Hybridization of Chaotic Maps and Gravitational Search Algorithm for Constrained Mechanical and Civil Engineering Design Frameworks

The Chaotic Gravitational Search Algorithm (CGSA) is a physics-based heuristic algorithm inspired by Newton's law of universal gravitation. It uses 10 chaotic maps for optimal global search and fast convergence rate. The advantages of CGSA has been incorporated in various Mechanical and Civil engineering design frameworks which include Speed Reducer Design (SRD), Gear Train Design (GTD), Three Bar Truss Design (TBTD), Stepped Cantilever Beam Design (SCBD), Multiple Disc Clutch Brake Design (MDCBD), and Hydrodynamic Thrust Bearing Design (HTBD). The CGSA has been compared with eleven state of the art stochastic algorithms. In addition, a non-parametric statistical test namely the Signed Wilcoxon Rank-Sum test has been carried out at a 5% significance level to statistically validate the results. The simulation results indicate that CGSA shows efficient performance in terms of high convergence speed and minimization of the design parameter values as compared to other heuristic algorithms. The source codes are publicly available on Github i.e. https://github.com/SajadAHMAD1.

Studi Komparasi Perancangan Balok Struktural Berdasarkan SNI 2847-2002, SNI 2847-2013 Dan SNI 2847-2019

This study aims to determine the difference in structural beam design using SNI 2847-2002, SNI 2847-2013 and SNI 2847-2019 by comparing the bending and shear reinforcement in the case study of the Faculty of Health Sciences Building, University of Borneo Tarakan. The results of the comparisons include: the maximum reinforcement ratio at SNI 2847-2013 and 2019 is around 16,667% smaller than SNI 2847-2002, the flexural capacity of the beam design results from SNI 2847-2013 and 2019 increases by about 12.5% compared to SNI 2847-2002, The shear capacity of concrete (Vc) designed with SNI 2847-2013 and 2019 increased by about 2% compared to SNI 2847-2002, as well as the design shear capacity of the accumulated concrete and shear reinforcement designed by SNI 2847-2013 and 2019 increased no more than 1% compared to SNI 2847-2002.

Multi-membrane search algorithm

This research proposes a new multi-membrane search algorithm (MSA) based on cell biological behavior. Cell secretion protein behavior and cell division and fusion strategy are the main inspirations for the algorithm. In order to verify the performance of the algorithm, we used 19 benchmark functions to compare the MSA test results with MVO, GWO, MFO and ALO. The number of iterations of each algorithm on each benchmark function is 100, the population number is 10, and the running is repeated 50 times, and the average and standard deviation of the results are recorded. Tests show that the MSA is competitive in unimodal benchmark functions and multi-modal benchmark functions, and the results in composite benchmark functions are all superior to MVO, MFO, ALO, and GWO algorithms. This paper also uses MSA to solve two classic engineering problems: welded beam design and pressure vessel design. The result of welded beam design is 1.7252, and the result of pressure vessel design is 5887.7052, which is better than other comparison algorithms. Statistical experiments show that MSA is a high-performance algorithm that is competitive in unimodal and multimodal functions, and its performance in compound functions is significantly better than MVO, MFO, ALO, and GWO algorithms.

Collimated neutron beam design for TRR thermal column

Tehran Research Reactor (TRR) is the main neutron source in Iran which can be used for different applications of neutrons such as neutron radiography and neutron therapy. TRR has a thermal column which can provide high intensity flux of thermal neutrons for users. The aim of this study is to design a neutron collimator for TRR thermal column to produce parallel neutron beam with suitable intensity of thermal neutrons. To achieve this goal, Monte Carlo code of MCNX has been used to evaluate different configurations, geometries and materials of neutron collimator. The results show that the final selected configuration can provide a uniform thermal neutron beam with a flux of 1.21E+13 (cm-2·s-1) which is suitable for many different neutron applications.

Behavior of Non-Shear-Strengthened UHPC Beams under Flexural Loading: Influence of Reinforcement Depth

This study was carried out in order to study the flexural behavior of fiber-reinforced ultra-high-performance concrete (UHPC) containing hybrid microsteel straight fibers and natural fine aggregates under four-point flexural loading. The experimental results revealed that the fiber pullout mechanism had a progressive pullout (collapse) mode. A highly flexural crack developed when the fiber pulling mechanism was explicitly triggered, leading to the failure of most beams. The maximum load in beams reinforced by 1.2, 1.6, and 2.0% exceeded that in beams without longitudinal reinforcement by 56, 73, and 94%, respectively. Further, bar reinforcements at 125, 115, 95, 85, and 75 mm depths led to increases of 56, 55, 73, 96, and 94% in beam load capacity, respectively. In addition, bar reinforcement at 115, 95, 85, and 75 mm depths reduced the beams’ ductility by 40, 23, 35, and 39% compared to those with 125 mm depth. All studied UHPC beams had an uncracked phase that extended to a curvature of about 7.5 × 10−6 rad, which occurred at about 10 kNm. The use of the design of experiments was exploited in this investigation to develop a prediction model for the ultimate moment capacity of UHPC beams. This prediction model took into account the sectional and material properties of UHPC beams. To carry out this analysis, a database of 25 beams, developed by other investigators, as well as the present authors, was utilized. With a mean prediction-to-test ratio of 0.92, this prediction model had a reasonable performance capacity. In turn, this model was used to generate isoresponsive surface contours that could be used for UHPC beam design.

A comparison of mixed-variables Bayesian optimization approaches

Most real optimization problems are defined over a mixed search space where the variables are both discrete and continuous. In engineering applications, the objective function is typically calculated with a numerically costly black-box simulation. General mixed and costly optimization problems are therefore of a great practical interest, yet their resolution remains in a large part an open scientific question. In this article, costly mixed problems are approached through Gaussian processes where the discrete variables are relaxed into continuous latent variables. The continuous space is more easily harvested by classical Bayesian optimization techniques than a mixed space would. Discrete variables are recovered either subsequently to the continuous optimization, or simultaneously with an additional continuous-discrete compatibility constraint that is handled with augmented Lagrangians. Several possible implementations of such Bayesian mixed optimizers are compared. In particular, the reformulation of the problem with continuous latent variables is put in competition with searches working directly in the mixed space. Among the algorithms involving latent variables and an augmented Lagrangian, a particular attention is devoted to the Lagrange multipliers for which a local and a global estimation techniques are studied. The comparisons are based on the repeated optimization of three analytical functions and a beam design problem.

Beamline K11 DIAD: a new instrument for dual imaging and diffraction at Diamond Light Source

The Dual Imaging and Diffraction (DIAD) beamline at Diamond Light Source is a new dual-beam instrument for full-field imaging/tomography and powder diffraction. This instrument provides the user community with the capability to dynamically image 2D and 3D complex structures and perform phase identification and/or strain mapping using micro-diffraction. The aim is to enable in situ and in operando experiments that require spatially correlated results from both techniques, by providing measurements from the same specimen location quasi-simultaneously. Using an unusual optical layout, DIAD has two independent beams originating from one source that operate in the medium energy range (7–38 keV) and are combined at one sample position. Here, either radiography or tomography can be performed using monochromatic or pink beam, with a 1.4 mm × 1.2 mm field of view and a feature resolution of 1.2 µm. Micro-diffraction is possible with a variable beam size between 13 µm × 4 µm and 50 µm × 50 µm. One key functionality of the beamline is image-guided diffraction, a setup in which the micro-diffraction beam can be scanned over the complete area of the imaging field-of-view. This moving beam setup enables the collection of location-specific information about the phase composition and/or strains at any given position within the image/tomography field of view. The dual beam design allows fast switching between imaging and diffraction mode without the need of complicated and time-consuming mode switches. Real-time selection of areas of interest for diffraction measurements as well as the simultaneous collection of both imaging and diffraction data of (irreversible) in situ and in operando experiments are possible.

Shear Strengthening of Deep T-Section RC Beams with CFRP Bars

Deep T-section beams have been widely used in engineering structures due to their high bearing capacity, high construction efficiency and economic benefits, while the current beam design theory can hardly interpret reasonably the mechanical behaviors of deep beams. The performance features of the deep T-beam were investigated, involving in strain distribution and principal stress trace using experimental tests. Different near surface mounted (NSM) reinforcement schemes were proposed for deep T-beams aiming at improving the shear capacity. The results show that the behaviors of deep T-beams dissatisfy the assumption of plane cross-section, and the ‘strut-and-tie’ model is applicable in such structures. The reinforcement systems can significantly relieve the strain concentration, mid-span deflection and crack width in deep T-beams, consequently improving the shear capacity range from 45 to 65%. The scheme is preferential for the reinforcement of deep T-beams when the applied angles, positions and lengths of CFRP bars are optimized based on the ‘strut-and-tie’ model.

Advanced arithmetic optimization algorithm for solving mechanical engineering design problems

The distributive power of the arithmetic operators: multiplication, division, addition, and subtraction, gives the arithmetic optimization algorithm (AOA) its unique ability to find the global optimum for optimization problems used to test its performance. Several other mathematical operators exist with the same or better distributive properties, which can be exploited to enhance the performance of the newly proposed AOA. In this paper, we propose an improved version of the AOA called nAOA algorithm, which uses the high-density values that the natural logarithm and exponential operators can generate, to enhance the exploratory ability of the AOA. The addition and subtraction operators carry out the exploitation. The candidate solutions are initialized using the beta distribution, and the random variables and adaptations used in the algorithm have beta distribution. We test the performance of the proposed nAOA with 30 benchmark functions (20 classical and 10 composite test functions) and three engineering design benchmarks. The performance of nAOA is compared with the original AOA and nine other state-of-the-art algorithms. The nAOA shows efficient performance for the benchmark functions and was second only to GWO for the welded beam design (WBD), compression spring design (CSD), and pressure vessel design (PVD).