Area Constraints Research Articles

Optimal power-law fluid flow in tree-like branching networks with self-similar and uniform roughness models

This study presents an analytical model for the flow of a power-law non-Newtonian fluid through a roughened tree-like branching network under volume and surface area constraints. We assume steady-state, axisymmetric, and laminar flow with non-slip boundary conditions along the network walls. We investigate and compare two different roughness models. In the first model, the roughness length scale is self-similar and aligns with the branching network pattern, while in the second model, the surface roughness length scale is uniform. We find that in the case of the self-similar roughness model, the effective conductance remains the same as that of the smooth network. However, in the case of the uniform roughness model, the effective conductance presents an overall decrease. We argue that the uniform roughness model is a more realistic one. Furthermore, the optimal effective conductance, Eopt, and the critical diameter ratio βc, are analyzed as functions of network geometry and fluid rheology. Under both volume and surface area constraints, increasing geometrical parameters such as the number of daughter branches and network generations, generally reduced Eopt, especially for shear-thickening fluids, while shear-thinning fluids were less affected. In macroscopic networks, where roughness is relatively small, the effect of roughness on Eopt is negligible; however, in microscopic networks, where roughness approaches the scale of the diameters of the smallest branches, it leads to pronounced conductance reduction. Furthermore, networks under surface area constraint show significantly lower Eopt values compared to volume-constrained systems. Moreover, we find that the uniform surface roughness model predicts scaling laws for optimal flow (at βc) that vary with all geometrical and rheological parameters. Finally, for macroscopic networks under the uniform roughness assumption, an approximation for βc was derived using linearization with respect to the roughness intensity parameter, and it was found to be in good agreement with the full model equations.

A fault tolerant CSA in QCA technology for IoT devices

According to recent research, with the ever-increasing use of Internet of Things (IoT) devices, there has arisen an ever-growing need for high-performance yet low-power circuits that can efficiently process information. Quantum-dot Cellular Automata (QCA) has emerged as a promising alternative to conventional complementary metal-oxide-semiconductor (CMOS) technology due to its great potential in digital design at nanoscale levels on account of very low power consumption and very high processing speed. However, QCA circuits are inherently prone to faults due to variations in manufacturing processes and due to the influence of environmental factors. These faults degrade the performance of a QCA circuit considerably. Hence, fault tolerance is one of the major factors of consideration while designing a QCA circuit, particularly when the application requires very reliable and continuous operation, say in an IoT system. As such, this work presents a fault tolerant Carry Skip Adder (CSA) for QCA-based circuits. The fault tolerance of basic arithmetic components of IoT nodes performing tasks corresponding to the signal processing, control, and data manipulations is enhanced in the proposed architecture. The area occupied by a fault-tolerant full-adder circuit is 0.06 μm² and a clock cycle is 0.75; its core will be used in the CSA design. It realizes fault-tolerant multiplexers (MUX) and a majority gate, which gives the same result when there is a missing or extra single-cell fault. The most astonishing characteristic of this transistor-based CSA is its 85% tolerance for different types of failures. The CSA with three layers contains 1542 quantum cells, 4.75 clock phases, and occupies an area of 4.59 μm². It is compact and efficient architecture; therefore, it is very suitable for IoT applications where the area constraint and power efficiency are the key issues. The proposed CSA will increase the robustness and reliability of QCA-based digital circuits by integrating fault tolerance into its design such that the circuitry based on QCA can keep their functionality on even in fault-prone environments.

Regularity for minimizers of a planar partitioning problem with cusps

We study the regularity of minimizers for a variant of the soap bubble cluster problem: min∑ℓ=0NcℓP(Sℓ),where cℓ>00$$\\end{document}]]>, among partitions {S0,⋯,SN,G} of R2 satisfying |G|≤δ and an area constraint on each Sℓ for 1≤ℓ≤N. If δ>00$$\\end{document}]]>, we prove that for any minimizer, each ∂Sℓ is C1,1 and consists of finitely many curves of constant curvature. Any such curve contained in ∂Sℓ∩∂Sm or ∂Sℓ∩∂G can only terminate at a point in ∂G∩∂Sℓ∩∂Sm at which G has a cusp. We also analyze a similar problem on the unit ball B with a trace constraint instead of an area constraint and obtain analogous regularity up to ∂B. Finally, in the case of equal coefficients cℓ, we completely characterize minimizers on the ball for small δ: they are perturbations of minimizers for δ=0 in which the triple junction singularities, including those possibly on ∂B, are “wetted”by G.

Dynamic mechanisms for membrane skeleton transitions.

The plasma membrane and the underlying skeleton form a protective barrier for eukaryotic cells. The molecular players forming this complex composite material constantly rearrange under mechanical stress. One of those molecules, spectrin, is ubiquitous in the membrane skeleton and linked by short actin filaments. In this work, we developed a generalized network model for the membrane skeleton integrated with myosin contractility and membrane mechanics to investigate the response of the spectrin meshwork to mechanical loading. We observed that the force generated by membrane bending is important to maintain a regular skeletal structure suggesting that the membrane is not just supported by the skeleton, but has an active contribution to the stability of the cell structure. We found that spectrin and myosin turnover are necessary for the transition between stress and rest states in the skeleton. Simulations of a fully connected network representing a whole cell show that the surface area constraint of the plasma membrane and volume restriction of the cytoplasm enhance the stability of the membrane skeleton. Furthermore, we showed that cell attachment through adhesions promotes cell shape stabilization.

Riemannian Shape Optimization of Thin Shells Using Isogeometric Analysis

ABSTRACTIn this contribution, we consider the optimal shape design of thin elastic shell structures based on a linearized shell model of Koiter's type, whose shape can be described by a surface immersed in three‐dimensional Euclidean space. We regard the set of unparametrized immersions of the surface as an infinite‐dimensional Riemannian shape space and perform optimization in this setting using the Riemannian shape gradient. Nonuniform rational basis splines (NURBS) are employed to discretize the shell and numerically solve the underlying equations that govern its mechanical behavior via isogeometric analysis. By representing NURBS patches as B‐spline patches in real projective space, NURBS weights can also be incorporated into the optimization routine. We discuss the practical implementation of the method and demonstrate our approach on the compliance minimization of a half‐cylindrical shell under static load and fixed area constraint.

Vertex-Weighted Consensus-Based Formation Control with Area Constraints and Collision Avoidance

In this paper, a consensus-based formation control strategy is presented, subject to area constraints and collision avoidance. To achieve a desired formation pattern, a control law is proposed that incorporates a vertex-tension function along with signed area constraints. The vertex-tension function provides the capabilities of collision avoidance among agents. Moreover, signed area constraints avoid local minimum stagnation and mitigate ambiguities within the formation shape. Additionally, the proposed approach can be implemented considering a group of differential-drive mobile robots in both centralized and decentralized settings. Simulation and real-world experiments are performed to validate the effectiveness of the proposed approach, where the experimental setup includes a multi-robot system composed of Turtlebot3® Waffle Pi robots.

Model decomposition method for minimizing the consumption of support structure for FFF

Fused filament fabrication (FFF) often requires additional support structures for manufacturing parts with overhanging areas, leading to substantial material and time wastage. Although several model decomposition techniques have been developed to tackle this issue, most focus solely on the constraint of overhang surface area. As a result, these techniques often struggle with parts that have intricate overhang characteristics, causing reduced printing surface accuracy and quality. This study introduces a precise method for detecting overhang regions and support-relevant overhang regions to improve the accuracy of overhang region identification and printing precision. Additionally, a model decomposition strategy leveraging genetic algorithm optimization is proposed to minimize the need for support structures, aiming for nearly support-free printing. Moreover, for intricate structures with a high topology where support structures are unavoidable, a novel projection support based on the distribution of periodic points in triangular form is developed to address this printing challenge. Experimental results demonstrate that the implementation of the algorithm outlined in this work on an FFF printer has achieved nearly support-free printing. Moreover, the proposed method for generating support structures has the potential to reduce material usage by 27 %.

Navigating the Challenges of Urbanization: A Case Study of Tokyos Developmental Issues and Strategic Solutions

Abstract: Tokyo, as a leading global metropolis, exemplifies the complex interplay between rapid urban expansion and associated challenges. This paper explores Tokyo's developmental issues since 1950, focusing on population density, land resource shortages, agricultural land decline, waste management, and disaster preparedness. Despite its status as Japans economic, cultural, and administrative center, Tokyo's limited land area and unique geographical constraints present significant hurdles. The study evaluates the city's responses to these challenges through urban planning and policy making, assessing both the effectiveness of existing solutions and areas for improvement. The paper highlights the need for a multifaceted approach involving strategic planning, innovative solutions, and collaborative efforts to enhance Tokyos resilience and sustainability. While providing valuable insights into Tokyos urbanization challenges, the study acknowledges limitations such as inconsistent data availability and the difficulty in measuring policy impacts. Future research should include comparative studies with other global megacities to identify universal and unique urbanization challenges and investigate the long-term effects of specific policies and practices on urban sustainability and quality of life.

Initialization Algorithms of a Rigid–Flexible Coupling Fluid–Structure Interaction System by Considering Length-and-Area Constraints

Rigid–flexible coupling fluid–structure interaction systems are expected to be future solutions for reducing energy lost in water. The dynamics of these systems is usually investigated via numerical simulations. However, in existing numerical works there is no accurate algorithm for the initialization of the flexible filament, which ensures both the length and area constraints, leading to inaccurate results or even severe numerical instabilities. We propose two alternative initialization algorithms, respectively, the “Trapezoidal arrangement” and the “Quartic curve arrangement”. The performances of both of these two algorithms are investigated in numerical simulations by using the immersed boundary method. The motion responses and force characteristics of the flexible filament are analyzed carefully, verifying the capability of the proposed algorithms. Specifically, “Quartic curve arrangement” is further recommended due to its good property of convergence.

A Sub-Channel Spatial Homogeneity-Based Channel Estimation Method for Underwater Optical Densely Arrayed MIMO Systems

The limited surface area and structural constraints of small underwater communication devices necessitate a dense placement of transmitting and receiving array elements in optical multiple-input multiple-output (MIMO) systems. The compact layout leads to the formation of sub-channels that exhibit notable spatial correlation and a tendency toward homogeneity. Although sub-channel spatial homogeneity (SSH) may diminish the communication capacity of MIMO systems, it provides a significant advantage by reducing the pilot overhead. In this study, we exploit the inherent SSH and the natural time-domain sparsity of channel impulse response (CIR) in the underwater optical densely arrayed MIMO (UODA-MIMO) system to propose an innovative SSH-based channel estimation (SSH-CE) method. We model the underwater optical CIR at Gbaud rates and integrate it with SSH characteristics. This approach transforms the reconstruction targets of compressive sensing (CS) from conventional CIR samples to prior CIR model parameters and the fitting residuals of the homogeneous sub-channels, reducing the pilot overhead. The simulation results of photon tracing for UODA-MIMO sub-channels in turbid harbor water indicate a monotonic, exponential decay in CIR at Gbaud rates, with transmission delays exceeding 5 nanoseconds for distances over 8 m. Moreover, the correlation coefficients among sub-channels reach a minimum of 0.975, confirming the presence of SSH in UODA-MIMO systems. In comparison to existing CS methods that rely on known sparsity, sparsity adaptation, and the structural sparsity of MIMO channels, the SSH-CE method achieves a lower degree of sparsity in reconstruction targets and a reduced lower bound for pilot requirements under the SPARK criterion. Specifically, the SSH-CE method achieves a reduction in the pilot overhead for reconstructing Nt sub-channels of K-sparse to 2Nt irrespective of CIR residual compensation.

Концептуально-онтологические аспекты множественности предка в информационных моделях «сущность-связь»

The design of information models in the development of automated systems involves constructing entity-relationship models, which define classes of entities and interclass relationships of the ancestor-descendant type, serving as a conceptual and ontological foundation for the subsequent creation of databases. This article explores aspects of representing the semantic constraints of the subject area imposed on relationships between entities in entity-relationship models. A special type of relationship between classes of entities, termed multiple ancestor (MA) relations, is highlighted, where several instances of the ancestor entity may exist for a single instance of the descendant entity. The article analyses the possible semantic constraints that arise in such cases and the anomalies they generate. Based on the introduced concepts of ascending kinship lines and the MA predicate, a formalisation of MA integrity is presented. Examples of formal MA constraints are provided, including positive (requiring the coincidence of ancestor instances), negative (requiring the mismatch of ancestor instances), and mixed. The mutual influence of several MA constraints with partially intersecting lines of ascending kinship is also examined. Finally, the feasibility of implementing MA constraints in relational database models is evaluated.

Boosting electricity generation associated with Saudi Arabi buildings using PCM and PV cells on walls and roof leading to a sustainable building

In Saudi Arabia, where the majority of regions receive a minimum incident shortwave solar energy exceeding 4 kWh/(m2. year), there is a high potential for electricity generation and simultaneously, a challenge in building cooling. In this study, by adding photovoltaic (PV) on the roof and wall, as well as using phase change material (PCM) inside the walls, electricity production and energy consumption of Saudi residential buildings were investigated. Taking into account the effects of radiation on vertical and horizontal envelopes as well as phase change in PCM, the energy equation was solved using DesignBuilder to specify hourly energy consumption and electricity generation. When installing PV cells at the optimal tilt, incoming radiation to the cells increases. However, creating shadows on subsequent rows of cells diminishes the effective PV surface area. Surprisingly, calculations revealed that if PV cells are installed at zero angle, owing to installing more PV cells, up to 31 % extra electricity is produced than when installed at the optimal tilt. As a side effect, the cooling load decreases by 5.1 % due to reduced radiation intensity on the roof. The orientation of the walls significantly impacts both phase change material (PCM) and PV-associated electricity generation. Placing PCM on the east wall optimizes its performance, while walls containing PV panels perform best when facing south. To further enhance cooling and reduce electricity demand, phase change material was incorporated into both the roof and wall, resulting in a 2 % reduction in overall electricity demand. Notably, in eight major populated areas across Saudi Arabia, under the constraint of the constant PV cell area, installing PV cells on the roof proves three times more advantageous than placing them on the walls.

Numerical optimisation of Dirac eigenvalues

Abstract Motivated by relativistic materials, we develop a numerical scheme to support existing or state new conjectures in the spectral optimisation of eigenvalues of the Dirac operator, subject to infinite-mass boundary conditions. We numerically study the optimality of the regular polygon (respectively, disk) among all polygons of a given number of sides (respectively, arbitrary sets), subject to area or perimeter constraints. We consider the three lowest positive eigenvalues and their ratios. Roughly, we find results analogous to known or expected for the Dirichlet Laplacian, except for the third eigenvalue which does not need to be minimised by the regular polygon (respectively, the disk) for all masses. In addition to the numerical results, a new, mass-dependent upper bound to the lowest eigenvalue in rectangles is proved and its extension to arbitrary quadrilaterals is conjectured.

Design Considerations for Power-Efficient Fully Integrated 3:1 Switched Capacitor DC-DC Converter for PV Modules

This article presents a power-efficient DC-DC converter based on a switched-capacitor (SC) cell in power management systems supplied for fully integrated photovoltaic (PV) modules. These modules shall provide high-performance point-of-load voltage regulation. The primary objective of this study is to better utilize capacitance and switches by selecting a proper SC topology in order to improve the power efficiency of SC converters. A general steady-state performance model is investigated to optimize and compare a variety of SC DC-DC topologies. The investigation method relies on a charge-multiplier approach and considers the impact of area constraint on capacitors. To identify the most suitable topology for a given conversion ratio, the performance-limit metrics of SC converters are calculated. The analysis provides framework to determine optimum switch size and switching frequency for a two-phase 3:1 series–parallel converter for a target load current of 10 mA implemented on a 22 nm process technology. The results shows that a minimum of 250 MHz switching frequency is desirable for achieving a target efficiency greater than 85% while maintaining the minimum output voltage of 0.34 V. The analysis results are verified through MATLAB and PSpice-based simulations.

Determination of an optimum patch configuration in the repair of a center crack in thin aluminum sheet using polymer composite patch

AbstractThe formation of cracks and their growth is an issue of concern in structural applications incorporating thin metal sheets. Adhering cracked region with a patch of composite material has proved effective in repairing cracks. Determining an optimum configuration of composite patch is still a challenge as a shorter patch may not be effective and a larger patch leads to wastage of resources. An appropriate methodology is required for specifying an optimum patch configuration in terms of its length, width, and thickness. The work presented prescribes a methodology for obtaining an appropriate combination of geometrical parameters of the composite patch. The computational tools like finite element analysis and response surface method have been incorporated. This is an extensive work consisting of a number of iterations of numerical analyses carried out for different combinations of the length and width of the patch. The results were also obtained for three different patch thicknesses in which the number of plies were increased from a single ply to three plies. The optimum size was obtained for each of the three patch thicknesses. Finally, a methodology for obtaining the most appropriate patch configuration based on the practical constraint of a small available area is prescribed.Highlights The crack repair in a thin structural sheet using fiber reinforced polymer composite patch separates at the interface. The optimum size of the patch needs to be used for an effective repair. The work consists of a combination of experiments and numerical simulations using finite element analysis. Response surface methodology is employed in this optimization study.

Enhancing precision in 3D printing for highly functional printing with high-speed vision

3D printing has revolutionized product design and manufacturing across various industries by enabling the creation of complex geometries with minimal waste. Despite its advancements, 3D printing still faces significant challenges, including spatial constraints and process control limitations. This paper introduces novel approaches to improve the functionality and precision of material extrusion 3D printers for the fused deposition modeling method, particularly for additional printing tasks such as printing on existing objects or continuing a print on a relocated object without prior knowledge of its position or even the environment is changed. We introduce a compensation system integrating a high-speed vision system for robot arms to address these challenges. Our system employs a three-step pose estimation process—fast point feature histograms (FPFH)-based, corner-based, and sub-pixel edge-based methods—to ensure high accuracy in restoring the position of printed pieces for additional printing tasks on a given object. Experimental results demonstrate substantial improvements in printing precision, with the system achieving sub-millimeter and sub-pixel accuracy. These advancements not only eliminate work area constraints but also enhance the adaptability and reliability of 3D printing processes.

A multi-objective approach to optimizing the geometry and envelope of rural dwellings for energy demand, thermal comfort, and daylight in cold regions of China: A case study of Shandong province

Rural dwellings in China’s cold regions face significant challenges related to energy consumption, thermal comfort, and daylight, with a projected substantial increase in energy demand in the future. Scientifically optimized design during the early planning stages can significantly enhance indoor thermal and daylight conditions, effectively reducing energy consumption. This study focuses on Shandong Province to comprehensively analyze the optimization of geometry and envelope design of rural dwellings in China’s cold regions. It employs a multi-objective optimization method, integrating genetic algorithms with dynamic energy simulations, to minimize total energy demand while ensuring thermal comfort and sufficient daylight. Utilizing the Octopus plugin in Grasshopper, in conjunction with EnergyPlus, Ladybug, and Honeybee, this research optimizes and analyzes the impact of various design variables on energy consumption, thermal comfort and daylight, including room depth, window-to-wall ratio in different orientations, thermal performance of the envelope, and related glass material parameters. The results indicate that the selected variables have significant energy-saving potential. Compared to the case study building, the optimized solutions can reduce total energy demand by over 62.41%, with the highest savings rate reaching 88.75%. This study emphasizes the importance of integrated design and optimization strategies in enhancing the sustainability of rural dwellings. It proposes both cost-free and cost-included optimization schemes: the former maximizes the energy-saving, thermal comfort and daylight potential of the selected variables, while the latter is more practically feasible considering the economic constraints of rural areas. The proposed optimization schemes provide multiple reference solutions and theoretical foundations for users of rural dwellings in China’s cold regions.

Hydrodynamics of multicomponent vesicles: A phase-field approach

In this paper, we introduce a thermodynamically-consistent phase-field model to investigate the hydrodynamics of inextensible multicomponent vesicles in various fluid flows with inertial forces. Our model couples the fluid field, surface concentration field representing chemical species on the membrane, and vesicle dynamics, while enforcing global area and volume constraints through a Lagrange multiplier method. Specifically, we employ full Navier–Stokes equations for the fluid field, the Cahn–Hilliard equations for the species concentration on the membrane, a nonlinear advection–diffusion equation to describe the evolution of the vesicle membrane, and an additional equation to enforce local inextensibility. We utilize a residual-based variational multiscale method for the Navier–Stokes equations and a standard Galerkin finite element framework for the remaining equations. The PDEs are solved using an implicit, monolithic scheme based on the generalized-α time integration method. We extend previous models for homogeneous vesicles (Aland et al., 2014; Valizadeh and Rabczuk, 2022) to multicomponent vesicles, introducing Cahn–Hilliard equations while maintaining thermodynamic consistency. Additionally, we employ isogeometric analysis (IGA) for higher accuracy. We present a variety of two-dimensional numerical examples, including multicomponent vesicles in shear flow and Poiseuille flow with and without obstructions, using the resistive immersed surface method to handle obstructions. Furthermore, we provide three-dimensional simulations of multicomponent vesicles in Poiseuille flow.

Minimal perception: enabling autonomy in resource-constrained robots.

The rapidly increasing capabilities of autonomous mobile robots promise to make them ubiquitous in the coming decade. These robots will continue to enhance efficiency and safety in novel applications such as disaster management, environmental monitoring, bridge inspection, and agricultural inspection. To operate autonomously without constant human intervention, even in remote or hazardous areas, robots must sense, process, and interpret environmental data using only onboard sensing and computation. This capability is made possible by advancements in perception algorithms, allowing these robots to rely primarily on their perception capabilities for navigation tasks. However, tiny robot autonomy is hindered mainly by sensors, memory, and computing due to size, area, weight, and power constraints. The bottleneck in these robots lies in the real-time perception in resource-constrained robots. To enable autonomy in robots of sizes that are less than 100 mm in body length, we draw inspiration from tiny organisms such as insects and hummingbirds, known for their sophisticated perception, navigation, and survival abilities despite their minimal sensor and neural system. This work aims to provide insights into designing a compact and efficient minimal perception framework for tiny autonomous robots from higher cognitive to lower sensor levels.

Optimization of relief hole blasting satisfying synergistic constraints of rock-breaking area and hole-bottom minimum burden

A strategy to optimize relief hole positions is proposed to enhance the effectiveness of tunnel blasting in rock breaking. This study employed two predefined arithmetic progressions to coordinate the distribution of rock-breaking areas and hole-bottom minimum burdens allocated to each row of holes. Iterative calculations were performed to determine the final position of each row of holes. To determine the optimal drilling scheme, modeling and simulation were conducted using a finite element method-smoothed particle hydrodynamics (FEM-SPH) coupling algorithm. This approach allowed for a comparison of the rock-breaking effects of relief holes under different constraint combinations. This study indicates that the displacement of rock particles varies in different depth zones. The largest displacements of the rock particles were observed in the middle of the charge section. For a conventional working face with a width of 12.2 m and a designed advance of 3 m, the rock-breaking efficiency is optimal when the two control ratios, rA and rW, are 1.5 and 1.4, respectively. This study advances the underground blasting design technology and contributes to energy reduction and efficiency improvements in blasting engineering.