Variable Cell Size Research Articles

Compression behavior of 316L diamond lattice structures fabricated via additive manufacturing with variable cell sizes

The unit size effect of 316L diamond lattice structures was systematically investigated through experiments, theory, and simulations. Experimental tests demonstrated that reducing the cell size to 5 mm and 2.5 mm enhances the load carrying capacity and energy absorption of the structures. Additionally, analytical solutions were developed to acceptably estimate the elastic modulus and yield strength of diamond lattice structures. Finite element simulations, incorporating elastic, plastic, and ductile damage models, were utilized to depict the entire deformation evolution at different strain levels. These simulations were found to be precisely consistent with experimental observations. The results confirmed a transition from non-uniform deformation to uniform large-scale plastic deformation. This transition is attributed to either locally fractured struts caused by longer struts in structures with large cell sizes or largely deformed, non-ruptured short beams in structures with smaller cell sizes. Comparisons with previous reports indicated that the current structures with a cell size of 2.5 mm exhibit outstanding mechanical performance, making them desirable candidates for engineering applications.

Large cells suppress the reproduction of Varroa destructor.

The parasitic mite, Varroa destructor has posed a threat to the health and survival of European honey bees, Apis mellifera worldwide. There is a prevailing belief that small comb cells could provide a management tool against Varroa mites. However, the hypothesis that smaller cells can impede Varroa reproduction has not been fully tested. Here, we tested this hypothesis under laboratory conditions by using two distinct Varroa in vitro rearing systems: one involved gelatin capsules of different sizes, specifically size 00 (0.95 mL) versus size 1 (0.48 mL), and the second consisted of brood comb cells drawn on 3D printed foundations with varying cell sizes, ranging from 5.0 mm to 7.0 mm at 0.5 mm intervals. The results showed that mother mites in size 00 cells had significantly lower fecundity and fertility compared to those in size 1 cells. Interestingly, the reproductive suppression in larger cells could be reversed by adding an extra worker larva. Similarly, gonopore size of mother mites was smaller in size 00 cells, but restored with another host larva. Furthermore, both the fecundity and fertility of mother mites decreased linearly with the size of brood comb cells. Our results suggest that the reproduction of V. destructor is hindered by larger cells, possibly because larger brood cells disperse or weaken host volatile chemical cues that are crucial for Varroa reproduction. The insights derived from this study are expected to hold significant implications for the implementation of Varroa management programs. © 2024 Society of Chemical Industry.

Investigation of Static Flexural Strength of Aluminium Honeycomb Panels with Varying Cell Sizes

Investigation of Static Flexural Strength of Aluminium Honeycomb Panels with Varying Cell Sizes

Chainmail inspired metamaterials for use in protective sports equipment

Contact sports and action sports require intense performance yet also include a high risk of injury. Subsequently, protective equipment for those sports usually must trade flexibility for protection and vice versa. Chainmail inspired mechanical metamaterials could be a solution to this dilemma. Chainmail is a type of body armour, consisting of a structured fabric made up of thousands of interlocking metallic rings. Chainmail inspired materials have recently been made from connected 3D shapes, rather than the typical 2D (flat) rings. This chainmail inspired material is flexible when relaxed but stiff when the chains are compressed together. This ability to control the material’s stiffness means chainmail is a type of mechanical metamaterial. Mechanical metamaterials are engineered structures which derive their properties from the structure of the material, not the material itself. In relation to protective equipment, this means that these chainmail materials or fabrics, can be flexible during normal use but stiffen when indented or impacted. The flexibility of these materials can be influenced by changing the size and shape of the connecting chains but to what extent and the effect this has on their stiffness is unknown. This type of structure could improve sporting protective equipment, where (as stated before) there are various trade-offs. The aim of this project was to develop a chainmail inspired material and test the effect of varying cell sizes has on the flexibility and indentation resistance of the material. Additive manufacturing was used to create the chainmail materials and a range of indenters were used to test them, the results of which indicate that as cell size decreases and number of cells increase; their flexibility and formability increases while also maintaining a good degree of indentation resistance, when compared to larger cell sizes. Based on this work, these structures could be tailored to different sporting protective equipment where flexibility, support, and stiffness requirements may vary between normal use and collisions or falls. These chainmail inspired materials could have various applications in contact sports such as rugby, American football and ice hockey where protection for players is key to reduce the severity of injuries. Similarly, action sports such as mountain biking, skateboarding, skiing and snowboarding also necessitate a high degree of protection. An Alternative application for these materials could be as a first aid device, where the material would be formed around the injury site as a brace and stiffened with compression, such as a vacuum pack.

Evaluating transient behaviour of large‐scale photovoltaic systems during lightning events using enhanced finite difference time domain method with variable cell size approach

Evaluating transient behaviour of large‐scale photovoltaic systems during lightning events using enhanced finite difference time domain method with variable cell size approach

Stackable and Deployable Laser‐Induced Graphene Layers Toward the Flexible Manufacturing of Smart 3D Honeycombs with Multifunctional Performance

AbstractSmart honeycombs are becoming the novel structural strategy for next‐generation devices and equipments. Unfortunately, traditional surface‐coating, structural immersing, and 3D printing approaches still face significant challenges in combining structural customization and performance multifunctionality. Herein, a brand‐new processing strategy is developed to construct graphene‐based smart honeycombs by stacking and deploying laser‐induced graphene (LIG) layers with alternatively inserted adhesives. Through tuning key parameters, various LIG‐enabled smart honeycombs (LIG‐HC) can be assembled with scalable areal dimension and thickness, variable cell sizes and shapes, as well as patternable graphene clusters. By further understanding the process‐dependent structural stability and electrical conductivity, multifunctional characteristics are systematically explored, including anisotropic mechanical, electrical, piezoresistive, and electromagnetic performance. To finally demonstrate the unique honeycomb multifunctionally applied in fields of aviation, an intelligent LIG‐HC enabled aircraft‐wing model is representatively constructed for performing anti‐/de‐icing, high‐temperature warning, flame retardancy, pressure and vibration monitoring, as well as electromagnetic shielding and stealth.

Generalizing to new geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulation

Generation of simulated detector response to collision products is crucial to data analysis in particle physics, but computationally very expensive. One subdetector, the calorimeter, dominates the computational time due to the high granularity of its cells and complexity of the interactions. Generative models can provide more rapid sample production, but currently require significant effort to optimize performance for specific detector geometries, often requiring many models to describe the varying cell sizes and arrangements, without the ability to generalize to other geometries. We develop a geometry-aware autoregressive model, which learns how the calorimeter response varies with geometry, and is capable of generating simulated responses to unseen geometries without additional training. The geometry-aware model outperforms a baseline unaware model by over 50% in several metrics such as the Wasserstein distance between the generated and the true distributions of key quantities which summarize the simulated response. A single geometry-aware model could replace the hundreds of generative models currently designed for calorimeter simulation by physicists analyzing data collected at the Large Hadron Collider. This proof-of-concept study motivates the design of a foundational model that will be a crucial tool for the study of future detectors, dramatically reducing the large upfront investment usually needed to develop generative calorimeter models.

Using cellular automata to simulate external heat and mass transfer in the wood drying process

This work involves modeling the external heat and mass transfer in the wood drying chamber. One of the remarkable features of this research is to use cellular automata with variable cell sizes closely related to the geometric parameters of the considered wood materials. This approach allows for modeling and analyzing the changes in the characteristics of wood materials during the hydrothermal treatment process, taking into account their unique geometry. Such modeling provides valuable information about how different shapes and sizes of wood react to various drying conditions. This research has significant implications for industries dependent on wood drying, such as construction and furniture production, as it offers an individual approach to upgrading the drying processes of wood materials with different geometries. The modeling in this work is carried out using wood materials, primarily pine, with a standardized thickness of 25 mm and an initial moisture content of 30 %. The modeling is conducted under conditions of moderate drying, accurately mirroring real-world scenarios. Using pine as the researched material aimed to represent a widely used wood species in the industry, thereby increasing the relevance of the results. The work also explores the influence of various parameters of the wood drying agent. To achieve this, three key factors are systematically varied: temperature, relative humidity, and drying agent velocity. Temperature fluctuations are carried out within a range of ±10 °C. Similarly, relative humidity is adjusted within ±10 % of standard technological parameters. Finally, the drying agent velocity was increased to a maximum of 6 m/s. Thus, the impact of these changes on the moisture content in wood materials is investigated. The results obtained can be applied in an industrial setting. The knowledge gained from the experiments can play a crucial role in improving the wood drying process. In summary, the work investigates the hydrothermal treatment of wood materials, shedding light on the critical role of wood drying agent parameters in controlling moisture content in wood materials. The potential advantages in terms of product quality and overall production efficiency cannot be overstated, and it is expected that this work will be a valuable resource for industries dependent on wood processing.

Methods to get more information from sparse vessel monitoring systems data

Vessel Monitoring Systems (VMS) and other vessel tracking data have been used for many years to map the distribution of fishing activities. Mapping areas with low levels of fishing activity can be of particular interest; for example to avoid conflicts between fishing and other ocean uses like offshore renewable energy or to protect relatively pristine ecosystems from increasing fishing pressure. A particular problem when trying to delineate areas that are lightly fished, is the relative sparsity of vessel monitoring data in these areas. This paper explores three novel methods for estimating the distribution of fishing activity from VMS data, with particular focus on lightly impacted areas. The first new method divides the area of interest into a nested grid with varying cell sizes (depending on the density of data at each location); the second new method uses Voronoi diagrams to define polygons around observations and the third method applies a local regression to generate a smooth map of fishing intensity. The new methods are compared with two established methods: applying spatial grids and interpolating fishing tracks. The track interpolation method generally performs better than any of the new methods, however it is not always possible or appropriate to apply track interpolation; in those cases the local regression method is the best alternative.

Перспективи застосування електрохімічного полірування зразків скеффолд, виготовлених за адитивною технологією

In recent years, the actual production of metal products directly from electronic data according to a three-dimensional model based on layer-by-layer manufacturing has evolved from rapid prototyping to additive manufacturing. As the quality of additively manufactured metal products continues to increase and their manufacturing processes improve and develop, the demand for additive manufacturing is increasing. Additive manufacturing technology, also known as 3D printing, has become increasingly popular recently. Using additive manufacturing, almost any complex geometry can be manufactured with high degree of precision. After the production of parts using the SLM technology from metal powder, post-processing is applied, in particular electrochemical polishing, the main purpose of which is to reduce surface roughness, increase the gloss of surface elements, and remove metal powder that has partially melted onto the outer surface of the product at the point of contact between the molten metal and the border of the part and the powder, which is located next to the melt. This is especially important for inclined surfaces, internal channels and cellular structures with developed outer surface. For research, samples were made using SLM technology from AISI 316L austenitic steel powder. The samples have a cube shape with a base of 10 mm, a height of 10 mm, and a thickness of 10 mm, with cell widths of 4 mm and 2 mm. The main body of both samples was printed using the same modes at a laser power of 220 W, a scanning speed of 1000 mm/s and a distance between laser passes of 0.14 mm. Samples were printed on Alfa-280 3D printer manufactured by ALT Ukraine LLC. Electropolishing was carried out in a solution of orthophosphoric acid (H3PO4) with glycerol (C3H8O3) by immersing the test samples in the electrolytic solution at a voltage of 17 V and a current density of 3 A/cm2. The control of weight and geometric parameters was carried out with the help of ADV-2000 analytical balances and MKC-25 micrometer. The electropolishing of the experimental samples took place in four stages: 1) visual - optical inspection with fixation, weight control before the start of the process; 2) electropolishing for 3 minutes, visual - optical inspection with photo fixation; weight control after 3 min. polishing process; 3) electropolishing of the same samples for another 3 minutes, visual – optical inspection with photo fixation, weight control after 6 minutes. polishing; 4) electropolishing of the same samples for another 3 minutes, visual - optical inspection with photo fixation; weight control after 9 min. electropolishing process. At each stage, a real current-voltage curve was recorded using an oscilloscope. As a result of weight control before and after the test, it was established that the samples lost approximately the same weight in the range of 6.9...7.1 % relative to the initial one. Based on the analysis of the obtained results, it was established that at a current density of 3 A/cm2 and at a voltage of 17 V, effective active uniform polishing of the surface of samples with a cellular structure of scaffold type with a variable cell size from 4 to 2 mm is realized.

Fluids transmission and thermal durability analysis of Miura-ori auxetic relief knits; the next generation wearable materials

Knitted materials with superior thermal comfort attributes and cheap production costs are primarily utilized in leisurewear. Auxetic materials having biaxial stretch capabilities increase the propensity of knitted auxetic fabrics for size-changing clothing applications, such as maternity wear and growing kids' apparel, consequently supporting the sustainable development goal of responsible material consumption. Knitted auxetic fabrics based on Miura-ori fold geometries have been engineered with typically targeted clothing fibrous assemblies/yarns (polyester, cotton, and acrylic) and assorting different knitting parameters. Diagonal relief and hybrid square relief patterns with variable structural knitted cell (SKC) size proved to be a solution towards size and shape-changing clothing materials. Fluid transmission, heat retention, and durability evaluations were undertaken to determine the efficacy towards wearability of such auxetic materials. Varying structural porosities and the number of folds per unit area created properties discrepancy, governing different Poisson’s ratios and thermal attributes. Engineered foldable geometries exhibited about 10% to 40% increase in fluids transmissions than control plain rib fabrics. Quadratic thermal resistance enhancements of above 100% were noticed for auxetic fabrics and increasing SKC size enhanced thermal insulation. Influence of studied input variables was found statistically significant; fluid transmission had a p-value<0.05 for all material, SKC, and structure factors; heat retention was also significantly affected by material and SKC variation. The SKC size expansion promoted auxeticity up to optimum size of 9×9. Corresponding associations estimation using bubble plot analysis revealed positive correlations between fluid transmissions and durability attributes; however, an increase in fluid transmission compromised the heat retention of materials.

Investigation of lattice infill parameters for additively manufactured bone fracture plates to reduce stress shielding

BackgroundStress shielding is a detrimental phenomenon caused by the stiffness mismatch between metallic bone plates and bone tissue, which can hamper fracture healing. Additively manufactured plates can decrease plate stiffness and alleviate the stress shielding effect. MethodsRectilinear lattice plates with varying cell sizes, wall thicknesses, and orientations are computationally generated. Finite element analysis is used to calculate the four-point bending stiffness and strength of the plates. The mechanical behaviors of three different lattice plates are also simulated under a simple diaphyseal fracture fixation scenario. ResultsThe study shows that with different combinations of lattice infill parameters, plates with up to 68% decrease in stiffness compared to the 100% infill plate can be created. Moreover, in the fixation simulations, the least stiff lattice plate displays 53% more average stress distribution at the healing callus region compared to the 100% infill plate. ConclusionsUsing computational techniques, it has been demonstrated that additively manufactured stiffness-reduced bone plates can successfully address stress shielding with the strategic modulation of lattice infill parameters. Lattice plates with design versatility have the potential for use in various fracture fixation scenarios.

Numerical method for compressible gas-particle flow coupling using adaptive parcel refinement (APR) method on non-uniform mesh

The Eulerian–Lagrangian (EL) approach is usually used for simulating the compressible gas-particle flows. In our previous study, we have developed the compressible multiphase particle-in-cell method (CMP-PIC) and achieved good results for both dilute and dense compressible gas-particle flow. However, the original CMP-PIC was only implemented on the uniform mesh, which limits its resolution, efficiency, and application in the field of engineering. Therefore, in the present study, we have implemented the developed algorithms for coupling terms and the adaptive parcel refinement APR method on the non-uniform mesh. The algorithm of coupling terms is a new method for interpolating between a parcel with definite volume and cells with different volumes; this has not been investigated in previous particle-in-cell (PIC) research. The improved operator of the multiphase coupling terms is put forward to adapt the wide range size ratios since directly using the original operator causes the loss of coupling effects. The APR sets up a numerical “breakup model” of a parcel from the computational perspective, which represents a new approach to a parcel-type numerical method. In the APR method, the parcel resolution can automatically match the resolution of the local Eulerian cell. Therefore, the improved CMP-PIC can handle the simulation when a large parcel enters the fine cell and prevents the abnormal termination due to non-physical packing of particles. Based on conservation and scaling laws, the strategy, split criterion, and split configuration are identified to correlate the parameters of the parent and child parcels. Additionally, the algorithms of the multiphase HLL/HLLC solvers are derived for flux and nozzling terms to adapt the Cartesian grid with varying cell sizes, which is a type of non-uniformity. Several one-dimensional and two-dimensional tests show the correctness and advantages of using the non-uniform mesh, improved operator, and APR method. Results show that the combination of improved interpolation operator and APR method can significantly improve the reliability, resolution of simulation results, and robustness of the algorithm. The simulation time is also reduced due to regional refinement.

Biomechanical behavior of diamond lattice scaffolds obtained by two different design approaches with similar porosity; a numerical investigation with FEM and CFD analysis.

Scaffolds provide a suitable environment for the bone tissue to maintain its self-healing ability and help new bone-cell formation by creating structures with similar mechanical properties to the surrounding tissue. In the modeling of the scaffolds, an optimum environment is tried to be provided by changing the geometrical properties of the cell architecture such as porosity, pore size, and specific surface area. For this purpose, different design approaches have been used in studies to change these properties. This study aims to determine whether scaffolds with similar porosities modeled by different design approaches exhibit distinct biomechanical behaviors or not. By using the Diamond lattice architecture, two different design approaches were constituted. The first approach has constant wall thickness and variable cell size, whereas the second approach contains variable wall thickness and constant cell size. The usage of different design approaches affected the amount of specific surface area in models with similar porosity. Mechanical compression tests were conducted via finite element analysis, while the permeability performance of configurations with similar porosities (50%, 60%, 70%, 80%, and 90%) was evaluated by using computational fluid dynamics. The mechanical results revealed that the structural strength decreased with increasing porosity. Since their higher specific surface area causes lower pressure drops, the second group exhibits better permeability. In addition, it was found that to evaluate the wall shear stresses occurring on the scaffold surfaces properly, it is essential to consider the stress distributions within the scaffold rather than the maximum values.

On the effects of spatial resolution on effective distance measurement in digital landscapes

BackgroundConnectivity is an important landscape attribute in ecological studies and conservation practices and is often expressed in terms of effective distance. If the cost of movement of an organism over a landscape is effectively represented by a raster surface, effective distances can be equated with the cost-weighted distance of least-cost paths. It is generally recognized that this measure is sensitive to the grid’s cell size, but little is known if it is always sensitive in the same way and to the same degree and if not, what makes it more (or less) sensitive. We conducted computational experiments with both synthetic and real landscape data, in which we generated and analyzed large samples of effective distances measured on cost surfaces of varying cell sizes derived from those data. The particular focus was on the statistical behavior of the ratio—referred to as ‘accuracy indicator’—of the effective distance measured on a lower-resolution cost surface to that measured on a higher-resolution cost surface.ResultsIn the experiment with synthetic cost surfaces, the sample values of the accuracy indicator were generally clustered around 1, but slightly greater with the absence of linear sequences (or barriers) of high-cost or inadmissible cells and smaller with the presence of such sequences. The latter tendency was more dominant, and both tendencies became more pronounced as the difference between the spatial resolutions of the associated cost surfaces increased. When two real satellite images (of different resolutions with fairly large discrepancies) were used as the basis of cost estimation, the variation of the accuracy indicator was found to be substantially large in the vicinity (1500 m) of the source but decreases quickly with an increase in distance from it.ConclusionsEffective distances measured on lower-resolution cost surfaces are generally highly correlated with—and useful predictors of—effective distances measured on higher-resolution cost surfaces. This relationship tends to be weakened when linear barriers to dispersal (e.g., roads and rivers) exist, but strengthened when moving away from sources of dispersal and/or when linear barriers (if any) are detected by other presumably more accessible and affordable sources such as vector line data. Thus, if benefits of high-resolution data are not likely to substantially outweigh their costs, the use of lower resolution data is worth considering as a cost-effective alternative in the application of least-cost path modeling to landscape connectivity analysis.

The effects of variable porosity and cell size on the thermal performance of functionally-graded foams

The thermal performance of several engineering devices, such as heat exchangers, volumetric solar receivers and thermal energy storage systems, is improved by open-cell metal or ceramic foams. Among them functionally-graded foams, through which morphological characteristics are variable, look promising. Heat transfer and pressure drop in a functionally-graded foam, with a uniform heat flux entering one of its sides, are investigated numerically in this paper. Porosity and cell size variable in the direction of the entering heat flux according to different power-law functions are considered; their maximum and minimum values are constrained at the opposite upper and lower sides of the foam. Governing equations, written with reference to a Representative Elementary Volume (REV) of the foam, are solved with a Local Thermal Non Equilibrium (LTNE) model by means of a finite element scheme; the code is validated with experimental data from the literature. The thermal performance of the foam is expressed by a Performance Evaluation Criterion (PEC), referred to the average morphological characteristics of foams with the same surface area. Nusselt numbers, friction factors and Performance Evaluation Criteria (PECs), for different power-laws, are predicted. A 38% higher PEC than in foams with uniform porosity is found in foams with variable-porosity while a 14% larger PEC is exhibited in foams with variable cell size. A 42% increase in PEC is found in foams that account for both variable porosity and cell size.

Microbial carrying capacity and carbon biomass of plastic marine debris.

Trillions of plastic debris fragments are floating at sea, presenting a substantial surface area for microbial colonization. Numerous cultivation-independent surveys have characterized plastic-associated microbial biofilms, however, quantitative studies addressing microbial carbon biomass are lacking. Our confocal laser scanning microscopy data show that early biofilm development on polyethylene, polypropylene, polystyrene, and glass substrates displayed variable cell size, abundance, and carbon biomass, whereas these parameters stabilized in mature biofilms. Unexpectedly, plastic substrates presented lower volume proportions of photosynthetic cells after 8 weeks, compared to glass. Early biofilms displayed the highest proportions of diatoms, which could influence the vertical transport of plastic debris. In total, conservative estimates suggest 2.1 × 1021 to 3.4 × 1021 cells, corresponding to about 1% of the microbial cells in the ocean surface microlayer (1.5 × 103 to 1.1 × 104 tons of carbon biomass), inhabit plastic debris globally. As an unnatural addition to sea surface waters, the large quantity of cells and biomass carried by plastic debris has the potential to impact biodiversity, autochthonous ecological functions, and biogeochemical cycles within the ocean.

Understanding the Principles of Pattern Formation Driven by Notch Signaling by Integrating Experiments and Theoretical Models.

Notch signaling is an evolutionary conserved cell-cell communication pathway. Besides regulating cell-fate decisions at an individual cell level, Notch signaling coordinates the emergent spatiotemporal patterning in a tissue through ligand-receptor interactions among transmembrane molecules of neighboring cells, as seen in embryonic development, angiogenesis, or wound healing. Due to its ubiquitous nature, Notch signaling is also implicated in several aspects of cancer progression, including tumor angiogenesis, stemness of cancer cells and cellular invasion. Here, we review experimental and computational models that help understand the operating principles of cell patterning driven by Notch signaling. First, we discuss the basic mechanisms of spatial patterning via canonical lateral inhibition and lateral induction mechanisms, including examples from angiogenesis, inner ear development and cancer metastasis. Next, we analyze additional layers of complexity in the Notch pathway, including the effect of varying cell sizes and shapes, ligand-receptor binding within the same cell, variable binding affinity of different ligand/receptor subtypes, and filopodia. Finally, we discuss some recent evidence of mechanosensitivity in the Notch pathway in driving collective epithelial cell migration and cardiovascular morphogenesis.

Enhancing effectiveness of tidal river management in southwest Bangladesh polders by improving sedimentation and shortening inundation time

Bangladesh, one of the countries most vulnerable to climate change, is threatened by sea level rise (SLR) and land subsidence. The tidal river management (TRM) practised in coastal regions of Bangladesh has the potential to raise the land by sedimentation, to counteract SLR and subsidence. TRM is an indigenous method in which dikes are breached to readmit sediment-rich water into a polder, which results in sediment being deposited in depressions in the polder called ‘beels’, while simultaneously preventing silting-up of the tidal rivers. However, after several years of continuous sedimentation from TRM, deposition has been uneven and less than expected.To study the effectiveness of TRM, this research analyses different scenarios to identify which operation schemes most effectively trap sediment to raise the land surface. The scenarios developed considered the number of inlets, flow regulation through the beel using open inlets or gated inlets with different operation schemes, and seasonality. The study area was Pakhimara Beel in southwest Bangladesh, where TRM is ongoing. To simulate the scenarios, a two-dimensional (2D) morphodynamic model with variable cell size was set up, calibrated and used. The simulation results were analysed for total sediment deposition, uniformity of spatial distribution of sediment deposition and trapping efficiency.Sediment deposition shows clear seasonal variability, with greatest deposition in the pre-monsoon period, less during monsoon and least in the dry season. Greatest deposition combined with high spatial uniformity was found for TRM that uses two inlets located at opposite sides connected to different watercourses. Regulated flow using successively opened gates resulted in highest sediment deposition in all seasons, about double that of the existing situation without gate. However, given the complexity and cost of gate operation, TRM with two inlets located at opposite sides of the beel without flow regulation may be considered more feasible, and still effective despite 20–30% less sediment deposition. To also increase acceptability by local affected stakeholders we propose to restrict this improved TRM to the monsoon period, to allow crops to be grown on the land in the dry and pre-monsoon periods, and ensure salinity is minimized. Such well-planned TRM has the potential to also counteract sea level rise in sinking deltas elsewhere in the world by enhancing sedimentation.

A vibration damping optimization algorithm for the integrated problem of cell formation, cellular scheduling, and intercellular layout

The three problems of cell formation (CF), cellular scheduling, and cellular layout are closely interrelated in the design of cellular manufacturing systems (CMSs) and should, therefore, be considered in an integrated structure. This paper presents a mixed-integer programming (MIP) model to examine such concurrent design by considering many design attributes, such as the machine duplication, alternative processing routes, reentrant parts, and variable cell size. In the presented model, decisions including machine grouping, processing route selection, operation sequencing, and cell assignment into candidate locations are taken such that the total completion time is minimized. Since the problem in hand belongs to the NP-hard class, a vibration damping optimization (VDO) algorithm is proposed to solve large-sized problems. In order to verify the efficiency of the proposed algorithm comparing to the CPLEX solver of the GAMS software and two other metaheuristic algorithms, namely a genetic algorithm (GA) and an ant lion optimizer (ALO) algorithm, several sample problems with different sizes and settings are implemented. The results demonstrate that the proposed algorithm can obtain better solutions in less computational time.