the coupled water-chloride ingress.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Reconstruction of concrete microstructure using complementarity of X-ray and neutron tomography

The concrete microstructure was successfully reconstructed using the complementarity of X-ray and neutron computed tomography (CT). Neither tomogram alone was found to be suitable to properly describe the microstructure of concrete under this study. However, by merging the information revealed by the two modalities, and using image segmentation, noise reduction, and image registration techniques we reconstruct the concrete microstructure. Void, aggregate, and cement paste phases are successfully captured down to the images' spatial resolution, even though the aggregate consists of multiple minerals. The coarse-aggregate volume fraction of the reconstructed microstructure was similar to that of the mixing proportions. Furthermore, image-based finite element analysis is performed to demonstrate the effects of microstructure on stress concentration and strain localization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fracturing process of micro-concrete under uniaxial and triaxial compression: Insights from in-situ X-ray mechanical tests

This paper presents an experimental study of concrete at meso-scale (aggregates, macro-pores and mortar matrix) in order to get a better understanding of the local failure mechanisms known to drive the macroscopic mechanical behaviour of the material. The main originality comes from conducting in-situ X-ray mechanical tests on micro-concrete samples of realistic composition (including cement, sand, aggregates and water), under uniaxial compression and, for the first time, under triaxial compression at 5 MPa, 10 MPa and 15 MPa confining pressures. A timeseries analysis of the set of 3D images coming from each test allows for the measurement of the 3D kinematic fields (displacement and strain fields) throughout the experiments. The different failure patterns observed for each loading path are discussed, along with a quantification of the 3D fracturing processes at the scale of the largest heterogeneities (aggregates and macro-pores). With an increasing level of confinement, the transition from brittle to ductile response is observed, as well as an increase of the strength of the material. The pronounced impact of the meso-scale heterogeneities of concrete on their local failure mechanisms is highlighted. It is shown that strain localisation mainly originates between aggregates and mortar matrix, with the shape and location of the largest aggregates and macro-pores essentially driving the propagation of the cracking network.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Estimation of constituent properties of concrete materials with an artificial neural network based method

Multi-scale models are developed for heterogeneous concrete materials to estimate their macroscopic mechanical properties in terms of micro-structural data. One crucial challenge of those models is the identification of local properties of constituent phases. In this paper, we present an efficient method based on Artificial Neural Networks (ANN). Typical concrete materials are taken as example. A macroscopic analytical strength criterion is established from three steps of nonlinear homogenization procedure. The macroscopic strength of materials is determined as a function of the frictional coefficient and cohesion of solid cement particles at nanometer scale, intra-particle pores, inter-particle pores and aggregates (inclusions). The objective is to identify the nanoscopic frictional coefficient and cohesion of cement particle from measured macroscopic values of uniaxial compression and tensile strengths. For this purpose, a numerical method based on the ANN is developed. With the analytical macroscopic strength criterion, sensitivity studies are first realized to identify the most important micro-structural parameters influencing the macroscopic strength of concrete. A simplified analytical macroscopic strength criterion is then proposed. A large dataset is further constructed through the inversion of the analytical strength criterion by using the aggregates volume fraction, porosity, macroscopic uniaxial tensile and compressive strengths as input variables and the frictional coefficient and cohesion of cement particles as output unknowns. An ANN model containing four hidden layers and 100 neurons in each layer is constructed and trained by using this dataset. Various types of validation of the ANN model are performed. It is found that the proposed ANN based model can effectively predict the frictional coefficient and cohesion of porous cement paste at the microscopic scale with a very good accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Design and experimental testing of a 150 kWh thermal battery using thermosiphons embedded in a concrete matrix for power plant flexible operation

One of the options for achieving the global temperature limitation of 1.5 °C target, for the mitigation of global warming, is based on the better penetration of renewables into the electrical grid. This has imposed a burden to fossil fuel fired power plants since they are required to operate away from their baseload mode to compensate for the inherent intermittence of the renewable power. Integrating energy storage with fossil plants is an option to achieve their needed flexibility. A cost competitive energy storage option for the solution is based on storing sensible heat in concrete. Here, this paper reports research results and development of a thermal battery cell (TBC) capable of operating at temperatures up to 425 °C. A novel concept consisting of a concrete matrix for sensible heat storage, engineered to provide enhanced thermal and mechanical properties, and twenty-two thermosiphon elements, engineered for dual action were designed and fabricated into a single thermal energy storage (TES) module. Research for the development of the components for the TBC was performed in the laboratory. Efficient heat transfer, to/from the storage media, was demonstrated under several charging and discharging conditions with a thermal storage capacity of 150 kWh th and a rapid discharge, making the TBC suitable for fast ramping when integrated with a fossil fuel fired power plant. Efficient radial heat transfer to the concrete was observed due to the well designed spacing and location of thermosiphons in the radial direction. A minimal temperature difference of 2 °C, between the thermosiphons bottom and top was obtained, demonstrating the isothermicity of those elements. An overall end-to-end TBC energy-to-energy round trip efficiency of 70% was achieved.

25 ENERGY STORAGE↗
DOE OSTI2021

Influence of alkali-silica reaction on the shear capacity of reinforced concrete beams with minimum transverse reinforcement

A growing number of critical concrete infrastructure are affected by alkali-silica reaction (ASR) damage such as the Seabrook Nuclear Power Plant in New Hampshire, Parker arch-gravity dam in Arizona, and several highway bridges in California and Texas. ASR causes expansion and cracking and degrades the concrete mechanical properties. Despite a wealth of material level studies there is still limited large-scale experimental data regarding the effects of ASR on reinforced concrete (RC) members. Due to the brittle nature of the shear failure in RC structures, this study focuses on the shear response of full-scale ASR damaged RC beams with minimum shear reinforcement. Six RC beams were built with different levels of ASR susceptibility and conditioned in different environments during which continuous expansion monitoring was performed. The beams all contained reactive fine aggregate (sand) and two of them had additional alkali, 1.25% by weight of cement, to accelerate ASR. The highest expansion rate of the beams happened during the first 150 days and the expansions stayed constant after 240 days and 330 days for beams conditioned in outdoor and laboratory conditions, respectively, until the last measurement at 575 days. The highest expansion, 0.4%, was seen in the beams with additional alkali and conditioned outside with regular water spray. Out of the six beams, three were selected at different levels of ASR damage and two shear tests were performed on the minimally reinforced spans close to the ends of each beam. Results indicated that beams gain shear strength from ongoing cement hydration in the presence of moisture for ASR expansions less than 0.2%. Compared to one of the beams with 0.2% ASR expansion, one of the other samples with 0.4% expansion lost 6% of its shear strength, 25% of its shear stiffness, and showed about two times larger shear cracks and shear deformations at peak load. Finally, the shear reinforcement yielded at 20% less load in the beam with 0.4% expansion compared to the beam with 0.2% expansion.

42 ENGINEERING↗
DOE OSTI2021

Experimental Investigation of Concrete Fatigue in Axial Compression

The use of concrete in fatigue critical structures, such as wind turbine towers, has necessitated the replacement of simplistic (and therefore insufficient) fatigue design recommendations with more accurate and advanced fatigue models that can consider a greater complexity of stress states and materials. As the first part of a multistage test series, an experimental investigation was conducted to determine the fatigue life of concrete subjected to axial compressive fatigue loading, focusing on the relatively high-cycle fatigue domain. Here, a wide range of values for maximum stress levels and stress ratios were considered. The experimental results were compared against existing predictive models, and the most applicable model was identified. Concrete strain and stiffness behavior during fatigue loading were also investigated and reported. Based on the observed behavior, a hypothesis for identifying the impending occurrence of fatigue failure, based on the monotonic stress-strain curve, is examined.

17 WIND ENERGY↗
DOE OSTI2022

Development of an Extremely Durable Concrete (EDC) - A Novel approach coupling Chemistry and Autogenous Crack Width Control (Final Report)

Concrete cracking is a challenging issue and a constant threat to the durability of modern physical infrastructure. It is most commonly produced by mechanical loading and environmental deformations endured under field conditions, and structural deterioration accelerates at large crack widths. There is an urgent need for dramatic reductions in O&M cost, energy use, and emissions for infrastructure. The goal of this project is to fundamentally design an Extremely Durable Concrete (EDC) with a life expectancy at least five times that of current concrete by deploying a coupled micromechanical and chemical approach in material design. EDC is expected to embody an autogenously tight crack width (<50μm), high ductility (>3%), and stable chemistry using a green binder based on Limestone Calcined Clay Cement (LC3), which together will produce a resilient formulation with self-healing capability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Effect of Fatigue on the Capacity and Performance of Structural Concrete

The goal of this project was to enhance the understanding of the fatigue behavior of concrete structures for the purpose of improving the design and assessment of towers and foundations that support wind turbines, which must endure repeated loadings from wind, waves, operations, and other dynamic effects that cause material degradation. This was achieved through physical experiments, a review of the technical literature, and collaboration with experts in key subject areas. The project produced a comprehensive database of publicly available fatigue data, several technical papers presenting the research findings, and two Technotes to be published by the American Concrete Institute that advance best practices in fatigue testing and enable the development of concrete-specific fatigue (S-N) (stress-life) curves. These contributions are expected to enhance the durability and cost-effectiveness of wind turbine support structures.

17 WIND ENERGY↗
DOE OSTI2024

Improving the Concrete Crack Detection Process via a Hybrid Visual Transformer Algorithm

Inspections of concrete bridges across the United States represent a significant commitment of resources, given their biannual mandate for many structures. With a notable number of aging bridges, there is an imperative need to enhance the efficiency of these inspections. This study harnessed the power of computer vision to streamline the inspection process. Our experiment examined the efficacy of a state-of-the-art Visual Transformer (ViT) model combined with distinct image enhancement detector algorithms. We benchmarked against a deep learning Convolutional Neural Network (CNN) model. These models were applied to over 20,000 high-quality images from the Concrete Images for Classification dataset. Traditional crack detection methods often fall short due to their heavy reliance on time and resources. This research pioneers bridge inspection by integrating ViT with diverse image enhancement detectors, significantly improving concrete crack detection accuracy. Notably, a custom-built CNN achieves over 99% accuracy with substantially lower training time than ViT, making it an efficient solution for enhancing safety and resource conservation in infrastructure management. These advancements enhance safety by enabling reliable detection and timely maintenance, but they also align with Industry 4.0 objectives, automating manual inspections, reducing costs, and advancing technological integration in public infrastructure management.

42 ENGINEERING↗
DOE OSTI2022

Biochar as a Building Material: Sequestering Carbon and Strengthening Concrete

It is possible to offset the carbon footprint of concrete by 60 kg (132 lbs) per cubic yard of ready-mix by deeply sequestering carbon with an engineered biochar additive. Our multidisciplinary team specializing in char production and cementitious materials has demonstrated that for every ton of cement, adding 100 kg of engineered biochar will not only lock in carbon, but also strengthen concrete in all key dimensions via enhancements to hydration and integration into the hardened matrix. As a non-chemical, inert additive the cement sequestration (CemSeq) char product can fully complement other powerful tools to reduce cement emissions and unlock the possibility for carbon negative concrete by 2050. The key findings of our initial research have shown that to achieve this the following are required: tailored milling of the char, using fast pyrolysis to produce the char, and modulating the cement flowability.

biochar↗
DOE OSTI2020

GPR Robotic Assisted Non-Destructive Evaluation of Concrete Structures - 20196

Reinforced concrete structures are always under exposure of internal or external deteriorations due to many factors such as environmental, nuclear radiation or even construction deficiencies. The use of nondestructive test is one of the reliable methods to inspect structural members. In this case, GPR has a good capability to detect inside deteriorations of concrete structures. However, in many cases it is hard to inspect structural members by hand due to safety issues or inaccessibility. Thus, an alternative way to reduce such risks is to employ robot to carry nondestructive equipment. In this research, twelve reinforced concrete RC beams (8 x 16 x 96, width, height and length) are cast in the lab. Three RC beams have no defect and nine others various defects such as corrosion, de-bonded bars, void, delamination and honeycombing. The one-point load is applied at the center of the RC beam. The loading level is carried out at three levels: 50%, 75% and 100% of maximum load and total load-displacement diagram are performed. The load is held at each level and the robotic GPR is used to scan the side of RC beams. Then, RADAN software is employed to find out any defects at different loading conditions and visualize the crack propagation. The RADAN results show that the pattern of crack propagation for corrosion and debonding are same. Also, the load-displacement results present that inside defect cause reduction of load-capacity of RC beam. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Microstructural characterization and assessment of mechanical properties of concrete based on combined elemental analysis techniques and Fast-Fourier transform-based simulations

This paper presents a pixel-based modeling approach of concrete which combines an experimental characterization of concrete and the Fast-Fourier transform simulations. High-resolution phase maps created from experimental characterization by micro X-ray fluorescence, energy dispersive X-ray analysis, and X-ray diffraction contain 9 different phases, including 22.17 vol.% of hydrated cement paste, 54.21 vol.% of minerals, and 23.62 vol.% of interfaces. These phases provide the input for determining the effective elastic properties, coupled with Fast-Fourier transform-based simulation. The simulation results show that the effective range of Young’s modulus of concrete is comparable with the range of experimental values ~ 37 ± 4 GPa with the assumption of realistic properties of interfaces.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Graphene Oxide Nanoribbons for High Early-Strength Cement Concrete

Longitudinal oxidative unzipping of the outer walls of multiwalled carbon nanotubes (MWCNTs) yields graphene oxide nanoribbons (GONRs), which exhibit greater open surface area and functional edge content than MWCNTs. This paper presents a study of the nano-amendment of Portland cement concrete with GONRs in concentrations between 0.05% (in weight of cement, wt%) and 0.0005 wt%, thus up to two orders of magnitude lower than that reported as lower-bound in the archival literature. The dispersibility in aqueous solution as a function of GONR concentration and oxygen weight content (O%) was assessed through dynamic light scattering (DLS) and zeta potential analysis. The results indicated that less effective suspensions were obtained for 0.05 wt% of GONRs and 22.7 O%. Therefore, GONR water suspensions with 30-40% O% were used to manufacture 50 mm × 100 mm cylindrical concrete specimens. After 7 days of curing, results from uniaxial compression tests using four specimens per configuration (MWCNT concentration and O%) showed that the incorporation of GONRs resulted in an average increase in compressive strength up to 45%. Consistent with the DLS and compression test results, SEM micrographs showed well-dispersed GONRs together with accelerated and preferential formation of calcium silicate hydrates (C-S-H) for all GONR concentrations. The results indicate, for the first time, that the incorporation of very small concentrations (as low as 0.0005 wt%) of well-dispersed GONR amendments can significantly enhance the early-age concrete strength. However, such enhancement became insignificant after 28 days of curing.

cement↗
DOE OSTI2022

Developing a heterogeneous ensemble learning framework to evaluate Alkali-silica reaction damage in concrete using acoustic emission signals

The monitoring and evaluation of Alkali-silica reaction (ASR) damage in concrete structures are required to ensure the serviceability and integrity of concrete infrastructures such as bridges and dams. The innovation of this paper lies in the development of an automatic ASR monitoring and evaluation approach by leveraging acoustic emission (AE) and a heterogeneous ensemble learning framework. Here, in this paper, ASR was monitored by AE sensors attached to a concrete specimen, which was placed in a chamber with high humidity and temperature. The recorded AE signals were filtered and divided by four ASR phases according to signal strength, crack width and expansion strain. A heterogeneous ensemble network including convolutional neural networks (CNN) and random forest models was employed to learn different features from AE signals and classify the AE signals into their corresponding phases. The results suggest that the proposed model has a high performance and classifies the signals into the assigned phases with high accuracy.

42 ENGINEERING↗
DOE OSTI2020

Vibro-acoustic modulation and data fusion for localizing alkali–silica reaction–induced damage in concrete

This article investigates the application of vibro-acoustic modulation testing for diagnosing damage in concrete structures. The vibro-acoustic modulation technique employs two excitation frequencies on a structure. The interaction of these excitations in the measured response indicates damage through the presence of sidebands in the frequency spectra. Past studies using this technique have mostly focused on metals and composites (thin plates or laminates). Our research focuses on concrete, which is a highly heterogeneous material susceptible to a variety of chemical, physical, and mechanical damage processes. In particular, this article investigates diagnosing cracking in concrete from an expansive gel produced by an alkali–silica reaction in the presence of moisture. Past studies have been limited to damage detection using vibro-acoustic modulation testing, whereas this article extends the technique to damage localization. A cement slab with pockets of reactive aggregate is used to investigate the diagnosis technique. The effects of different testing parameters, such as locations, magnitudes, and frequencies of the two excitations, are analyzed and incorporated in the damage localization methodology. A Bayesian probabilistic methodology is developed to fuse the information from multiple test configurations in order to construct damage probability maps for the test specimen. The results of vibro-acoustic modulation–based damage localization are validated by petrographic study of cores taken from the slab.

Karve, Pranav↗
DOE OSTI2025

PyCMG-based Simulation of Volumetric Concrete Microstructure

Concrete is a complex, heterogeneous material with a microstructure composed of aggregates, cement paste, and pores spanning multiple length scales. Understanding this microstructure is critical for advancing the performance, durability, and modeling of concrete-based systems. While experimental imaging such as X-ray computed tomography (XCT) provides valuable insights, generating large datasets with detailed ground truth annotations is both costly and labor-intensive due to challenges in segmenting similar phases, such as aggregates and cement paste, that often share similar attenuation properties. To address this, we developed a pipeline to simulate realistic 3D concrete microstructures using the open-source Python package PyCMG. This simulation effort focuses on generating high-fidelity, annotated microstructures that can serve as training or benchmarking datasets for image analysis, segmentation algorithms, and machine learning models, particularly in scenarios where experimental data is scarce.

Ziabari, Amir [Oak Ridge National Laboratory; ORNL↗