Mühendislik Fakültesi

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Advances in the computation of nmr parameters for inorganic nuclides
(ELSEVIER, 2023) Holmes, Sean T.; Alkan, Fahri; Dybowski, Cecil; 0000-0002-4046-9044; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Alkan, Fahri
In this article, we discuss practical aspects of the computation of NMR parameters of inorganic nuclides, as well as insights afforded by such calculations into the characterization of molecular-level structure and dynamics and the validation of theoretical models. An emphasis is placed on calculation of the magnetic shielding tensors of solids using cluster-based models that account for intermolecular interactions. In particular, the use of valence modification of terminal atoms using bond valence theory (VMTA/BV), which reduces net charges on clusters through terminal pseudoatoms with nonstandard nuclear charges, is demonstrated to be a robust technique for calculations on nuclei in network solids. Cluster-based calculations, including those that employ the VMTA/BV method, afford a unique opportunity to calculate magnetic shielding tensors for nuclei in solids by using density functional theory approximations beyond the generalized gradient approximation and by incorporating relativistic effects at the spin-orbit level. These developments are spurred by use of the zeroth-order regular approximation (ZORA), which provides a robust method of accounting for relativistic effects (up to the spin-orbit level) experienced by valence electrons. Calculations of NMR parameters are discussed for fluorine, cadmium, tin, tellurium, mercury, lead, and platinum, all of which have seen significant advances in recent years. These examples highlight the importance of such factors as coordination geometry, oxidation state, relativistic effects, and density functional approximations on computed magnetic shielding tensors.
A bi-criteria approach to scheduling in the face of uncertainty: Considering robustness and stability simultaneously
(Nova Science Publishers, Inc., 2014) Selcuk, Gören; Sabuncuoĝlu, Ihsan; 000-0002-5320-4213; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Selcuk, Gören; Sabuncuoĝlu, Ihsan
It is possible to scrutinize impacts of uncertainty on schedules from two different perspectives. The flrst one has to do with the fact that schedules are required to main- tain high performance in the face of uncertainty. In other words, it is desired that their performances are insensitive to negative impacts of disruptions. We refer to this view- point as the robustness perspective. The second viewpoint is about another quality: when a schedule is executed in the shop floor, the realized schedule is required not to deviate much from its initial version. This is because many activities besides pro- duction are planned based on the production schedule. It is important that unforeseen disruptions affect the plans for these activities as little as possible. We refer to this viewpoint as the stability perspective. Even though a considerable body of literature has emerged on hedging schedules against the negative effects of unforeseen disrup- tions in the last two decades, few studies address the problem of scheduling under uncertainty from both the robustness and the stability perspectives at the same time. The nature of the relation between robustness and stability, the trade-off between them, the circumstances under which they conflict or reconcile need to be thoroughly inves- tigated. To this end, we propose a bi-criteria approach to simultaneously investigate the robustness and stability of production schedules. We consider proactive schedul- ing in a single machine environment with random processing times. We use the total expected flow time and the total variance of job completion times as the robustness and stability measures, respectively. The proposed o-constraint variants are exact methods to generate the set of all Pareto-optimal schedules. We also develop an algorithm to generate a flxed number (set by the decision-maker) of near-Pareto-optimal schedules to deflne the characteristics and the shape of the trade-off curve without generating the entire Pareto set. Our computational experiments indicate that the proposed algorithms are efflcient.
Cognitive Radio Networks for Smart Grid Communications Potential Applications, Protocols, and Research Challenges
(CRC PRESS-TAYLOR & FRANCIS GROUP6000 BROKEN SOUND PARKWAY NW, STE 300, BOCA RATON, FL 33487-2742 USA, 2016) Kogias, Dimitris; Tuna, Gurkan; Gungor, Vehbi Cagri; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Gungor, Vehbi Cagri
Cognitive Radio Networks for Smart Grid Communications Potential Applications, Protocols, and Research Challenges
Communications Technologies for Smart Grid Applications: A Review of Advances and Challenges
(IGI Global, 2022) Tuna, Gurkan; Daş, Resul; Gungor, Vehbi Cagri; 0000-0003-0803-8372; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Gungor, Vehbi Cagri
Smart grid is a modern power grid infrastructure for improved efficiency, reliability, and safety, with smooth integration of renewable and alternative energy sources, through automated control and modern communications technologies. The smart grid offers several advantages over traditional power grids such as reduced operational costs and opening new markets to utility providers, direct communication with customer premises through advanced metering infrastructure, self-healing in case of power drops or outage, providing security against several types of attacks, and preserving power quality by increasing link quality. Typically, a heterogeneous set of networking technologies is found in the smart grid. In this chapter, smart grid communications technologies along with their advantages and disadvantages are explained. Moreover, research challenges and open research issues are provided.
Deep Learning Based Formation Control of Drones
(Springer Science and Business Media Deutschland GmbH, 2021) Kabore, Kader M.; Güler, Samet; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Güler, Samet
Robot swarms can accomplish demanding missions fast, efficiently, and accurately. For a robust operation, robot swarms need to be equipped with reliable localization algorithms. Usually, the global positioning system (GPS) and motion capture cameras are employed to provide robot swarms with absolute position data with high precision. However, such infrastructures make the robots dependent on certain areas and hence reduce robustness. Thus, robots should have onboard localization capabilities to demonstrate a swarm behavior in challenging scenarios such as GPS-denied environments. Motivated by the need for a reliable onboard localization framework for robot swarms, we present a distance and vision-based localization algorithm integrated into a distributed formation control framework for three-drone systems. The proposed approach is established upon the bearing angles and the relative distances between the pairs of drones in a cyclic formation where each drone follows its coleader. We equip each drone with a monocular camera sensor and derive the bearing angle between a drone and its coleader with the recently developed deep learning algorithms. The onboard measurements are then relayed back to the formation control algorithm in which every drone computes its control action in its own frame based on its neighbors only, forming a completely distributed architecture. The proposed approach enables three-drone systems to perform in coordination indepen- dent of any external infrastructure. We validate the performance of our approach in a realistic simulation environment. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Developing New Empirical Formulae for the Resilient Modulus of Fine-Grained Subgrade Soils Using a Large Long-Term Pavement Performance Dataset and Artificial Neural Network Approach
(SAGE Publications Ltd, 2022) Fedakar, Halil Ibrahim; 0000-0002-7561-5363; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Fedakar, Halil Ibrahim
Artificial neural network (ANN) has been successfully used for developing prediction models for resilient modulus (Mr). However, no reliable Mr formula derived from these models has been proposed in previous studies, although engineers/ researchers need empirical formulae for hand calculation of Mr. Therefore, this study aimed to propose reliable empirical formulae for the Mr of fine-grained soils using ANN. For this purpose, thousands of ANN models were developed using the long-term pavement performance (LTPP) and external datasets. The input parameters were the percentage of soil particles passing through #200 sieve (P200), silt percentage (SP), clay percentage (CP), liquid limit (LL), plasticity index (PI), maximum dry density ([rdry]max), optimum moisture content (wopt), confining pressure (sc), and nominal maximum axial stress (sz). The ANN models were compared with several constitutive models. The results indicate that the constitutive models failed to predict the Mr, and the best Mr predictions were obtained by the ANN-C9 (P200, SP, CP, LL, PI, sc, and sz), ANN-C10 (P200, SP, CP, [rdry]max, wopt, sc, and sz), and ANN-C11 (P200, SP, CP, LL, PI, [rdry]max, wopt, sc, and sz) models. Thus, the structures of these ANN models were formulated and proposed as the new empirical formulae for the Mr of fine-grained soils. Sensitivity analysis was also performed on these ANN models. It was determined that (rdry)max is the most influential parameter in the ANN-C10 model, and LL is the most influential parameter in the ANN-C9 and ANN-C11 models. On the other hand, sc and sz are the least influential parameters.
Dietary fibers
(SPRINGER LINK, 2021) Dragan, Simona Ruxanda; Damian, Georgiana; Pah, Ana Maria; Hayta, Mehmet; Kahraman, Kevser; 0000-0002-2786-3944; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Kahraman, Kevser
Dietary fibers have become increasingly popular in recent years with various applications in the food and pharmaceutical industry industries. Dietary fibers are plant-based foods which are incompletely digested by digestive enzymes. The water-soluble fibers are prebiotics, which are fermented in the colon and have a beneficial role for gut microbiota. The insoluble fibers are not affected by digestive systems and provide bulking. Fiber intake has various benefits: it reduces appetite, lowers variance in blood sugar levels, reduces the risk of cardiovascular disease, lowers the risk of diabetes, balances intestinal pH, alle¬viates constipation, and facilitates regular defecation.
The Digitized Shoulder: From Preoperative Planning to Patient-Specific Guides
(SPRINGER LINK, 2022) Sadeghi, Majid Mohammad; Kapicioglu, Mehmet; Kececi, Emin Faruk; Bilsel, Kerem; 0000-0001-8561-6960; AGÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümü; Kececi, Emin Faruk
As the information and computer technologies improve, it can change how the shoulder surgeries and treatments are done. Digitalization of the shoulder joint acquired via MR and CT (1) shows the surgeons the pathology in a more easily understandable way, (2) generates models for preoperative planning, and (3) uses special software to generate patient-specific instruments. Digitalization of the shoulder will make the shoulder disorder’s treatment easier and more accurate in the future.
Effluent treatment in denim and jeans manufacture
(ELSEVIER, 2015) Uzal, Nigmet; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Nigmet
This chapter discusses the major strategies that should be considered in the treatment of denim dyeing and jeans processing wastewater. It first gives an overview of wastewater characteristics and further elaborates on the different techniques currently available for treating wastewater. There follow the strategies to be adopted for water reuse and the recovery of dyes and chemicals. Also emphasised is the utilisation of novel technologies that provide waste minimisation, recovery and reuse opportunities and pollution prevention, instead of end of pipe approaches for treating this highly polluted wastewater.
Energy harvesting and battery technologies for powering wireless sensor networks
(ELSEVIER, 2016) Tuna, Gürkan; Güngör, Vehbi Çağrı; 0000-0003-0803-8372; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Güngör, Vehbi Çağrı
Due to the advances in wireless sensor networks (WSNs), factory and plant process automation systems are being reinvented. WSN-based industrial applications often cost much less than wired networks in both the short and long terms; automation engineers are empowering existing solutions with the new capabilities of WSNs. On the other hand, since industrial wireless sensor networks (IWSNs) consist of thousands of nodes, the problem of powering the nodes is critical. Power to the nodes is usually provided through primary batteries and this necessitates replacement when the batteries are depleted. However, the replacement may not be cost-effective or even feasible in most industrial applications.Though advancements in integrated circuit technologies help in saving more energy by leading to lower energy consumption levels, they do not eliminate the use of battery power. In this regard, energy harvesting technologies play a key role in extending the battery lifetime of the nodes. Wireless sensor nodes within industrial plants can operate from energy harvested from available energy sources such as heat, mechanical motion or vibration, indoor lighting, electromagnetic fields, and air flow. In this chapter, a review of existing energy storage technologies and various energy-harvesting techniques is given. The chapter then discusses open research issues in these topics.
Estimation of Protease Activity by Use of the Mixolab
(ELSEVIER, 2013) Kahraman, Kevser; Koksel, H.; 0000-0002-2786-3944; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Kahraman, Kevser
It is known that the preharvest attack on wheat by some heteropterous insects (Eurygaster spp., Aelia spp., and Nysius huttoni) reduces the breadmaking quality of the resulting wheat flour (Lorenz and Meredith 1988, Swallow and Every 1991, Harriri et al 2000). The problem is quite common in Mediterranean, Middle Eastern, and East European countries. Before harvest, these insects inject their salivary secretions into maturing wheat ears when they feed. Following attack by the insect, the grain matures normally, but a light-colored opaque patch surrounds the site where the insect pierced the grain. The penetration point is visible as a small dark spot in the middle of this patch. The damaged area is softer and usually collapses when pressed by a fingernail. The secretions contain proteases that break down the gluten structure during mixing and fermentation (Kretovich 1944; Every et al 1998; Sivri et al 1998, 1999).
GREEN SUPPLIER SELECTION BY USING FUZZY TOPSIS METHOD
(WORLD SCIENTIFIC PUBL CO PTE LTDPO BOX 128 FARRER RD, SINGAPORE 9128, SINGAPORE, 2016) Dogan, Ahmet; Soylemez, Ismet; Ozcan, Ugur; 0000-0002-8253-9389; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Soylemez, Ismet
With the increased environmental consciousness in customers, organizations took upon the task of redesigning their strategic goals in a more environment-sensitive way in order to fulfill their social obligations, to enable sustainability, to gain competitive advantage and to make the world more habitable. Because, the emerging conditions in the 21st century indicate that the traditional criteria - such as price, cost so on for supply chain management, supplier selection and performance measurement of suppliers are no more sufficient and there is the necessity of adding new criteria such as environmental matters. This paper deals with the problem of selecting green suppliers in an organization in Turkey that has operations in the field of accumulator. The aim is to select the greenest of 3 suppliers in Turkey, France and Bulgaria which supply the organization with the plastic material used in the production of accumulator. The problem is solved via fuzzy TOPSIS, which is a multi-criteria decision making method (MCDM), and the results are used to select the greenest supplier.
Integrating Gene Ontology Based Grouping and Ranking into the Machine Learning Algorithm for Gene Expression Data Analysis
(SPRINGER INTERNATIONAL PUBLISHING AGGEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND, 2021) Yousef, Malik; Sayici, Ahmet; Bakir-Gungor, Burcu; AGÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü; Sayici, Ahmet; Bakir-Gungor, Burcu
Recent advances in the high throughput technologies resulted in the production of large gene expression data sets for several phenotypes. Via comparing the gene expression levels under different conditions, such as disease vs. control, treated vs. not treated, drug A vs. drug B, etc., one could identify biomarkers. As opposed to traditional gene selection approaches, integrative gene selection approaches incorporate domain knowledge from external biological resources during gene selection, which improves interpretability and predictive performance. In this respect, Gene Ontology provides cellular component, molecular function and biological process terms for the products of each gene. In this study, we present Gene Ontology based feature selection approach for gene expression data analysis. In our approach, we used the ontology information as grouping (term) information and embedded this information into a machine learning algorithm for selecting the most significant groups (terms) of ontology. Those groups are used to build the machine learning model in order to perform the classification task. The output of the tool is a significant ontology group for the task of 2-class classification applied on the gene expression data. This knowledge allows the researcher to perform more advanced gene expression analyses. We tested our approach on 8 different gene expression datasets. In our experiments, we observed that the tool successfully found the significant Ontology terms that would be used as a classification model. We believe that our tool will help the geneticists to identify affected genes in transcriptomic data and this information could enable the design of platforms to assist diagnosis, to assess patients' prognoses, and to create patient treatment plans.
Leaching of Turkish Oxidized Pb–Zn Flotation Tailings by Inorganic and Organic Acids
(Springer, 2020) Kaya M.; Kursunoglu S.; Hussaini S.; Gul E.; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü
n eco-friendly approach and simultaneous recovery of metals from mine tailings is still a significant challenge. This study investigates the extraction of zinc metal from the Kayseri region oxidized lead-zinc (Pb–Zn) flotation tailings by leaching using three different inorganic acids (HNO3, HCl, and H2SO4) and six different organic acids (citric (CA), oxalic (OA), formic (FA), ascorbic (AA), malic (MA), and tartaric (TA) acids). The effects of acid type and concentration, leaching temperature and time, and solid/liquid (S/L) ratio were studied for maximum Zn dissolution and minimum Pb, Fe, and As co-dissolution at lowest temperature and leaching time. For inorganic acids at 1/10 S/L ratio, 1.0 M H2SO4 and HCl concentrations achieved 92% Zn + 0% Pb + 12% Fe at 40 °C leaching temperature and 60 min leaching time and 92% Zn + 10% Pb + 0% Fe at 80 °C leaching temperature and 30 min leaching time, respectively. For organic acids, at 1/10 S/L ratio and 1.0 M concentration, 92% Zn + 8.3% Pb with malic acid at 80 °C leaching temperature and 180 min leaching time and 91% Zn + 12% Pb with citric acid at 60 °C leaching temperature and 180 min leaching time were achieved. 1.0 M formic acid dissolved about 83% Zn + 2.8% Pb at 80 °C and 180 min leaching time. More than 90% Zn dissolution can be succeeded by using either inorganic acids at 40 °C for 30–60 min leaching time or organic acids at 60–80 °C for 180 min leaching time. Oxalic acid significantly dissolved Fe and As without Zn and Pb dissolution. © 2020, The Minerals, Metals & Materials Society.
Lead Blast Furnace Dust Recycling
(SPRINGER LINK, 2023) Top, Soner; Altiner, Mahmut; Kurşunoğlu, Sait; 0000-0003-3486-4184; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Top, Soner
The recycling of lead (Pb), which has a limited reserve in the world, has great importance in terms of sustainable and efficient use of resources. Currently, more than half of the lead, which is the softest of base heavy metals, is recovered by recycling. In addition to the insulation of the cables and its use as a radiation shield, lead is mostly used in the manufacture of lead-acid batteries (LABs). Generally, lead smelting flue dust, also known as lead smelting fly ashes, formed during the smelting stage in secondary Pb production is fed back into the smelter. However, the impurities contained in this dust and the other required specifications for feeding into the furnace prevent dust from being fed back into the furnaces. Therefore, it is essential to evaluate these by-products with an effective process and to obtain valuable content from them. In this chapter, firstly the characterization of lead smelting flue dust has been investigated. Afterwards, the processes that can be applied to obtain contents such as Pb, Sb, Zn, and As from these materials were compiled from the literature and a comprehensive review study was presented.
Modeling of suspended sediment concentration carried in natural streams using fuzzy genetic approach
(SPRINGER LINK, 2014) Kisi, Ozgur; Fedakar, Halil Ibrahim; 0000-0002-7561-5363; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Fedakar, Halil Ibrahim
This chapter proposes fuzzy genetic approach so as to predict suspended sediment concentration (SSC) carried in natural rivers for a given stream cross section. Fuzzy genetic models are improved by combining two methods, fuzzy logic and genetic algorithms. The accuracy of fuzzy genetic models was compared with those of the adaptive network-based fuzzy inference system, multilayer perceptrons, and sediment rating curve models. The daily streamflow and suspended sediment data belonging to two stations, Muddy Creek near Vaughn (Station No: 06088300) and Muddy Creek at Vaughn (Station No: 06088500), operated by the US Geological Survey were used as case studies. The root mean square errors and determination coefficient statistics were used for evaluating the accuracy of the models. The comparison results revealed that the fuzzy genetic approach performed better than the other models in the estimation of the SSC.
Paper-based substrates for sustainable (opto)electronic devices
(ELSEVIER, 2022) Usta, Hakan; Facchetti, Antonio; 0000-0002-0618-1979; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Usta, Hakan
Cellulose-based paper has been a convenient eco-friendly platform for storing and exchanging information for thousands of years. Amazingly, the studies and advancements in the past decade have demonstrated that paper and nanocellulose-based substrates are also attractive for fabricating flexible electronic circuits as well as optoelectronic components and devices. Paper and nanocellulose-based substrates have been considered for use in new generation green devices and optoelectronic applications based on their sustainable and inexpensive source, lightweight, and superior mechanical/optical properties, all factors that could also reduce manufacturing costs for producing these devices. In this chapter, we review functional materials and optoelectronic devices fabricated on paper or nanocellulose-based substrates including transistors and circuits, solar cells, light-emitting diodes, and other devices, such as sensors/actuators, batteries, supercapacitors/energy-harvesters, and breathalyzer/diagnosis devices. We also thoroughly discuss remaining challenges and promising research directions with paper-based substrates for future advancements in green optoelectronics.
Polymeric and Small-Molecule Semiconductors for Organic Field-Effect Transistors
(Wliey Online Library, 2015) Usta, Hakan; Facchetti, Antonio; 0000-0002-0618-1979; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Usta, Hakan
This chapter reviews the achievements in the development of molecular and polymeric semiconductors for charge transport in thin-film transistors (TFTs). In particular, it introduces the basic concepts of organic semiconductor structure and organic thin-film transistor (OTFT) operation and then focuses on initial studies and works. Organic semiconductors for OTFTs must possess two essential structural features for their successful implementation in printed electronics. The first feature is a π-conjugated core/chain composed of linked unsaturated units. The second feature is core functionalization with solubilizing substituents, which is essential for inexpensive manufacture by solution methods as well as for enhancing solid-state core interactions. There are several advantages in using polymeric versus molecular p-conjugated semiconductors. Isoindigo has become a popular conjugated moiety in polymer semiconductor design because of its strong electron-withdrawing character. Polymeric p-channel TFTs have reached new heights, with hole mobilities unthinkable only few years back and surpassing 10 cm2V-1 s-1.
Potential Effects of Short-Range Order on Hydrogen Embrittlement of Stable Austenitic Steels—A Review
(Springer Science and Business Media Deutschland GmbH, 2021) Koyama, Motomichi; Bal, Burak; Canadinc, Dermican; Habib, Kishan; Tsuchiyama, Toshihiro; Tsuzaki, Kaneaki; Akiyama, Eiji; AGÜ, Mühendislik Fakültesi, Makine Mühendisliği Bölümü; Bal, Burak
Here, we present a review of the hydrogen embrittlement behavior of face-centered cubic (FCC) alloys with short-range order (SRO) of solute atoms. In this paper, three types of FCC alloys are introduced: Fe–Mn–C austenitic steels, high-nitrogen steels, and CoCrFeMnNi high-entropy alloys. The Fe–Mn–C austenitic steels show dynamic strain aging associated with Mn–C SRO, which causes deformation localization and acceleration of premature fracture even without hydrogen effects. The disadvantageous effect of dynamic strain aging on ductility, which is associated with the deformation localization, amplify plasticity-assisted hydrogen embrittlement. Cr–N and Co–Cr–Ni SRO effects in high-nitrogen austenitic steels and high-entropy alloys enhance the dislocation planarity, which causes stress concentration in the grain interior and near the grain boundaries. The stress concentration coupled with hydrogen effects causes quasi-cleavage and intergranular fractures. © 2020, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Properties of alkali-activated lightweight concrete
(ELSEVIER, 2021) Top, Soner; Altiner, Mahmut; Vapur, Hüseyin; 0000-0003-3486-4184; AGÜ, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü; Top, Soner
This chapter presents a brief overview of the properties of alkali-activated lightweight concrete. Nowadays, the production of lightweight concrete has great attentions due to its extraordinary advantages such as reduced mass, improved sound and thermal insulation properties. Furthermore, the low gas emissions and the utilization of waste materials increase the importance of alkali-activated lightweight concrete. In this chapter, the strengths of lightweight concrete were examined by considering the aggregate type and density, the alkali activator type and concentration, the type of fiber reinforcements and foaming agents, which are the factors that have the most impact on the strengths. Thermal conductivity, fire resistance, acoustic performance, and durability properties have been explained considering the key points in the literature. In addition to porosity, it has been determined that one of the most important factors directly affecting the fire resistance is the precursor type. It has been concluded that the fire resistance of the concrete prepared by using K-based precursors is higher. Acoustic performances of alkali-activated lightweight concrete vary. It is necessary to use a high amount of aggregate in order to obtain concretes with wide frequency ranges and high absorption coefficient. Contrary to concrete produced from Portland cement, alkali-activated concrete is more resistant to acid and sulfate attacks, since the formation of gypsum and strength is less.

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