- JanaGanaMana

Articles2

doi:10.1007/s12355-022-01214-3

Activated Carbon from Sugarcane Bagasse Pyrolysis for Heavy Metals Adsorption

2023-06-01

Sugar Tech

0974-0740

12355

10.1007/s12355-022-01214-3

619 , 3 , 25

http://dx.doi.org/10.1007/s12355-022-01214-3

AbstractSugarcane bagasse is an agro-industrial waste available in enormous quantities in Egypt. It is rich of organic carbon which makes it a potential feedstock for activated carbon production. This study provides an optimized pyrolysis method for activated carbon production from Sugarcane bagasse. Sugarcane bagasse samples impregnated with sulfuric acid, for 24 h, and carbonized at 500 °C, for two hours, yielded the best activated carbon with a surface area of 431.375 m2/g. The best impregnation ratio was 2.5:1 (sulfuric acid/bagasse). The prepared activated carbon was used for adsorbing heavy metals (Pb, Cd, Mn, Cu, Cr) from Nile Tilapia reused frying oil. It could adsorb 80% of the heavy metals and particularly removed the Cd. The characteristics of the prepared activated carbon are comparable to those recommended for the commercial activated carbon. The production cost of the activated carbon using this method is about 707 $ which is cheaper than the commercial activated carbon by about 40%.

-- Kakom, S. M. Abdelmonem, N. M. Ismail, I. M. Refaat, A. A.

doi:10.1007/s40544-022-0641-6

Predicting EHL film thickness parameters by machine learning approaches

2023-06-01

Friction

2223-7704

40544

10.1007/s40544-022-0641-6

992 , 6 , 11

http://dx.doi.org/10.1007/s40544-022-0641-6

AbstractNon-dimensional similarity groups and analytically solvable proximity equations can be used to estimate integral fluid film parameters of elastohydrodynamically lubricated (EHL) contacts. In this contribution, we demonstrate that machine learning (ML) and artificial intelligence (AI) approaches (support vector machines, Gaussian process regressions, and artificial neural networks) can predict relevant film parameters more efficiently and with higher accuracy and flexibility compared to sophisticated EHL simulations and analytically solvable proximity equations, respectively. For this purpose, we use data from EHL simulations based upon the full-system finite element (FE) solution and a Latin hypercube sampling. We verify that the original input data are required to train ML approaches to achieve coefficients of determination above 0.99. It is revealed that the architecture of artificial neural networks (neurons per layer and number of hidden layers) and activation functions influence the prediction accuracy. The impact of the number of training data is exemplified, and recommendations for a minimum database size are given. We ultimately demonstrate that artificial neural networks can predict the locally-resolved film thickness values over the contact domain 25-times faster than FE-based EHL simulations (R2 values above 0.999). We assume that this will boost the use of ML approaches to predict EHL parameters and traction losses in multibody system dynamics simulations.

-- Marian, Max Mursak, Jonas Bartz, Marcel Profito, Francisco J. Rosenkranz, Andreas Wartzack, Sandro

doi:10.1007/s40544-022-0635-4

Astonishingly distinct lubricity difference between the ionic liquid modified carbon nanoparticles grafted by anion and cation moieties

2023-06-01

Friction

2223-7704

40544

10.1007/s40544-022-0635-4

949 , 6 , 11

http://dx.doi.org/10.1007/s40544-022-0635-4

AbstractThe astonishingly distinct lubricity difference between the ionic liquid modified carbon nanoparticles grafted by anion and cation moieties (A-g-CNPs and C-g-CNPs) was well established as additives of polyethylene glycol (PEG200). The peripheral anion moieties and positively charged inner parts of C-g-CNPs could successively absorb onto the friction interfaces by electrostatic interactions to form the organic—inorganic electric double layer structures, tremendously boosting the lubricity of PEG200. Contrarily, the preferentially electrostatic adsorption of negatively charged inner parts but repulsion of the peripheral cation moieties determined the weak embedded stability of A-g-CNPs between the friction interfaces, even impairing the lubricity of PEG200. This work can offer solidly experimental and theoretical guidance for designing and developing the high-performance nanoadditives modified by ionic molecules.

-- Wang, Baogang Yao, Linping Dai, Shanshan Lu, Hongsheng

doi:10.1007/s11721-022-00218-9

Wildfire detection in large-scale environments using force-based control for swarms of UAVs

2023-06-01

Swarm Intelligence

1935-3820

11721

10.1007/s11721-022-00218-9

89 , 1-2 , 17

http://dx.doi.org/10.1007/s11721-022-00218-9

AbstractWildfires affect countries worldwide as global warming increases the probability of their appearance. Monitoring vast areas of forests can be challenging due to the lack of resources and information. Additionally, early detection of wildfires can be beneficial for their mitigation. To this end, we explore in simulation the use of swarms of uncrewed aerial vehicles (UAVs) with long autonomy that can cover large areas the size of California to detect early stage wildfires. Four decentralised control algorithms are tested: (1) random walking, (2) dispersion, (3) pheromone avoidance and (4) dynamic space partition. The first three adaptations are known from literature, whereas the last one is newly developed. The algorithms are tested with swarms of different sizes to test the spatial coverage of the system in 24 h of simulation time. Best results are achieved using a version of the dynamic space partition algorithm (DSP) which can detect 82% of the fires using only 20 UAVs. When the swarm consists of 40 or more aircraft 100% coverage can also be achieved. Further tests of DSP show robustness when agents fail and when new fires are generated in the area.

-- Tzoumas, Georgios Pitonakova, Lenka Salinas, Lucio Scales, Charles Richardson, Thomas Hauert, Sabine

doi:10.1007/s11721-023-00223-6

Cross-disciplinary approaches for designing intelligent swarms of drones

2023-06-01

Swarm Intelligence

1935-3820

11721

10.1007/s11721-023-00223-6

1 , 1-2 , 17

http://dx.doi.org/10.1007/s11721-023-00223-6

-- Croon, G. C. H. E. Hönig, W. Theraulaz, G. Vásárhelyi, G.

doi:10.1007/s40544-022-0639-0

The mechanisms and applications of friction energy dissipation

2023-06-01

Friction

2223-7704

40544

10.1007/s40544-022-0639-0

839 , 6 , 11

http://dx.doi.org/10.1007/s40544-022-0639-0

AbstractAbout 30% of the world’s primary energy consumption is in friction. The economic losses caused by friction energy dissipation and wear account for about 2%–7% of its gross domestic product (GDP) for different countries every year. The key to reducing energy consumption is to control the way of energy dissipation in the friction process. However, due to many various factors affecting friction and the lack of efficient detection methods, the energy dissipation mechanism in friction is still a challenging problem. Here, we firstly introduce the classical microscopic mechanism of friction energy dissipation, including phonon dissipation, electron dissipation, and non-contact friction energy dissipation. Then, we attempt to summarize the ultrafast friction energy dissipation and introduce the high-resolution friction energy dissipation detection system, since the origin of friction energy dissipation is essentially related to the ultrafast dynamics of excited electrons and phonons. Finally, the application of friction energy dissipation in representative high-end equipment is discussed, and the potential economic saving is predicted.

-- Liu, Huan Yang, Boming Wang, Chong Han, Yishu Liu, Dameng

doi:10.1007/s11721-022-00214-z

Noise-resistant and scalable collective preference learning via ranked voting in swarm robotics

2023-06-01

Swarm Intelligence

1935-3820

11721

10.1007/s11721-022-00214-z

5 , 1-2 , 17

http://dx.doi.org/10.1007/s11721-022-00214-z

AbstractSwarm robotics studies how to use large groups of cooperating robots to perform designated tasks. Given the need for scalability, individual members of the swarm usually have only limited sensory capabilities, which can be unreliable in noisy situations. One way to address this shortcoming is via collective decision-making, and utilizing peer-to-peer local interactions to enhance the behavioral performances of the whole swarm of intelligent agents. In this paper, we address a collective preference learning scenario, where agents seek to rank a series of given sites according to a preference order. We have proposed and tested a novel ranked voting-based strategy to perform the designated task. We use two variants of a belief fusion-based strategy as benchmarks. We compare the considered algorithms in terms of accuracy and precision of decisions as well as the convergence time. We have tested the considered algorithms in various noise levels, evidence rates, and swarm sizes. We have concluded that the proposed ranked voting approach is significantly cheaper and more accurate, at the cost of less precision and longer convergence time. It is especially advantageous compared to the benchmark when facing high noise or large swarm size.

-- Shan, Qihao Mostaghim, Sanaz

doi:10.1007/s41095-022-0296-2

Bin-scanning: Segmentation of X-ray CT volume of binned parts using Morse skeleton graph of distance transform

2023-06-01

Computational Visual Media

2096-0662

41095

10.1007/s41095-022-0296-2

319 , 2 , 9

http://dx.doi.org/10.1007/s41095-022-0296-2

AbstractX-ray CT scanners, due to the transmissive nature of X-rays, have enabled the non-destructive evaluation of industrial products, even inside their bodies. In light of its effectiveness, this study introduces a new approach to accelerate the inspection of many mechanical parts with the same shape in a bin. The input to this problem is a volumetric image (i.e., CT volume) of many parts obtained by a single CT scan. We need to segment the parts in the volume to inspect each of them; however, random postures and dense contacts of the parts prohibit part segmentation using traditional template matching. To address this problem, we convert both the scanned volumetric images of the template and the binned parts to simpler graph structures and solve a subgraph matching problem to segment the parts. We perform a distance transform to convert the CT volume into a distance field. Then, we construct a graph based on Morse theory, in which graph nodes are located at the extremum points of the distance field. The experimental evaluation demonstrates that our fully automatic approach can detect target parts appropriately, even for a heap of 50 parts. Moreover, the overall computation can be performed in approximately 30 min for a large CT volume of approximately 2000×2000×1000 voxels.

-- Yamauchi, Yuta Yatagawa, Tatsuya Ohtake, Yutaka Suzuki, Hiromasa

doi:10.1007/s42064-022-0149-x

Adaptive connected hierarchical optimization algorithm for minimum energy spacecraft attitude maneuver path planning

2023-06-01

Astrodynamics

2522-0098

42064

10.1007/s42064-022-0149-x

197 , 2 , 7

http://dx.doi.org/10.1007/s42064-022-0149-x

AbstractSpace object observation requirements and the avoidance of specific attitudes produce pointing constraints that increase the complexity of the attitude maneuver path-planning problem. To deal with this issue, a feasible attitude trajectory generation method is proposed that utilizes a multiresolution technique and local attitude node adjustment to obtain sufficient time and quaternion nodes to satisfy the pointing constraints. These nodes are further used to calculate the continuous attitude trajectory based on quaternion polynomial interpolation and the inverse dynamics method. Then, the characteristic parameters of these nodes are extracted to transform the path-planning problem into a parameter optimization problem aimed at minimizing energy consumption. This problem is solved by an improved hierarchical optimization algorithm, in which an adaptive parameter-tuning mechanism is introduced to improve the performance of the original algorithm. A numerical simulation is performed, and the results confirm the feasibility and effectiveness of the proposed method.

-- He, Hanqing Shi, Peng Zhao, Yushan

doi:10.1007/s11721-022-00215-y

A field-based computing approach to sensing-driven clustering in robot swarms

2023-06-01

Swarm Intelligence

1935-3820

11721

10.1007/s11721-022-00215-y

27 , 1-2 , 17

http://dx.doi.org/10.1007/s11721-022-00215-y

AbstractSwarm intelligence leverages collective behaviours emerging from interaction and activity of several “simple” agents to solve problems in various environments. One problem of interest in large swarms featuring a variety of sub-goals is swarm clustering, where the individuals of a swarm are assigned or choose to belong to zero or more groups, also called clusters. In this work, we address the sensing-based swarm clustering problem, where clusters are defined based on both the values sensed from the environment and the spatial distribution of the values and the agents. Moreover, we address it in a setting characterised by decentralisation of computation and interaction, and dynamicity of values and mobility of agents. For the solution, we propose to use the field-based computing paradigm, where computation and interaction are expressed in terms of a functional manipulation of fields, distributed and evolving data structures mapping each individual of the system to values over time. We devise a solution to sensing-based swarm clustering leveraging multiple concurrent field computations with limited domain and evaluate the approach experimentally by means of simulations, showing that the programmed swarms form clusters that well reflect the underlying environmental phenomena dynamics.

-- Aguzzi, Gianluca Audrito, Giorgio Casadei, Roberto Damiani, Ferruccio Torta, Gianluca Viroli, Mirko

doi:10.1007/s42107-022-00555-4

Deaggregation of seismic hazard for Amaravati capital region in Peninsular India

2023-06-01

Asian Journal of Civil Engineering

2522-011X

42107

10.1007/s42107-022-00555-4

1077 , 4 , 24

http://dx.doi.org/10.1007/s42107-022-00555-4

AbstractThis paper presents the deaggregation of seismic hazard analysis for the Amaravati region of Andhra Pradesh, characterized by moderate seismicity in Peninsular India. The past few major earthquakes in the Peninsular Indian region have attracted many researchers to conduct a micro-level seismic hazard analysis. After the bifurcation of Telangana state from Andhra Pradesh in 2014, Amaravati and adjoining localities have been proposed as new capital to the residual state of Andhra Pradesh. Because of the significance of capital, the present study i.e., deaggregation of seismic hazard of the Amaravati region has been carried out. In this study, the complete analysis was carried out in three stages. First, an updated earthquake catalog has been prepared from a radial distance of 500 km keeping Velgapudi as the center. The seismic hazard parameters were estimated considering the earthquake data after declustering. In the second stage of the study, the probabilistic seismic hazard analysis of the Amaravati region has been carried out considering four potential seismic source zones and using the attenuation relation proposed by the national disaster authority of India (2010). The seismic hazard curves representing the cumulative seismic hazard and the uniform hazard spectra subjected to bedrock conditions of the Amaravati region have been developed. The peak horizontal acceleration and spectral acceleration were estimated up to a maximum spectral period of 2.0 s. In the final stage of the study, the seismic hazard results are further deaggregated to understand the relative ground motion of the earthquake sources in terms of magnitude and hypocentral distance. The deaggregation of seismic hazard is shown for 10%, 5%, and 2% probabilities of exceedance in 50 years corresponding to bedrock conditions. Finally, the obtained results were compared with the latest version of IS: 1893 part-1: 2016 (Criteria for earthquake-resistant design of structures), and noticed that the selected study region was being overestimated. The outcomes of this study could significantly help to generate or scale the acceleration time histories for site-specific ground response analysis, insurance agencies for policy-making, and builders for designing the new structures and retrofitting existing structures.

-- Reddy, M. Madhusudhan Rao, Ch. Hanumantha Reddy, K. Rajasekhara Kumar, G. Kalyan

doi:10.1007/s12355-022-01192-6

Highly Efficient Utilization of Sugar in Molasses for Butyric Acid Production by Clostridium tyrobutyricum

2023-06-01

Sugar Tech

0974-0740

12355

10.1007/s12355-022-01192-6

580 , 3 , 25

http://dx.doi.org/10.1007/s12355-022-01192-6

AbstractMolasses, a sugar industry waste product with low cost and high sugar content, can be used as a high-quality carbon source for microbial fermentation. In this study, molasses was pretreated by means of acid–base treatment combined with 0.6% mass fraction of activated carbon in order for its sugar concentration (78.42 g/L) and composition to meet the needs of Clostridium tyrobutyricum fermentation. C. tyrobutyricum was able to produce butyric acid from the sugars of treated molasses by microbial adaptive laboratory evolution. After 120 h of shake flask fermentation, high-performance liquid chromatography and gas chromatography showed that 46.39% of fructose and 32.56% of glucose in molasses after treatment were converted to 31.52 g/L butyric acid by C. tyrobutyricum. The results showed that the two-step process, combined with microbial adaptive laboratory evolution technology used to hydrolyze and reuse sugar, is an adapted method for the utilization of molasses, a by-product of the sugarcane industry.

-- Wang, Bing Zhou, Xiang Ren, Jun-Le Zhang, Miao-Miao Wu, Qing-Feng Yuan, Shan Liu, Wei Lu, Dong

doi:10.1007/s42064-022-0154-0

Natural coupled orbit—attitude periodic motions in the perturbed-CRTBP including radiated primary and oblate secondary

2023-06-01

Astrodynamics

2522-0098

42064

10.1007/s42064-022-0154-0

229 , 2 , 7

http://dx.doi.org/10.1007/s42064-022-0154-0

AbstractThis study investigated periodic coupled orbit—attitude motions within the perturbed circular restricted three-body problem (P-CRTBP) concerning the perturbations of a radiated massive primary and an oblate secondary. The radiated massive primary was the Sun, and each planet in the solar system could be considered an oblate secondary. Because the problem has no closed-form solution, numerical methods were employed. Nevertheless, the general response of the problem could be non-periodic or periodic, which is significantly depended on the initial conditions of the orbit-attitude states. Therefore, the simultaneous orbit and attitude initial states correction (SOAISC) algorithm was introduced to achieve precise initial conditions. On the other side, the conventional initial guess vector was essential as the input of the correction algorithm and increased the probability of reaching more precise initial conditions. Thus, a new practical approach was developed in the form of an orbital correction algorithm to obtain the initial conditions for the periodic orbit of the P-CRTBP. This new proposed algorithm may be distinguished from previously presented orbital correction algorithms by its ability to propagate the P-CRTBP family orbits around the Lagrangian points using only one of the periodic orbits of the unperturbed CRTBP (U-CRTBP). In addition, the Poincaré map and Floquet theory search methods were used to recognize the various initial guesses for attitude parameters. Each of these search methods was able to identify different initial guesses for attitude states. Moreover, as a new innovation, these search methods were applied as a powerful tool to select the appropriate inertia ratio for a satellite to deliver periodic responses from the coupled model. Adding the mentioned perturbations to the U-CRTBP could lead to the more accurate modeling of the examination environment and a better understanding of a spacecraft’s natural motion. A comparison between the orbit-attitude natural motions in the unperturbed and perturbed models was also conducted to show this claim.

-- Bakhtiari, Majid Abbasali, Ehsan Sabzy, Siavash Kosari, Amirreza

doi:10.1007/s11721-022-00216-x

Drone flocking optimization using NSGA-II and principal component analysis

2023-06-01

Swarm Intelligence

1935-3820

11721

10.1007/s11721-022-00216-x

63 , 1-2 , 17

http://dx.doi.org/10.1007/s11721-022-00216-x

AbstractIndividual agents in natural systems like flocks of birds or schools of fish display a remarkable ability to coordinate and communicate in local groups and execute a variety of tasks efficiently. Emulating such natural systems into drone swarms to solve problems in defense, agriculture, industrial automation, and humanitarian relief is an emerging technology. However, flocking of aerial robots while maintaining multiple objectives, like collision avoidance, high speed etc., is still a challenge. This paper proposes optimized flocking of drones in a confined environment with multiple conflicting objectives. The considered objectives are collision avoidance (with each other and the wall), speed, correlation, and communication (connected and disconnected agents). Principal Component Analysis (PCA) is applied for dimensionality reduction and understanding of the collective dynamics of the swarm. The control model is characterized by 12 parameters which are then optimized using a multi-objective solver (NSGA-II). The obtained results are reported and compared with that of the CMA-ES algorithm. The study is particularly useful as the proposed optimizer outputs a Pareto Front representing different types of swarms that can be applied to different scenarios in the real world.

-- Bansal, Jagdish Chand Sethi, Nikhil Anicho, Ogbonnaya Nagar, Atulya

doi:10.1007/s42064-022-0152-2

Review of space relative navigation based on angles-only measurements

2023-06-01

Astrodynamics

2522-0098

42064

10.1007/s42064-022-0152-2

131 , 2 , 7

http://dx.doi.org/10.1007/s42064-022-0152-2

AbstractRelative navigation is a key enabling technology for space missions such as on-orbit servicing and space situational awareness. Given that there are several special advantages of space relative navigation using angles-only measurements from passive optical sensors, angles-only relative navigation is considered as one of the best potential approaches in the field of space relative navigation. However, angles-only relative navigation is well-known for its range observability problem. To overcome this observability problem, many studies have been conducted over the past decades. In this study, we present a comprehensive review of state-of-the-art space relative navigation based on angles-only measurements. The emphasis is on the observability problem and solutions to angles-only relative navigation, where the review of the solutions is categorized into four classes based on the intrinsic principle: complicated dynamics approach, multi-line of sight (multi-LOS) approach, sensor offset center-of-mass approach, and orbit maneuver approach. Then, the flight demonstration results of angles-only relative navigation in the two projects are briefly reviewed. Finally, conclusions of this study and recommendations for further research are presented.

-- Gong, Baichun Wang, Sha Li, Shuang Li, Xianqiang

doi:10.1007/s42064-022-0148-y

Feasibility analysis of angles-only navigation algorithm with multisensor data fusion for spacecraft noncooperative rendezvous

2023-06-01

Astrodynamics

2522-0098

42064

10.1007/s42064-022-0148-y

179 , 2 , 7

http://dx.doi.org/10.1007/s42064-022-0148-y

AbstractRelative navigation is crucial for spacecraft noncooperative rendezvous, and angles-only navigation using visible and infrared cameras provides a feasible solution. Herein, an angles-only navigation algorithm with multisensor data fusion is proposed to derive the relative motion states between two noncooperative spacecraft. First, the design model of the proposed algorithm is introduced, including the derivation of the state propagation and measurement equations. Subsequently, models for the sensor and actuator are introduced, and the effects of various factors on the sensors and actuators are considered. The square-root unscented Kalman filter is used to design the angles-only navigation filtering scheme. Additionally, the Clohessy—Wiltshire terminal guidance algorithm is introduced to obtain the theoretical relative motion trajectories during the rendezvous operations of two noncooperative spacecraft. Finally, the effectiveness of the proposed angles-only navigation algorithm is verified using a semi-physical simulation platform. The results prove that an optical navigation camera combined with average accelerometers and occasional orbital maneuvers is feasible for spacecraft noncooperative rendezvous using angles-only navigation.

-- Du, Ronghua Liao, Wenhe Zhang, Xiang

doi:10.1007/s42064-022-0150-4

Application of homotopy perturbation method to the radial thrust problem

2023-06-01

Astrodynamics

2522-0098

42064

10.1007/s42064-022-0150-4

251 , 2 , 7

http://dx.doi.org/10.1007/s42064-022-0150-4

AbstractThe dynamics of a spacecraft propelled by a continuous radial thrust resembles that of a nonlinear oscillator. This is analyzed in this work with a novel method that combines the definition of a suitable homotopy with a classical perturbation approach, in which the low thrust is assumed to be a perturbation of the nominal Keplerian motion. The homotopy perturbation method provides the analytical (approximate) solution of the dynamical equations in polar form to estimate the corresponding spacecraft propelled trajectory with a short computational time. The accuracy of the analytical results was tested in an orbital-targeting mission scenario.

-- Niccolai, Lorenzo Quarta, Alessandro A. Mengali, Giovanni

doi:10.1007/s41095-022-0283-7

Polygonal finite element-based content-aware image warping

2023-06-01

Computational Visual Media

2096-0662

41095

10.1007/s41095-022-0283-7

367 , 2 , 9

http://dx.doi.org/10.1007/s41095-022-0283-7

AbstractMesh-based image warping techniques typically represent image deformation using linear functions on triangular meshes or bilinear functions on rectangular meshes. This enables simple and efficient implementation, but in turn, restricts the representation capability of the deformation, often leading to unsatisfactory warping results. We present a novel, flexible polygonal finite element (poly-FEM) method for content-aware image warping. Image deformation is represented by high-order poly-FEMs on a content-aware polygonal mesh with a cell distribution adapted to saliency information in the source image. This allows highly adaptive meshes and smoother warping with fewer degrees of freedom, thus significantly extending the flexibility and capability of the warping representation. Benefiting from the continuous formulation of image deformation, our poly-FEM warping method is able to compute the optimal image deformation by minimizing existing or even newly designed warping energies consisting of penalty terms for specific transformations. We demonstrate the versatility of the proposed poly-FEM warping method in representing different deformations and its superiority by comparing it to other existing state-of-the-art methods.

-- Cao, Juan Zhang, Xiaoyi Huang, Jiannan Zhang, Yongjie Jessica

doi:10.1007/s42107-022-00548-3

A study on the near and far-field earthquake response of a low and mid-rise building resting on soft soil considering soil–structure interaction (SSI)

2023-06-01

Asian Journal of Civil Engineering

2522-011X

42107

10.1007/s42107-022-00548-3

919 , 4 , 24

http://dx.doi.org/10.1007/s42107-022-00548-3

AbstractIn this paper, the seismic performance of a low and mid-rise moment-resisting steel frame has been studied, including three and nine stories buildings with a mat foundation on soft soil, under the near and far-field earthquake effects through two-dimensional modeling using the FDM. The frames mentioned above were analyzed under fixed-base (no SSI) and flexible-base (considering SSI) conditions. Results show that the near-field earthquake imposed more critical responses than the far-field earthquake, indicating the importance of investigating near-filed earthquakes. In addition, it is observed that soil–structure interaction (SSI) increases stress and amplitude compared to a fixed base.

-- Golafshani, Sajjad Akhtarpour, Ali Ghaemi Rad, Hoda Khosravi, Sajjad

doi:10.1007/s42107-022-00557-2

GA-based hybrid ANN optimization approach for the prediction of compressive strength of high-volume fly ash concrete mixes

2023-06-01

Asian Journal of Civil Engineering

2522-011X

42107

10.1007/s42107-022-00557-2

1115 , 4 , 24

http://dx.doi.org/10.1007/s42107-022-00557-2

AbstractThe present study employs the artificial neural network (ANN) analysis to predict concrete strength containing different fly ash percentages. Based on the parameters such as water-to-binder ratio (w/b), coarse aggregate to the total aggregate ratio (CA/TA), and fly ash content, a Genetic Algorithm (GA) based hybrid ANN optimization model has also been devised. These variables were chosen to effectuate the best fly ash concrete mix in the feasible compressive strength range. A total of 64 concrete mixes were taken by considering the above parameters for strength determination, optimization, and verification through the ANN model. The data obtained experimentally was trained to propose ANN model to determine the strength of concrete for various combinations of w/b, CA/TA, and fly ash content. The data was carefully assessed and analyzed to provide a statistically significant model that may be used to predict the strength of fly ash concrete. The actual values are compared to the ANN-predicted strengths. The measured compressive strength values are quite similar to those derived using the suggested model. Thus, it can be inferred that the model based on ANN analysis is an effective method for predicting the compressive strength of fly ash concrete.

-- Hashmi, A. Fuzail Ayaz, M. Bilal, A. Shariq, M. Baqi, A.