Summary of key articles demonstrating photoacoustic imaging of the eye.
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In the eye, the major endogenous light-absorbing materials are hemoglobin and melanin. Hemoglobin is present in blood vessels in the iris, choroid, ciliary body, retina, conjunctiva, and pathologic neovascularization. Melanin is present inside the uvea (iris, choroid and ciliary body), retinal pigment epithelium (RPE) and pigmented tumors.
Photoacoustic imaging (PAI), which converts light energy into sound waves, has been demonstrated to image hemoglobin [1, 2] and melanin [3, 4]. Thus eyes are an ideal system for PAI. PAI can provide an ocular vascular image based on the inherent optical absorbance of hemoglobin. Many eye diseases, including corneal neovascularization, macular degeneration, diabetic retinopathy, sickle cell retinopathy, and retinal vein occlusions, involve abnormalities in the vasculature. Thus the unique ability of PAI to provide detailed vascular morphologic information can assist ophthalmic diagnosis.
Currently several imaging modalities have been used to diagnose and monitor ocular diseases. Well-established imaging instruments include color fundus photography, ultrasound (US) imaging, fluorescein angiography (FA), indocyanine green angiography (ICGA), scanning laser ophthalmoscopy (SLO), optical coherence tomography (OCT) and OCT angiography (OCTA). Each imaging modality has advantages and disadvantages. OCT has a limited depth of penetration and has difficulty visualizing deep structures like the choroid and sclera. FA and ICGA require the use of an exogenous contrast agent that may cause adverse reactions and cannot specify the depth of the vessels. OCTA is unable to show leakage, provides limited view of microaneurysms, has a limited depth of penetration, and has a restricted field of view often with motion artifacts.
PAI is a new, emerging, non-ionizing and non-invasive imaging technology. PAI is based on the optical absorption contrast so that can provide anatomical information and functional analysis for the eye as well as with a high depth of penetration. In 2010, photoacoustic imaging was first described in the eye of a living animal [4]. Since then, there is a huge advance in photoacoustic imaging of the eye. Furthermore, the application of multimodality imaging systems including integrated photoacoustic microscopy (PAM) with other imaging modalities and the use of contrast agents for molecular imaging have undergone significant development. This chapter focuses on recent advances and applications of photoacoustic imaging of the eyes.
Photoacoustic imaging systems can be divided into several categories which include: optical-resolution photoacoustic microscopy (OR-PAM), acoustic-resolution photoacoustic microscopy (AR-PAM), photoacoustic computed tomography (PACT), photoacoustic tomography (PAT) [5, 6]. Ocular PAI systems are primarily OR-PAM and AR-PAM systems due to the importance of high resolution imaging in the eye [7, 8, 9]. AR-PAM is used to image deep-tissues, where an illumination laser is diffusively delivered to the tissue and a focused acoustic detector is used to detect the induced PA signals. The lateral resolution of AR-PAM is determined by the acoustic focus spot, and the axial resolution is determined by the acoustic center frequency and bandwidth [5, 8]. OR-PAM has a tighter optical focus than AR-PAM and can achieve micrometer-level lateral resolution. The lateral resolution of OR-PAM is determined by the optical focal spot, and the axial resolution is still determined by the acoustic parameters [5, 8].
PAI can also be classified into mechanical-scanning systems and optical-scanning imaging systems [7]. In the mechanical-scanning mode, both the optical excitation and ultrasound transducer are simultaneously scanned over a planar surface. Each step of the scan can detect and generate a PA signal. During imaging, a water tank is necessary to maintain ultrasound coupling [6]. The mechanical-scanning can be used to visualize almost all the eye tissues, including the cornea, iris, lens, retina, choroid, sclera, and blood vessels [4]. In the optical-scanning mode, the focused optical illumination is raster-scanned using galvanometers, while the ultrasound transducer is kept stationary [10]. Figure 1a shows the schematic diagram of the optical-scanning in a multimodality system. Figure 1b illustrates the physical setup [11]. Compared with mechanical-scanning, optical-scanning can provide higher scanning speed, and it is suitable for chorioretinal microvasculature imaging, and compatibility with OCT and SLO [9, 12].
Integrated multimodal PAM, OCT, and FM imaging system. (a) Schematic. (b) Photograph of the multimodality retinal and choroidal imaging system. OPO, optical parametric oscillator; SLD, superluminescent diode; BS, beam splitter; DM, dichroic mirror; SL, scan lens; OL, ophthalmic lens; CIP, conjugate image planes. Adapted with permission from Ref. [
Currently, many applications of ocular PAI have been reported. This chapter summarizes those applications by the anatomic portion of the eye imaged and functional information.
Anterior segment PA imaging of a normal eye receives signal from hemoglobin in the red blood cells of the iris microvasculature. Both AR-PAM and OR-PAM have been reported for iris vascular imaging. de la Zerda et al. [4] have used AR-PAM to qualitatively assess the rabbit eye
PA images of the iris vasculature. (a) Label-free photoacoustic ophthalmic angiography of hemoglobin oxygen saturation sO2 in the iris microvasculature of a living adult Swiss Webster mouse. CP, ciliary process; MIC, major iris circle; RCB, recurrent choroidal branch; RIA, radial iris artery. Adapted with permission from Ref. [
Normal corneal tissue is avascular and optically transparent. Corneal neovascularization is a pathologic condition that can lead to reduced vision characterized by the presence of blood vessels in the cornea. This pathophysiology has been observed in humans with inflammatory or autoimmune responses.
Liu et al. [16] have used a mechanical scanning OR-PAM system to image corneal neovascularization of alkali-burn-injured mouse eyes
PA images of the corneal neovascularization. (a) Photograph (left) and PA maximum intensity projection (MIP) image (right) of a mouse eye. Adapted with permission from Ref. [
Several of the above studies of the anterior segment vasculature images have utilized mechanical scanning OR-PAM system. However, mechanical scanning OR-PAM has limitations: the imaging speed is slow and careful coupling medium is required. Recently, a non-interferometric photoacoustic remote sensing microscopy system has been developed with a high scan rate and an improved signal-to-noise (SNR).
Posterior segment PAI of a normal eye images red blood cells in the retinal and choroidal microvasculature. To obtain the images, both AR-PAM and OR-PAM systems have been used, along with mechanical scanning and optical scanning systems.
Using an AR-PAM system, de la Zerda et al. [4] have used a pulsed laser (wavelength 740 nm) combined with a 25 MHz central frequency transducer to mechanically scan a living rabbit eye. They have obtained the blood distribution of the posterior eye. But owing to the system’s lateral resolution of 200 μm, limited features of the retinal or choroidal vasculature are visualized. Furthermore, it took 90 min to acquire the full 3-D image.
Jiao et al. [12] have developed an optical-scanning OR-PAM system for
Retinal vasculature imaging by optical-scanning OR-PAM system. (a–c) PA imaging of retinal vasculature in a rat eye. (a) Showing the imaged retinal structure by PAOM. (b) Segmented PAOM images of the retinal blood vessels. (c) Pseudo-colored PAOM images of the retinal vessels and RPE. Adapted with permission from Ref. [
Before 2017, most reported PAM imaging of the posterior segment used small animals, like mice and rats. Mice have an axial length of ~3 mm and rats ~6 mm, which is much smaller that the human axial length of ~23 mm. In order to improve clinical translation of the technology, Tian et al. [19] have developed a novel PAM system to visualize rabbit chorioretinal vasculature. Rabbit eyes have an axial length of 18.1 mm [23], which is almost 80% of the axial length of human eyes. They have used a 570 nm pulsed laser. The excited PA signals have been captured by a custom-built needle-shaped ultrasonic transducer (27 MHz; bandwidth: 60%) placed in contact with the conjunctiva by ultrasound gel. The laser pulse energy on the rabbit cornea was 80 nJ or half the ANSI safety limit [24]. The lateral and axial resolution of the PAM system were 4.1 and 37 μm, respectively. This PAM system obtain high-resolution images of New Zealand rabbit retinal and choroidal vasculature (Figure 4d–f).
Wei et al. [25] have first applied an OCT-guided PAOM system to image the choroidal vessels in albino rats. The laser output optical wavelength was 578 nm, and the laser pulse energy was set below 40 nJ. The induced PA waves were detected by a custom-built, unfocused needle ultrasonic detector (35 MHz; bandwidth: 50%). The lateral resolution of PAOM was around 20 μm and the axial resolution of PAOM was 23 μm. Based on the OCT cross-sectional images, the distance from the retinal vessel layer to the choroid was found to be 200 μm [26]. Thus, the retinal and choroidal vessels were well resolved along the axial direction. Figure 5a–c show PAOM images of segmented retinal vessels and choroidal vessels. Song et al. [20, 27] have used an integrated PAOM and OCT system to detect
PA images of the chorioretinal vasculature. (a–c) PA imaging of chorioretinal vessel in an albino rat eye. (a) Complete chorioretinal vessel network image. (b) Segmented retinal vessels. (c) Segmented choroidal vessels [
Retinal neovascularization (RNV) is the growth of abnormal new retinal blood vessels and represents a major cause of vision loss and blindness. RNV is a common complication of several retinal diseases, including proliferative diabetic retinopathy (PDR), retinal vein occlusions (RVO), sickle cell retinopathy, and retinopathy of prematurity (ROP).
Zhang et al. [11] have demonstrated an integrated PAM, OCT, and fluorescence microscopy (FM) multimodality system to evaluate RNV
PA images of the retinal neovascularization. (a–c) RNV in albino rabbits. (a) Color fundus image. (b) 2D PAM image indicated by white dashed box in (a). (c) 3D reconstruction of PAM image. (d–f) RNV in pigmented rabbits. (d) Color fundus image. (e) 2D PAM image indicated by white dashed box in (d). (f) 3D reconstruction of PAM image. White arrows indicate normal retinal vessels; green arrows indicate RNV. Adapted with permission from Ref. [
Choroidal neovascularization (CNV) is characterized by the abnormal growth of new vessels originating from the choroidal vasculature and their subsequent growth under the RPE, subretinal space, or a combination of both [29]. CNV most commonly occurs in neovascular age-related macular degeneration (AMD), which is a major cause of vision loss. Dai et al. have used PAM system to investigate laser-induced rat CNV evolution. For the PAM system, the laser output wavelength was 532 nm, and the pulse energy was 60 nJ. The induced PA signals from the retina were detected by a customized ultrasonic transducer (30 MHz; bandwidth: 15 MHz). the axial and lateral resolution of PAM were 50 and 20 μm, respectively. The new capillaries growing from the choroid up to subretinal space can be distinguished as shown in Figure 7.
PAM images at different depth in CNV rat fundus. (a) 2D enface image of anterior retinal structure. (b) 2D enface image of posterior retinal structure. (c) 2D enface image of RPE layer. Scale bars indicate 100 μm. Adapted with permission from Ref. [
Retinal oxygen metabolic rate (rMRO2) is an essential parameter in the retina and can help further understanding of some blinding diseases, such as diabetic retinopathy [31, 32] and glaucoma [33, 34]. The precise measurement of rMRO2 can be critical in investigating these blinding diseases. Song et al. [35] and Liu et al. [36] have successfully determined rMRO2 in rats by integrating PAOM and OCT. Obtaining rMRO2 measurements required measuring retinal blood flow and sO2 together. They have quantified retinal blood flow by Doppler SD-OCT, and retinal sO2 by PAOM at three wavelengths (570, 578, and 588 nm). Owing to the distinct light absorption spectrum between HbO2 and HbR, multi-wavelength imaging can assess the sO2 in retinal vessels. They have calculated total retinal blood flow as 7.43 ± 0.51 and 7.38 ± 0.78 μL/min within the venous and arterial systems, respectively. The sO2 value in arterial and venous blood were 93.0 ± 3.5 and 77.3 ± 9.1%, respectively. In PAOM system, they used a tunable laser (output laser wavelength: 570, 578, and 588 nm), the laser energy was 40 nJ/pause. Acoustic waves were detected by an unfocused small-footprint ultrasonic transducer (40 MHz; bandwidth: 30 MHz). The lateral resolution was 20 μm, and the axial resolution was 23 μm. The study measured rMRO2 in normal small animals. Hariri et al. [37] have demonstrated the use of PA ocular imaging (PAOI) in measuring chorioretinal oxygen saturation (CR-sO2) gradients in New Zealand white rabbits with ocular ischemia model. The PAOI signal showed a sixfold decrease in CR-sO2 after significant elevation of IOP during ischemia. In the PAOI, they used a tunable laser (680–970 nm), 750 and 850 nm were used to differentiate the HbO2 and HbR. A linear array ultrasound transducer with a center frequency of 15 MHz was used to detect acoustic signals. The lateral and axial resolution were 580 and 290 μm, respectively. One limitation of the study was balancing special resolution and penetration depth. Although they could achieve much deeper penetration, they could not discriminate between the retina and the choroid, nor could they distinguish individual vessels.
Melanin is naturally present in the eye within the iris, ciliary body, pigmented choroid, and RPE [38]. The RPE is a single layer of epithelial cells beneath the neurosensory retina and tightly adherent to the underlying choroid. The RPE plays a crucial role in the overall health of the retina: nourishing photoreceptors and disposing of retinal waste and metabolic end products. The melanin concentration in RPE can decrease over time due to light exposure and oxidative stress [39]. RPE melanin decrease is a sign of ocular senescence and is a risk factor and a pathognomonic sign of AMD [40, 41]. To further study melanin, PAI has been used to specifically detect and quantify melanin [42].
In 2010, Silverman et al. [43] for the first time have demonstrated that PAI can acquire images of melanin in the iris in
PA images of melanin of the RPE. (a, b) MAP of the PAM images of the RPE of the pig eye: (a) without AO. (b) With AO. Adapted with permission from Ref. [
The above papers are qualitative studies of eye melanin by PAI. PAI also has the capability of providing a quantitative reading of melanin concentration in the eye. Shu et al. [49] have performed a Monte Carlo (MC) stimulation to investigate light propagation and energy deposition in the eye and tested the feasibility of using PAOM to quantify the RPE melanin concentration. In this study, they used PA signals from retinal blood vessels as references to measure RPE melanin variation. However, the main challenge in accurate quantification of RPE melanin concentration is to distinguish the RPE from underlying pigmented choroid. The RPE is a 10 μm thick cell monolayer and is tightly attached to the choroid, and thus a higher axial resolution of PAOM was necessary. Shu et al. [45] then have used a micro-ring resonator (MRR) detector in their PAOM system to increase the axial resolution (<10 μm). They obtained images where the RPE and choroid can be distinguished in
PAI can obtain volumetric images of melanin in the eye and can quantify melanin in the RPE and the choroid. However, the technique has yet to be explored in eye disease models and the human eye, so it is unknown that how it can be used in eye research and clinic in the future.
PA imaging can obtain structural and functional imaging of the eye. PAI can also be combined with other ocular imaging devices, such as OCT, SLO, AF, AO, FA, and fundus photography. These combined multimodal platforms can compensate the weaknesses of each system and provide more comprehensive information of the eye. That would be very beneficial for investigating ocular pathology and detecting disease. For instance, with correcting wave-front errors with AO, the lateral resolution of PAM can be improved [44]. With PAM and AF combined, information on the distribution and concentration of retinal melanin and lipofuscin can be obtained
PA imaging can achieve anatomic information with monochromatic pulsed laser illumination. However, to acquire ocular functional information using PAI, multi-wavelength laser illuminations is required. An optical parametric oscillator (OPO) (for example, the Ekspla NT-242, pulse repetition rate 1 kHz, duration 3–6 ns, tunable wavelength range 405–2600 nm) can be used as a suitable laser source to obtain the above information. However, in multimodality systems, such as PA imaging and OCT, the two modalities can require different types of illuminations and thus separate light sources. Liu et al. [48] have used a single ultrafast laser source (pulse repetition rate 10 kHz, pulse duration 3 ns, center wavelength 800 nm; bandwidth 30 nm) to acquire melanin-specific images of
In reported studies to date, researchers either placed a water tank on the cornea or directly coupled an ultrasonic needle transducer with the eyelid or sclera using ultrasonic gel or balanced salt solution (BBS). Given the sensitivity of the human eye, this is not ideal for clinical application on patients. Non-contact remote sensing has been described where an interferometer is used to sense the surface displacement induced by PA ultrasound signals [53, 54]. Discovering a non-contact ultrasonic detection with both stability and sensitivity is a promising area of active investigation.
The field of view (FOV) of PA imaging is limited by the ultrasound transducer. The typical scan area of reported studies has been shown in Table 1. For most studies, the image area was no more than 3 × 3 mm. The human retina area is about 10 cm2, so increasing the field of view would be beneficial, possibly through novel ultrasound transducer configurations or array patterns.
PA system | Applications | Publication | Scanning pattern | Laser illumination | US | Speed and size | Resolution | Animal |
---|---|---|---|---|---|---|---|---|
AR-PAM | whole eye | de la Zerda [4] | Wide field illumination | W: 700/740 nm E: 0.5 mJ/cm2 | CF: 15/25 MHz B: 60% | 90 min for 12 × 8 mm | L: 200/240 μm A: 83/50 μm | rabbit |
OR-PAM | Iris vasculature and sO2 | Hu [13] | Mechanical scanning | W: 570/578 nm E: 40 nJ | CF:75 MHz | 120 min for 2 × 2 mm | L: 5 μm A: 15 μm | Swiss Webster mouse |
OR-PAM | Iris vasculature | Rao [15] | Hybrid-scanning | W: 532 nm E: 60 nJ | B: 25 MHz | 128 s for 4 × 4 mm | L: 3.5 μm A: <31 μm | Albino mouse |
OR-PAM | Iris vasculature | Zhao [14, 55] | Mechanical scanning | W: 532 nm E: 11 mJ/cm2 | CF: 75 MHz | 0.5 frame/s | L: 5.43 μm | SD rat |
OR-PAM | Corneal NV; iris vasculature | Liu [16] | Mechanical scanning | W: 532 nm E: 80 nJ | CF:10 MHz B: 80% | 20 min for 3 × 3 mm | L: 2.76 μm A: 50 μm | C57BL6/J mouse |
OR-PAM | Anterior vasculature | Jeon [17] | Mechanical scanning | W: 532 nm | CF: 50 MHz B: 50 MHz | 3 × 3 mm | L: 3 μm | BALB/c mouse |
OR-PAM | Corneal NV; blood flow and sO2 | Kelly-Goss [18] | Mechanical scanning | W: 532/559 nm E: 50/30 nJ | CF:35 MHz B: 70% | 30 min for entire cornea | 2.7 μm | Transgenic Tie2-GFP mouse |
PAOM+SD-OCT | Retinal vasculature; RPE | Jiao [12] | Optical scanning | W: 532 nm E: 40 nJ | CF: 30 MHz B: 50% | 2.7 s for 2 × 2 mm | L: 20 μm A: 23 μm | Long Evans rat |
PAOM+SD-OCT | Retinal and choroidal vasculature | Wei [25] | Optical scanning | W: 578 nm E: 40 nJ | CF: 35 MHz B: 50% | 2.7 s for 2 × 2 mm | L: 20 μm A: 23 μm | SD rat |
PAOM+SD-OCT + AF-SLO + FA | Retinal and choroidal vasculature; RPE | Song [20] | Optical scanning | W: 532 nm E: 40 nJ | CF: 40 MHz B: 15 MHz | 2.7 s for 2 × 2 mm | L: 20 μm A: 23 μm | Albino /pigmented rats |
Fundus camera +PAOM | Retinal and choroidal vasculature | Liu [22] | Optical scanning | W: 532 nm E: 60 nJ | CF: 35 MHz B: 50% | 2.7 s for 2 × 2 mm | L: 20 μm A: 23 μm | Albino /pigmented rats |
PAOM+SD-OCT | Retinal and choroidal vasculature; RPE | Song [27] | Optical scanning | W: 532 nm E: 40 nJ | CF: 40 MHz B: 16 MHz | 2.7 s for 2 × 2 mm | L: 20 μm A: 23 μm | Albino /pigmented rats |
PAM+OCT | Retinal and choroidal vasculature | Tian [19] | Optical scanning | W: 570 nm E: 80 nJ | CF: 27 MHz B: 60% | 65 s for 3 × 3 mm | L: 4.1 μm A: 37 μm | Albino rabbit |
PAM+OCT + FM | Retinal vasculature and RNV | Zhang [11] | Optical scanning | W: 532 nm E: 80 nJ | CF: 27 MHz B: 60% | 65 s for 3 × 3 mm | L: 4.1 μm A: 37 μm | Albino/pigmented rabbits |
PAM+OCT | RVO and RNV | Nguyen [28] | Optical scanning | Multi-wavelength E: <80 nJ | CF: 27 MHz B: 60% | 65 s for 3 × 3 mm | L: 4.1 μm A: 37 μm | Albino rabbit |
PAM+OCT | CNV; retinal structure; RPE | Dai [30] | Optical scanning | W: 532 nm E: 60 nJ | CF: 40 MHz B: 16 MHz | 19.5 frame/s | L: 20 μm A: 50 μm | Brown Norway rat |
PAOM+OCT | Retinal rMRO2; sO2; blood flow | Song [35], Liu [36] | Optical scanning | W:570/578/588 nm E: 40 nJ | CF:30 MHz B: 15 MHz | 2.7 s for 2 × 2 mm | L: 20 μm A: 23 μm | SD rat |
OR-PAM | Chorioretinal sO2 | Hariri [37] | Optical scanning | W: 750/850 nm E: 8 ± 0.5 mJ | CF: 15 MHz | 0.8 frame/s | L: 580 μm A: 290 μm | Albino rabbit |
AO-PAM | Ciliary body, RPE melanin | Jiang [44] | Optical scanning | W:532 nm E: 40 nJ | CF:30 MHz B:50% | 2.7 s for 2 × 2 mm | L: 2.5 μm A: 23 μm | Pig |
PAOM+AF | RPE melanin; lipofuscin | Zhang [46] | Optical scanning | W: 532 nm E: 40 nJ | CF: 30 MHz B: 50% | 2.7 s for 2 × 2 mm | L: 4.5 μm A: 23 μm | Albino/pigmented rats |
PAOM+SD-OCT | RPE melanin | Liu [47] | Optical scanning | W: 1064/532 nm E: 20 nJ | CF:30 MHz B: 50% | 2.7 s for 2 × 2 mm | L: 20 μm A: 23 μm | SD/Long Evans rats |
Broadband PAM | RPE melanin concentration | Shu [45] | Optical scanning | W: 532 nm | MRR B: 280/27 MHz | 22 s per image | A: <10 μm | Porcine/human RCCs |
Summary of key articles demonstrating photoacoustic imaging of the eye.
W, wavelength; E, energy; CF, central frequency; B, bandwidth; NV, neovascularization; SD, Sprague Dawley; RPE, retinal pigmented epithelial; RNV, retinal neovascularization; RVO, retinal vein occlusion; CNV, choroidal neovascularization; rMRO2, retinal oxygen metabolic rate; AO, adaptive optics; AF, autofluorescence; MRR, micro-ring resonator; RCC, RPE-choroid complexes.
Several current PA imaging systems can acquire high-resolution images in <1 min. The imaging speed is limited by the laser pulse repetition rate. The image speed can be reduced until it depends on the ultrasound propagation time from the posterior eye. The advantage of improving imaging speed is that it will reduce motion artifacts and increase patient comfort. Ideally a clinical PA system would acquire images in less than a second to a couple seconds.
The lateral resolution of PA imaging is determined by the smallest achievable spot size of the illuminating light in the retina. Tian and Zhang et al. described the lateral resolution of their PAM system as 4.1 μm [11, 19]. AO allows one to correct for ocular aberrations and has been applied to ophthalmic imaging to improve resolution. A feasibility study was conducted on the integration of AO with PAM for
The axial resolution of PA imaging is determined by the bandwidth of the ultrasound transducer. The larger ultrasonic bandwidth will allow higher axial resolution, but with less sensitivity. Therefore, a balance is required between axial resolution and sensitivity.
Currently many PA images require post-image processing to display images. Further investigation of an advanced ophthalmic PA imaging system is to obtain real-time imaging.
PA imaging is often limited to albino animals when imaging the choroid due to the high PA signal of the RPE melanin in pigmented animals. Further methods need to be developed and refined to penetrate the RPE layer and allow improved choroidal visualization. NIR light has been proposed as a solution, but further testing is needed.
PA imaging has been demonstrated in some animal eye models to date, including mouse corneal neovascularization model, rat CNV model, and rabbit retinal neovascularization model. PA imaging needs to be further explored in more eye disease models to evaluate how the information provided by PA imaging will be used clinically in the future.
To improve PA image sensitivity and specificity, exogenous contrast agents can be utilized. PA imaging with exogenous contrast agents also allows one to extend the imaging scope to molecular imaging [56, 57]. Exogenous contrast agents for PA imaging include organic and inorganic agents. However, each agent has advantages and limitations. Organic agents (e.g., ICG) can have a limited level of contrast enhancement but a more rapid path to clinical translation [58]. Inorganic agents (e.g., gold nanoparticle (AuNP)) can offer higher contrast but a less rapid path to clinical translation due to less long-term evidence of biosafety [59, 60]. Thus, exploring suitable exogenous contrast agents with safety and high contrast can be used for PA imaging will be meaningful in future research. In addition, theranostic agents that can be used both for diagnostic imaging and therapy, should be further refined and developed to allow for targeted therapy at the time of imaging.
Before PA imaging can be applied to human imaging, a thorough evaluation of laser safety is necessary. Although the reported systems compare their laser fluence to the ANSI laser safety regulations, [24] one must monitor the long-term effect of both single and multiple imaging sessions on the structure and function of the retina. In additional, regulatory approval should be sought for a clinical system so that PA can be applied to patients and diseases.
The chapter introduces the applications, recent developments, and future directions of PA imaging in the eye. It has been demonstrated that PA imaging can provide both anatomic and functional information of eye with high-resolution, high sensitivity, high-contrast, and high depth of penetration. This chapter describes the ocular structure of PA imaging including normal vasculature of the iris, retina, and choroid, neovascularization in cornea, retina, and choroid, and melanin of the RPE. This chapter summarized PA imaging to quantify the functional information of measuring the vascular sO2 and quantifying the absolute melanin concentrations. Limitations and future directions of PA imaging of the eye are also discussed.
This research was supported by a grant from the National Eye Institute 1K08EY027458 (YMP), Fight for Sight-International Retinal Research Foundation FFSGIA16002 (YMP), unrestricted departmental support from Research to Prevent Blindness, and the University of Michigan Department of Ophthalmology and Visual Sciences, and China Scholarship Council No.201806370270.
None.
Concrete is a mixture made of aggregates, water, cement, and different additives. The “lightweight” term can be added to different types of concrete which are all common in one specification, and that is “lower density” than normal weight concrete (NWC). This reduction in density is achievable by different methods such as using lightweight aggregate (LWA) in concrete, foamed concrete (FC), and autoclaved aerated concrete (AAC) or by any other techniques that reduce the final specific weight of the product, and thus the achieved weight is less than what we have in NWC mixtures. Whereas NWC weighs from 2240 to 2450 kg/m3, lightweight concrete weighs ∼300–2000 kg/m3, but the practical range of density for lightweight concrete is 500–1850 kg/m3. Before talking about the background of LWC, we prefer to explain a little more about the different types of LWC and their mechanical properties.
There are a variety of lightweight aggregates that can be used in the production of LWAC, such as natural materials, like volcanic pumice, and the thermal-treated natural raw materials like expanded glass, clay, shale, etc. LECA is an example of expanded clay and Poraver is an example of expanded glass aggregates. There are also other types, which are aggregates made of industrial by-products such as fly ash, like Lytag. The final properties of the LWC will depend on the type and mechanical properties of LWA used in the concrete mixture.
With incorporation of considerable amount of entrained air (20% to 50%) in concrete, foamed concrete is produced which is a workable, low-density, pumpable, self-levelling, and self-compacting LWC. Foamed concrete is used more as a nonstructural concrete for filling voids in infrastructures, a good thermal insulation, and filler for space in buildings with less increase in the dead load.
AAC, or also named as autoclaved gas concrete, to which a foaming agent is added, was first produced in 1923 in Sweden and is one of the oldest types of LWC. AAC construction systems were then popular all around the world because of its ease of use.
Lightweight aggregate concretes (LWAC) can be used for structural applications, according to the American Concrete Institute (ACI). To be considered as structural lightweight concrete (SLWC), the minimum 28-day compressive strength and maximum density are 17 MPa and 1840 kg/m3, respectively. The practical range for the density of SLWC is between 1400 and 1840 kg/m3. LWC made of a material with lower densities and higher air voids in the cement paste are considered as nonstructural lightweight concrete (NSLWC) and will most likely be used for its insulation and lower weight properties. LWC with compressive strength less than 17 MPa is also considered as NSLWC. There are several benefits with using LWAC such as improved thermal specifications, better fire resistance, and dead load reduction which results in lower cost of labor, transportation, formworks, etc., especially in precast concrete construction industry. With the reduction of the concrete density, the properties of the concrete change fundamentally. For two specimens of concrete with the same compressive strength, but one made of LWC and the other one made of NWC, the tensile strength, ultimate strains, and shear strengths are all lower in LWC than NWC, while the amount of creep and shrinkage is higher for LWC. LWC are also less stiff than the equivalent NWC. However, there are benefits in using LWC such as reduction in dead load that results in slight reduction in the depth of a beam or slab. It is also observed that the elastic modulus of LWC is lower than the equivalent strength of NWC, but when considering the deflection of a slab or beam, this is counteracted by the reduction in dead load.
In the present chapter after the discussion about the lightweight concrete and its properties, we will study about the compressive strength of LWC and the methods for evaluation and prediction of compressive strength of LWC. Further a case study of LWC made of LWA will be conducted and presented for a better understanding of the properties of LWC. In the end the conclusion of the chapter will be drawn.
Concrete is a relatively heavy building material; therefore many experiments have been conducted throughout the twentieth century to decrease its weight without impairing other properties. During the 1920s and 1930s, many different types of lightweight concrete were developed, e.g., Durisol, Siporex, Argex, and Ytong. Probably the most famous and first type of autoclaved gas concrete was Ytong. It was invented by the Swedish architect, Johan Axel Eriksson, assistant professor at the Royal Institute of Technology in Stockholm. In the early 1920s, Eriksson experimented with different samples of gas concrete and put the mixtures in an autoclave to speed up the curing process. In November 1929, the industrial production of Ytong blocks began. The name combines the y of Yxhult, the town where the first Swedish factory was located, and the end of betong, the Swedish word for concrete. The material was very popular in Sweden from 1935 onward, with a true breakthrough immediately after World War II, when it became one of the most important building materials in the country. Also, the manufacturing process was exported to other countries such as Norway, Germany, the UK, Spain, Poland, Israel, Canada, Belgium, and even Japan. The autoclaved gas concrete Siporex was developed in Sweden in 1935. The LWAC, Argex, was first produced in Denmark in 1939 under the international brand name Leca. Starting with an annual production in Copenhagen of 20,000 m3, the total production throughout Europe had increased by 1972 to nearly 6 million m3 per year (adopted from postwar building materials “postwarbuildingmaterials.be”).
The later type of LWC which is called LWAC is one of the most popular one among them and from that time until today has been the subject of many research works around the word. Even today there are many ongoing extensive research programs on SLWC and NSLWC made of LWA. In the present chapter, we focus on LWAC, and for the case study, we will discuss a part of the ongoing research of the author on LWAC [1]. Categorized examples of the research works conducted recently have been discussed below:
In 2013, a research was conducted on producing concrete containing recycled aggregates obtained from crushed structural and nonstructural lightweight concrete [2]. The mechanical properties of this concrete were investigated. Concrete compositions made of recycled lightweight concrete aggregates (RLCA) were measured for their compressive strength, modulus of elasticity, tensile strength, and abrasion resistance. The influence of the properties of the aggregates on concrete properties were discussed including concrete density, compressive strength, structural efficiency, splitting tensile strength, modulus of elasticity, and abrasion resistance. This research proved that it is possible to produce structural recycled lightweight concrete from crushed, structural, and nonstructural LWC with densities below 2000 kg/m3. Improvements in mechanical properties can be seen when the LWA is replaced with RLCA. The study concluded that recycled lightweight aggregate is a potential alternative to conventional LWC.
In 2015, other researchers studied the properties of LWC consisting of cinder and light expanded clay aggregates (LECA) [3]. By replacing coarse aggregate with blended lightweight aggregates such as cinder and LECA, there was a reduction in weight and, respectively, a decrease in compressive strength, but they were able to use cinder and LECA as a replacement for normal coarse aggregate to reduce the cost, while the compressive strengths were close to the strengths of NWC. The average compressive strength for samples that included the abovementioned LWA was 39.2 N/mm2, while the average compressive strength for NWC was 43.4 N/mm2. The density of the LWC varied from 1800 to 1950 kg/mm3 and the density for the NWC was 2637 kg/m3. The slump from the fresh concrete mix and the average compressive and tensile strength of the hardened concrete were analyzed in the research.
Similar research presented on waste materials showcased that waste materials can be reused as construction materials, in 2016 [4]. Foam glass and high-impact polystyrene (HIPS) are materials they collected through the processing of waste materials. The glass foam is found from a glass cutlet, and the polystyrene is collected from butadiene modified rubber. They investigated the compressive and flexural strength, water absorption, and bulk density of the proposed concrete mixtures. LWC with foamed glass aggregates was affected by the amount of aggregate. Larger amounts of aggregate cause a decrease in compressive and bending strength and an increase in absorption. The addition of HIPS improved the compressive strength; however, it did not have a significant influence on water absorption. In 2017, Kurpinska and Ferenc studied on the physical properties of lightweight cement composites consisting of granulated ash aggregate (GAA) and granulated expanded glass aggregate (GEGA) [5]. This study showcased the significant impact of grain type and size on the physical properties of lightweight concrete. After the mechanical properties of 15 different mixtures were calculated and measured, they utilized a finite element modeling program to study the possibility of applying this type of LWC in structural elements, extenders, and insulation material.
In 2017, the material properties and effects of crushed and expanded waste glass aggregates on LWC properties were evaluated [6]. In this study, an image-based approach is used to extract the characterization of the materials. Pore measurement and pore structures of each material type were evaluated using a microscope, 3D, and X-ray micro-computed tomography. Thermal conductivity for the material was measured. There results showed that crushed and expanded waste glass aggregates are supported as alternatives for lightweight aggregates. LWC with a density less than 2000 kg/m3, including crushed waste aggregate, have shown to have a compressive strength over 38 MPa. This was considered as effective lightweight concrete, and it satisfied the desired mechanical properties.
An experimental investigation on the compressive strength and durability of LWC with fine expanded glass (FEG) and expanded clay aggregates (ECA) using different micro-fillers including ground quartz sand and silica fume was conducted in 2018 [7]. Based on their research, ECA is one of the most popular aggregates for SLWC, and using this aggregate is important for sustainable development in the construction industry. The relationships between compressive strength and density of concrete mixtures with different proportions of LWA were explored. The effects of fine LWA on density and compressive strength of LWAC were also analyzed. They could reach to compressive strengths of 39.5–101 MPa for the mixtures containing EGA and 43.8–109 MPa for mixtures containing ECA. The density of the mixtures containing EGA and ECA are 1458–2278 and 1588–2302 kg/m3, respectively. Different compressive strength-density relationships were obtained for LWC containing EGA and LWC containing ECA even though the compositions had the same amount of cement, water to cement ratio, micro filler, and total volume of LWA. While understanding the basic mechanical properties (density and compressive strength) of concrete containing LWA such as ECA and EGA was the main goal of this study, it was concluded that the application of expanded glass aggregate (EGA) in concrete is still in its early stages.
As in the present book, compressive strength of concrete is the main subject of discussion; later in this chapter, we will discuss a case study on compressive strength of a specific type of LWC containing EGA implementing a NDT method in addition to the conventional compression test. Therefore in the next section, we will briefly talk about the usage of NDT in the evaluation of compressive strength and properties of concrete.
Nondestructive testing (NDT) methods are widely used in the investigation of the mechanical properties and integrity of concrete structures. As seen in Table 1, provided by AASHTO [8], the following techniques are used for detecting defects in concrete structures for field use. In the present study, ultrasonic pulse velocity (UPV) method is used to evaluate the properties of LWC. Ultrasonic techniques measure the velocity of a pulse, generated from a piezoelectric transducer in concrete, and this measurement assesses the mechanical properties of a concrete. Based on research and correlations, the pulse velocity relates items such as compressive strength or corrosion [1]. As seen in Table 1, UPV detects corrosion in reinforcement; however, it is not studied in this report.
AASHTO states that the accurate measurement of the concrete’s strength depends on several factors and is best determined experimentally [8]. In the present work in addition to the conventional compression test, UPV is utilized to explore the properties of concrete. In general UPV tests are used to distinguish the material and integrity of concrete sample being tested. This technique enhances quality control and detection of defects. In the field, UPV verifies concrete uniformity, detects internal imperfections and finds the imperfections’ depth, estimates the deformation moduli and compressive strength, and monitors characteristic variations in concrete throughout time [9]. From observations, certain factors influence UPV. The theory for elasticity for homogeneous and isotropic materials states that the pulse velocity of compressional waves (P-waves) is indirectly proportional to the square root of the dynamic modulus of elasticity, Ed, and inversely proportional to the square root of its density,
The capability of defect detection | ||||||
---|---|---|---|---|---|---|
Method based on | Cracking | Scaling | Corrosion | Wear and abrasion | Chemical attack | Voids in grout |
Strength | N | N | P | N | P | N |
Sonic | F | N | Gb | N | N | N |
Ultrasonic | G | N | F | N | P | N |
Magnetic | N | N | F | N | N | N |
Electrical | N | N | G | N | N | N |
Nuclear | N | N | F | N | N | N |
Thermography | N | Gb | Gc | N | N | N |
Radar | N | Gb | Gc | N | N | N |
Radiography | F | N | F | N | N | F |
Capability of investigating techniques for detecting defects in concrete structures in field use [8].
G = good; F = fair; P = poor; N = not suitable; Gb = beneath bituminous surfacing; Gc = detects delamination.
Constituents of concrete | Aggregate | Size | Average influence |
Type | High influence | ||
Cement | Percentage | Moderate influence | |
Type of cement | Moderate influence | ||
Other constituents | Fly ash content | Average influence | |
Water/cement ratio | High influence | ||
Humidity degree/moisture content | Average influence | ||
Other factors | Reinforcements | Moderate influence | |
Age of concrete | Moderate influence | ||
Voids, crack | High influence |
Influencing factors for UPV method.
Therefore based on the previous studies, it is recommended that for each type of LWA used in LWC, the researchers conduct an experimental program to drive a brand new relation between UPV and compressive strength of concrete, which is not the focus of the present chapter. Hence in the present chapter, we have presented some of the most recent proposed equations, relating UPV to compressive strength of LWC, and presented some of the available equations relating UPV to compressive strength of LWC and NWC for those interested to compare the configurations of the equations and to initial their research for the specific types of LWA of interest.
During the last decades, many researchers presented different methods for the evaluation of compressive strength for LWA concrete versus UPV. The LWA in those studies consists of different types of natural or man-made LWA such as recycled lightweight concrete aggregates (RLCA), light expanded clay aggregate (LECA), high-impact polystyrene (HIPs), granulated ash aggregate (GAA), granulated expanded glass aggregate (GEGA), foam expanded glass aggregate (FEG), expanded clay aggregate (ECA), and expanded glass aggregate (EGA). In the literature several factors that influence the relation between compressive strength and UPV were examined. Most important analyzed factors included the cement type and content, amount of water, type of admixtures, initial wetting conditions, type and volume of aggregate, and the partial replacement of normal weight coarse and fine aggregates by LWA. As a result, simplified expression was proposed to estimate the compressive strength of different types of LWAC and its composition. The dependence of UPV and the modulus of elasticity were also explored in many of works [13]. They presented the expression below for a wide range of SLWC with compressive strength varying from 20 to 80 MPa. UPV and density are measured in meters per second and kg/m3. From the regression analysis,
where fc is the compressive strength of concrete (MPa), UPV is the ultrasonic pulse velocity (m/s), KUPV is a constant representing the correlation coefficient, and ρ is the dry density of specimen (kg/m3). In the research presented elsewhere [9], equations for LWC containing fibers were proposed to estimate the concrete compressive strength from respective UPV values. The equations presented below are the compressive strength of concrete at days 7 and 28, respectively:
where fc is the compressive strength of concrete (MPa) and v is the pulse velocity (m/s). Other types of equations were presented in 2015 [10], which contributed the coarse aggregate content as a ruling factor in the relationships presented. In the developed equations, the fc was represented for a compressive cube strength measured in MPa. The variable, v, is UPV and it was measured in kilometers per second. The expressions are presented below for different coarse aggregate (CA) contents:
For CA (coarse aggregate content) = 1000 kg/m3
For CA = 1200 kg/m3
For CA = 1300 kg/m3
For CA = 1400 kg/m3
Table 3 showcases some of the different equations generated by researchers in the last decades to predict compressive strength of concrete, fc, in terms of UPV [15].
No. | Proposed equations | Author, year |
---|---|---|
1 | Kheder, 1999 | |
2 | Qasrawri, 2000 | |
3 | AIJ, 1983 | |
4 | Ali-benyahia, 2017 | |
5 | Atici, 2011 | |
6 | Khan, 2012 | |
7 | Kim, 2012 | |
8 | Najim, 2017 | |
9 | Rashid, 2017 | |
10 | Trtniket et al., 2009 |
Proposed equations for finding the compressive strength of concrete using UPV [15].
In this section an experimental program was developed and conducted by the author and his graduate student to investigate the compressive strength of LWAC containing a specific type of expanded glass aggregate (EGA), to better showcase the properties of LWAC [1].
Tables 4 and 5 consist of the sieve analyses for the normal weight gravel and coarse sand, respectively, which were measured according to ASTM C136-01 [16]. The NWA’s absorption capacity, specific gravity, and moisture content are evaluated according to ASTM C 127-01 [17] and ASTM C 566 [18]. Table 6 includes aggregate properties such as specific gravity, absorption capacity, moisture content, and fineness modulus (FM). In Figures 1 and 2, the individual aggregates are shown. The maximum normal weight aggregate size was 9.53 mm (3/8″).
Sieve analysis | Sample size (SS): 2.27 kg | |||
---|---|---|---|---|
Sieve size | Weight retained (kg.) | % retained | % coarser | % finer |
19 mm | 0 | 0 | 0 | 0 |
13 mm | 0 | 0 | 0 | 0 |
9 mm | 0.047 | 2.073 | 2.073 | 97.93 |
No. 4 | 1.6 | 70.49 | 72.56 | 27.4 |
No. 8 | 0.5 | 21.622 | 94.18 | 5.82 |
No. 10 | 0.021 | 0.92 | 95.1 | 4.9 |
Passing | 0.112 | 4.9023 | 99.99 | 0.001 |
Sum of SS | 2.27 |
Sieve analysis for normal weight gravel mix.
Sieve analysis | Sample size (SS): 1000 g | ||
---|---|---|---|
Sieve no. | Weight retained (g) | % retained | % finer |
8 | 5 | 0.5 | 99.5 |
10 | 49.5 | 5.45 | 94.55 |
16 | 283 | 33.75 | 66.25 |
20 | 286.5 | 62.4 | 37.6 |
30 | 364.5 | 98.85 | 1.15 |
40 | 11 | 99.95 | 0.05 |
pan | 0.5 | 100 | 0 |
Sum of SS | 1000 |
Sieve analysis for normal weight coarse sand.
Property | Normal weight aggregates | Lightweight aggregates | |||
---|---|---|---|---|---|
Gravel mix (GM) | Coarse sand (CS) | Poraver (0.25–0.5 mm) | Poraver (1–2 mm) | Poraver (2–4 mm) | |
Specific gravity (ton/m3) | 2.4 | 2.75 | 0.55 | 0.36 | 0.32 |
Absorption capacity (%) | 2.3 | 1.87 | 19 | 9 | 9 |
Moisture content (%) | 4.5 | 6.4 | 0.5 | 0.5 | 0.5 |
Fineness modulus | 3.64 | 2.9 | 1.92 | 3.81 | 4.7 |
LWA and NWA properties.
NWA, from left to right, normal weight gravel mix, and coarse sand.
LWA, from left to right, Poraver 0.25–0.5, 1–2, and 2–4 mm.
The LWA used in this study is Poraver, [19] which is an expanded glass granule. The material is pressure resistant, durable and dimensionally stable, 100% mineral, spherical in shape, ecological, and not hazardous to health. According to the Poraver technical data sheet, the aggregate is lightweight according to ASTM C330, C331, and C332 and DIN EN 13055-1. Mineral casting and polymer concrete, plaster and dry mortar, lightweight panels, automotive, 3D printing, and other additional practices are practical applications of this material. The aggregate sizes and properties of the LWA are presented in Table 6. The Poraver technical data sheet provided the absorption capacity and moisture content on delivery and specific gravity for the LWA [19].
The experimental work includes various concrete mixes consisting of lightweight EGA, and these concrete mixes were created with partial or total replacement of NWA with LWA. The ACI 211.2-98 guide for LWC was followed for mix designing [20]. In this study, the control of the cement content is intended to properly understand the compressive strength for different concrete mixes without being influenced by the cementitious material effects. Many combinations of aggregates were tested and the optimum aggregate sizes to increase the compressive strength were selected. The mix proportions of the LWAC mixes are found in Table 7. The cement type used was Ordinary Portland cement CEM I 42.5 N. In the presented tables, Poraver size 0.25–0.5 is referred to as LWA (fine), while the LWA sizes, 1–2 and 2–4 mm, are considered as LWA (coarse).
Mix label | w/c | Cement (g) | Water (g) | GM (g) | CS (g) | LWA | LWA | LWA |
---|---|---|---|---|---|---|---|---|
(0.25–0.5 mm) (g) | (1–2 mm) (g) | (2–4 mm) (g) | ||||||
1 | 0.29 | 685 | 199 | 304 | 2545 | — | — | 154 |
2 | 1.88 | 576 | 1084 | 658 | 1275 | — | — | 2631 |
3 | 0.31 | 576 | 177 | 3284 | 508 | — | — | 767 |
4 | 0.47 | 576 | 272 | 2631 | 1021 | — | 658 | 254 |
5 | 0.47 | 576 | 272 | 658 | 1021 | 254 | 658 | — |
6 | 0.7 | 576 | 404 | 1973 | 767 | 508 | 329 | — |
7 | 0.7 | 576 | 404 | 658 | 1021 | 254 | 658 | — |
8 | 0.47 | 576 | 272 | 3284 | 1021 | 181 | — | — |
9 | 0.47 | 576 | 272 | 3284 | 767 | 167 | — | — |
10 | 0.47 | 576 | 272 | 3284 | 508 | 253 | — | — |
11 | 0.47 | 576 | 272 | 3284 | 254 | 340 | — | — |
12 | 0.47 | 576 | 272 | 3284 | 340 | 421 | — | — |
Mix proportions.
ASTM C 192 was used as the guide for making and curing concrete test specimens in the laboratory [21]. The specimens were demolded after 24 hours and submerged underwater until a day before testing. UPV (Figure 3) and the axial compression machine (ACM) in Figure 4 were used to determine the compressive strength of concrete at days 7 and 28.
Ultrasonic pulse velocity instrument.
Compression test machine.
In general it was observed that with increase in the amount of LWA in the concrete mixture, the compressive strength and UPV of LWC decrease, which was expected. In Figure 5, the relationship between UPV and fc (measured with ACM), at the age of 7 and 28 days for the LWC is presented. It can be observed that the results are scattered and more tests and specimens and concrete mixtures will be required to be able to establish a solid relationship between UPV and compressive strength for this type of LWAC. The best empirical relation obtained from curve fitting analyses for this study can be written as below:
UPV versus fc for LWC tested at days 7 and 28.
where fc is the compressive strength of concrete (MPa) and v is the pulse velocity (km/s).
To be able to investigate the effect of the LWA content in the mix proportions, we have selected the mixes with constant w/c ratio of 0.47 and gradually replaced the NWA with LWA (Table 8). Figure 6 depicts the relation between fc and replacement ratio (RR) or LWA content for these individual mix proportions. From this figure, it can be observed that for the LWC in this study, as the LWA content increases, fc decreases. Figure 7 shows the relation between UPV and RR or LWA content for these individual mix proportions. From this figure, it can be observed that for the LWC in this study, as the LWA content increases, UPV decreases as expected.
Mixes | RR | w/c | Cement (g) | Water (g) | GM (g) | CS (g) | LWA, coarse (g) | LWA, fine (g) |
---|---|---|---|---|---|---|---|---|
12a | 0 | 0.47 | 576 | 272 | 3284 | 1275 | — | 0 |
12b | 20 | 0.47 | 576 | 272 | 3284 | 1021 | — | 254 |
12c | 40 | 0.47 | 576 | 272 | 3284 | 767 | — | 508 |
12d | 60 | 0.47 | 576 | 272 | 3284 | 508 | — | 767 |
12e | 80 | 0.47 | 576 | 272 | 3284 | 254 | — | 1021 |
12f | 100 | 0.47 | 576 | 272 | 3284 | 0 | — | 1275 |
Comparison between different LWA contents.
fc versus RR for LWC.
UPV versus RR for LWC.
The relationship between UPV, fc (compressive strength), and dry density for the mix proportions in Table 8 is presented in Figures 8 and 9. It can be observed that for the LWC in this study, as the dry density increases, UPV and fc also increase, but the results are scattered when working with LWC. To be able to compare these results from those of NWC, mixes of NWC with similar compositions but without any LWA were produced, and results were presented in Figures 10 and 11. It is observed that the result for the relationship between UPV, fc and, dry density for LWC is more scattered than similar test result for NWC.
fc versus dry density for LWC.
UPV versus dry density for LWC.
fc versus dry density for NWCUPV versus dry density for NWC.
UPV versus dry density for NWC.
There are different types of LWC available in the industry that depending on the method which is used for production of each type, the properties of the LWC can be completely different. Lightweight aggregate concrete (LWAC), foamed concrete (FC), and autoclaved aerated concrete (AAC) are among the most common types. On the other hand, structural and nonstructural lightweight concrete can be produced for different purposes. Lightweight aggregate concrete, such as the one discussed in this study, are being used nowadays in the advancement of concrete technology, but it is proven that each type of LWA needs to be tested before being used in structures and even for nonstructural purposes. Compressive strength of LWC is an important characteristic of LWC that can be measured or predicted with few methods such as NDT methods. Ultrasonic pulse velocity was utilized to assess the compressive strength, fc, of the LWC containing EGA in the present study. In this chapter it was observed that LWA can replace NWA to achieve smaller bulk densities and UPV can be used as a method for evaluation of compressive strength of LWC. Based on the case study conducted in the present chapter, it was showcased that as the dry density of the LWC decreased, UPV and fc decreased, respectively. Comparisons of actual fc values obtained from CTM proved UPV can be related to fc, and the results showed similar characteristics to previous works, while the previous work’s equations cannot be used for the aggregates used in this study. The results of the present study are limited to the mix design and materials that were used in this work, and it should be noted that these results cannot be extended to other types, sizes, etc. of aggregates and different mix designs.
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