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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessment of Machine Learning for Ultrasonic Nondestructive Evaluation of Alkali–Silica Reaction in Concrete

Alkali–silica reaction (ASR) is a type of material degradation in concrete structures that leads to concrete cracking and rebar corrosion, thereby reducing the material’s structural integrity and the overall structure’s lifetime and raising safety concerns. Ultrasonic nondestructive evaluation (NDE) has been proven to be a valuable technique for assessing concrete properties and monitoring ASR progression in concrete. However, the deployment and analysis of ultrasonic NDE and its data requires specialized expertise, often relying on the engineer’s subjective interpretation. With the surge in computational power, artificial intelligence (AI) and machine learning (ML) algorithms have become popular in automating NDE data analysis. Various industrial sectors are increasingly adopting ML algorithms for NDE data analysis with a growing emphasis on AI–assisted automation. Regulatory agencies are also preparing for this technological shift, anticipating corresponding revisions in standards. Thus, there is an urgent need to identify the capabilities and limitations of current ML technologies for the evaluation of concrete material properties and damage status. Furthermore, the effects of various factors on ML model performance must be thoroughly investigated. The study summarized herein evaluated the effectiveness of two ML models (i.e., support vector regression (SVR) and deep neural network (DNN)) in predicting concrete material damage induced by ASR based on the long-term ultrasonic monitoring data. Four distinct concrete specimens were cast with artificially induced ASR, and over a period exceeding 500 days, ultrasonic signals and expansion data were continuously collected. For the SVR model, wave velocity and 12 other wave features were extracted from the ultrasonic signals, with 6 out of 13 features selected as input for the model. Different combinations of training and testing datasets were designed to explore factors influencing prediction performance, including the range of data within training and testing sets, in addition to various signal preprocessing methodologies. These findings suggest the importance of using a training dataset with a broader data range compared with testing datasets for improved model performance alongside consistent signal preprocessing across datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Temperature dependence of viscoelastic Poisson’s ratio of cement mortar

Abstract Concrete creep research has focused primarily on uniaxial response. However, biaxially prestressed concrete structures are common, resulting in a multiaxial stress state that can complicate the behavior of a viscoelastic material like concrete. Significant creep strains may be induced in directions transverse to each principle stress due to Poisson’s effect. Past research is unclear regarding the viscoelastic or viscoplastic properties of concrete outside of uniaxial response. It has been reported in separate studies that concrete viscoelastic/viscoplastic Poisson’s ratio (VPR) is an increasing, decreasing and constant function with time, with all reported measurements performed at room temperature. In this paper, the 3D basic creep response of mature cement mortar is examined using a confined compression experiment that allows direct determination of the full stress and infinitesimal strain tensors in a single test, which enables the determination of VPR under a multiaxial stress state. For this purpose, a unique, miniature version of the standardized concrete creep frame is designed that is amenable to placing in climate chambers and temperature ovens. The experimental results indicate that the VPR of sealed, mature cement mortar is nearly constant and equal to the elastic at room temperature, while the VPR gradually increases with time when measured at 60 °C.

Construction & Building Technology↗
DOE OSTI2023

Life cycle cost, energy, and carbon emissions of molds for precast concrete: Exploring the impacts of material choices and additive manufacturing

Molds for precast concrete are commonly used to create simple- to complex-shaped concrete products away from construction sites. These molds are often handmade from wood; however, additively manufacturing (AM, or 3D printing) fiber-reinforced polymer composites is an advantageous alternative, producing significantly more durable, highly complex molds faster, but likely at a higher cost. Here, this study explores the impact of material and production variables on the cost, energy, and carbon emissions of employing composite AM molds over the full lifecycle. The case study employed techno-economic and life cycle assessments to show that using wood flour–poly(lactic acid) or recycled carbon fiber–acrylonitrile butadiene styrene for AM molds can be less expensive than conventional wood molds, especially when considering use phase costs. While wood molds have the least environmental impacts due to wood's higher biogenic carbon sequestration and minimal processing, optimizing AM designs could reduce energy demand, carbon emissions, and cost.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Effect of autogenous shrinkage on microcracking and mass transport properties of concrete containing supplementary cementitious materials

It is well-known that supplementary cementitious materials (SCMs) and low water-to-binder (w/b) ratio increase autogenous shrinkage, but the impact on microcracking and long-term transport properties is less understood. This paper examines the effect of microcracking induced by autogenous shrinkage on transport properties of concretes cured up to ~3.6 years. Variables include SCM type (9% SF, 70% GGBS), w/b ratio (0.20–0.45), maximum-aggregate-size (MSA: 5–20 mm) and shrinkage reducing admixture (SRA). Oxygen diffusivity, permeability and water sorptivity were correlated with microcracks characterised using laser scanning confocal microscopy and 3D X-ray microtomography. Results show greater microcracking in mixes containing SCMs, low w/b ratio and large MSA. At the same w/b ratio and binder type, strong positive correlations are observed between transport and microcracking with increasing MSA, confirming the negative impact of autogenous shrinkage. SRA was effective in reducing these effects. The significance is compared with drying shrinkage and implications for durability are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Review of supplementary cementitious materials with implications for age-dependent concrete properties affecting precast concrete

Here, this paper presents a comprehensive review of existing research examining the effects of supplementary cementitious materials on age-dependent concrete properties with the most profound implications for precast concrete production. The review covers the physical and chemical properties of selected types of supplementary cementitious materials, concrete mixture proportions, concrete curing methods, testing procedures, and test results related to the fresh properties and strengths of a range of concrete mixtures. Although the use of supplementary cementitious materials in precast concrete products is common, the detailed information provided in this paper may facilitate more widespread use of these materials to enhance concrete properties and comply with sustainability initiatives.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

A unified finite strain gradient-enhanced micropolar continuum approach for modeling quasi-brittle failure of cohesive-frictional materials

Here, in this work, a novel framework for modeling quasi-brittle crack propagation and shear band dominated failure of cohesive-frictional materials like concrete, mortar, rock, tough ceramics, energetic materials, but also granular materials like sands or powders in terms of a unified continuum approach is proposed. It is based on a combination of the gradient-enhanced continuum with gradients of internal variables for representing quasi-brittle cracking, and the micropolar continuum, accounting for the deformation of the microstructure. For developing the gradient-enhanced micropolar framework, the set of balance equations and the kinematic relations are derived, and the constitutive relations are established in a general manner. The framework is formulated in a geometrically exact setting, based on the thermodynamically sound theory of hyperelasto-plasticity, and the numerical implementation by means of the finite element method is discussed. For assessing the approach, realizations of this new approach in terms of constitutive models for particular materials are developed. They are applied to numerical benchmark examples, investigating various loading conditions, and the obtained results are validated by means of a comparison with experiments from the literature.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Greenhouse gas emissions of global construction material production

Abstract Global production of building materials is a primary contributor to greenhouse gas (GHG) emissions, but the production of these materials is necessary for modern infrastructure and society. Understanding the GHG emissions from building materials production in the context of their function is critical to decarbonizing this important sector. In this work, we present estimates of global production, approximate ranges of GHG emissions, and ranges of material properties of 12 critical building material classes to provide a unified dataset across material types. This dataset drew from industry analyses of production and emissions, ranges of emission factors within a material type, and broad reporting of thermal and mechanical properties to compare both within and between material types. Globally, in 2019, we estimate 42.8 Gt of these 12 materials were produced, with 38.6 Gt used in the building and construction industry. As a result of this production, 9.3 Gt of CO 2 was emitted, or 25% of global fossil GHG emissions, with 5.8 Gt CO 2 (16% of global GHG emissions) due to materials used in construction applications. Both construction material production and emissions are primarily driven by structural materials, such as concrete and steel. Material selection can play a key role in reducing emissions in the context of the function, with variation in emissions of structural materials per unit strength between 0.001–0.1 kg CO 2 /kg/MPa and in insulation materials per R -value/thickness of 0.018–0.14 kg CO 2 /kg/(K⋅m 2 W −1 ))). The developed dataset can play a key role in supporting decision-making in materials by providing a unified source for examining emissions, material properties, and quantity of material produced.

Kane, Seth (ORCID:0000000269401369)↗
DOE OSTI2020

Determination of Elastic Coefficients for a Composite with Crossing Steel - 20086

For a composite material with an embedding of crossing reinforcement bars, the elastic coefficients are calculated by solving a boundary-value problem (elastostatic problem). The background material is concrete whereas the bars are made of steel. The bars cross each other horizontally at a right angle. The boundary-value problem is solved numerically by using 3-D quadratic basis functions in ABAQUS{sup R}. Under external shear loading conditions, the effective elastic coefficients on the macroscale are quite larger for a cross-section in which the bars are immediately below the ones in the cross-section normal to it. The shear modulus in the off-plane direction is about one and half times larger than that in the in-plane direction. (authors)

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

Development of an MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete

Abstract Although contactless ultrasonic wavefield imaging shows potential for effective nondestructive inspection of various engineering materials, it has been rarely applied to concrete materials owing to technical challenges including low signal-to-noise ratio (SNR) caused by inherent heterogeneity of concrete. This paper presents development of a multi-channel MEMS ultrasonic microphone array system and its application to compressed wavefield imaging of concrete materials. The developed multi-channel MEMS ultrasonic microphone array system contains eight MEMS ultrasonic microphone elements and a signal conditioning circuit that enables measurements of ultrasonic signals with high SNR. A compressed sensing approach, based on the multiple measurement vector (MMV) concept, is applied to reconstruct a full dense ultrasonic wavefield data from sparsely sampled ultrasonic wavefield data. Experiments are carried out on a laboratory concrete sample to verify the performance of the developed MEMS microphone array system and proposed compressed sensing approach and then large-scale concrete samples to demonstrate practical application. The experimental results demonstrate that the developed MEMS microphone array system provides high-quality (SNR > 20 dB) ultrasonic data collected from concrete elements; furthermore, the proposed compressed sensing approach provides accurate reconstruction of dense wavefield data, as determined by peak signal-to-noise ratio (PSNR), from sparsely measured wavefield data with compression ratios up to 85% and PSNR above 25 dB in data collected form realistic large-scale concrete samples. By combining the MEMS array system and compressed sensing approach, the total ultrasonic data acquisition time needed to produce dense wavefield data can be significantly reduced.

Instruments & Instrumentation↗
DOE OSTI2024

Comparative Life Cycle Analysis of Carbon Dioxide Utilization in Concrete Products

In this study, a comparative LCA of CO2U concrete processes is conducted, revealing promise in several research areas. The environmental impacts of replacing conventional binder and aggregates with carbonated steel slag and direct carbonation of concrete are investigated in ten different product systems, which include both ready-mix and pre-cast concretes. The results indicate that cement substitution, CO2 uptake, electricity consumption, and the electricity grid mix constitute critical levers for deep decarbonization of concrete building materials. This presentation applies LCA to inform the use of CO2U concrete technology pathways in the design of sustainable concrete while promoting transparency and rational assumptions in the presence of uncertainty. Broader themes in the work include LCA of emerging technologies and the sensitivity of LCA results to co-product management methods.

Clarke, James↗
DOE OSTI2021

Corrosion of Steel During Long-Term Exposure to Evolving Cementitious Environments

SRS is proceeding with closure of the H-Area Tank Farm (HTF) and F-Area Tank Farm (FTF). Closure consists of removing the bulk waste, heel removal, and filling the tank with tailored grout formulations. The long-term performance of the concrete and steel materials of construction and the closure grout is an important consideration for Performance Assessment (PA) of closed tanks in FTF and HTF. Over PA timeframes of hundreds, thousands, to tens of thousands of years, the chemical and physical properties of the concrete and steel materials will slowly degrade due to environmental exposure and material aging. In the interim these materials will provide a barrier to the leaching of radionuclides into the soil. Savannah River Remediation (SRR) is updating relevant portions of these analysis inputs to support an imminent revision to the HTF PA and a future update to the FTF PA. This analysis provides an update to the previous PA inputs for steel corrosion. The Central Scenario for the PA analysis includes three postulated modeling cases: 1) Realistic Case, 2) Compliance Case, and 3) Pessimistic Case. This analysis also included a Fast Flow Path Case. This latter case considered the circumstance where the initial condition of the concrete was a completely degraded state and that grout shrinkage exposed the steel to the soil environment immediately. In effect, the steel was unprotected by the concrete and grout. The cases have various degrees of conservatism considered. Chemical, physical and tank configuration parameters were investigated to understand their effects on the predicted time to release of the contaminants. The assessment reviewed the initial tank and steel configuration, service life degradation of the steel, and potential corrosion mechanisms associated with degradation of the concrete materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
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 OSTI2021

CO 2 utilization in built environment via the P CO 2 swing carbonation of alkaline solid wastes with different mineralogy

Carbon mineralization to solid carbonates is one of the reaction pathways that can not only utilize captured CO 2 but also potentially store it in the long term. In this study, the dissolution and carbonation behaviors of alkaline solid wastes (i.e., waste concrete) was investigated. Concrete is one of the main contributors to a large carbon emission in the built environment. Thus, the upcycling of waste concrete via CO 2 utilization has multifaceted environmental benefits including CO 2 emission reduction, waste management and reduced mining. Unlike natural silicate minerals such as olivine and serpentine, alkaline solid wastes including waste concrete are highly reactive, and thus, their dissolution and carbonation behaviors vary significantly. Here, both conventional acid (e.g., hydrochloric acid) and less studied carbonic acid (i.e., CO 2 saturated water) solvent systems were explored to extract Ca from concrete. Non-stoichiometric dissolution behaviors between Ca and Si were confirmed under far-from-equilibrium conditions (0.1 wt% slurry density), and the re-precipitation of the extracted Si was observed at near-equilibrium conditions (5 wt% slurry density), when the Ca extraction was performed at a controlled pH of 3. These experiments, with a wide range of slurry densities, provided valuable insight into Si re-precipitation phenomena and its effect on the mass transfer limitation during concrete dissolution. Next, the use of the partial pressure of CO 2 for the pH swing carbon mineralization process was investigated for concrete, and the results were compared to those of Mg-bearing silicate minerals. In the P CO 2 swing process, the extraction of Ca was significantly limited by the precipitation of the carbonate phase (i.e., calcite), since CO 2 bubbling could not provide a low enough pH condition for concrete–water–CO 2 systems. Furthermore, this study showed that the two-step carbon mineralization via P CO 2 swing, that has been developed for Mg-bearing silicate minerals, may not be viable for highly reactive Ca-bearing silicate materials (e.g., concrete). The precipitated calcium carbonate (PCC) derived from waste concrete via a pH swing process showed very promising results with a high CO 2 utilization potential as an upcycled construction material.

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

Understanding the Elastic, Plastic, and Damage Features in Fracturing of Self-reinforced Thermoplastic Composites via Non-destructive Digital Imaging Correlation

This work demonstrated the utilization of non-destructive Digital Imaging Correlation (DIC) method to characterize the elastic, plastic, and damage features during the Mode I intra-laminar fracturing process of self-reinforced thermoplastic composites by using a self-reinforced polypropylene (PP) composite as an example. The DIC results clearly showed the development of huge plastic zone (PZ) and non-negligible Fracture Process Zone (FPZ) in front of the notch tip during the fracturing process, and the geometries and sizes of the foregoing zones at the peak load were further quantified. Such an interesting fracturing behavior of self-reinforced thermoplastic composites is way different from brittle materials (e.g., glass, acrylic, etc.), ductile materials (e.g., aluminum, steel, etc.), and even quasi-brittle materials (e.g., concrete, nanoparticle-reinforced composites, tough ceramics, wood, cement, carbon/glass fiber-reinforced polymers, etc.). Thus, understanding the elastic, plastic, and damage features is the first step before better characterizing the material fracture properties of self-reinforced thermoplastic composites through new analytical methods and computational modeling. These efforts are of utmost importance for wide applications of self-reinforced thermoplastic composites in various engineering fields in the future.

Lightweight Composites, Self-reinforced Thermoplas↗
DOE OSTI2023

Metamodels for Rapid Analysis of Large Sets of Building Designs for Robotic Constructability: Technology Demonstration Using the NASA 3D Printed Mars Habitat Challenge

Disruptive robotic construction technologies such as additive deposition of cementitious materials like concrete (or "3D concrete printing") require the synchronous operation of multiple pieces of equipment in the production setup. In such an environment, it is crucial to simulate the robotic motions (for toolpath clashes) and the cementitious material behavior (for toolpath failures) to ensure fail-proof constructability of the envisioned building geometry. However, toolpath clash detection requires 4D simulations of the production setup, which are computationally graphics intensive, whereas toolpath failure detection requires actual 3D printing of test parts from the geometry to identify areas prone to failure while 3D printing, which is physically tedious. Both these processes, being computationally and physically intensive, have largely curtailed designers from simulating and exploring large sets of design options with varying geometries and toolpath configurations. To overcome this and allow designers to explore large sets of design possibilities, this paper proposes two novel computational metamodels capable of performing robotic toolpath clash detection and failure detection with significantly reduced times than the earlier approaches. The developed metamodels were used to rapidly simulate large sets of building design options for robotic constructability in the NASA 3D-Printed Mars Habitat Challenge.

clash detection↗