Geometric Design Research Articles

A coupled plasma-thermal model for hollow cathode power decomposition and parametric analysis

Abstract A 2D axisymmetric transient coupled plasma-thermal model is developed to simulate the plasma behavior during the self-sustained discharge of hollow cathodes, which presents a complete hollow cathode structure and energy transfer processes in multiphysics fields. The model has been validated by quantitative agreement between the simulation results and experimental data on the plasma and emitter temperature at the NSTAR cathode. The effects of thermal protection design, operating conditions, and geometric design on the cathode performance are analysed through electric and thermal power decomposition. The parametric analysis shows that the optimal thermal protection design is to use a 1/3 thickness cathode tube with 4 layers of radiation shielding close to the tube, which reduces 43.7% conductive and 61.1% radiative heat dissipation, respectively. Increasing the inlet flow rate counter-intuitively reduces the emitter temperature due to the potential reversal in the diffusion electric field dominated region, revealing that the flow rate can be traded for the dual optimisation of lifetime and power consumption. Under high current conditions, the IAT effect dominates the plume resistance to increase the discharge voltage after an inflexion point, which is the main factor limiting the cathode performance. A large internal radius gives a uniform low emission and helps to prolong life, while the orifice length should be avoided to be longer than 4 times the orifice radius due to the significantly enhanced Joule heating in the narrow orifice. The orifice radius determines the power deposition due to electron and ion bombardment through potential penetration. For high-current discharger cathodes dominated by electron bombardment, large or through-orifice designs are preferred, while for low-current neutralizer cathodes dominated by electron bombardment, small-orifice designs are recommended.

Impact of microelectrode geometry and surface finish on enzymatic biosensor performance

Food production, environmental protection, biotechnology, and medicine, all depend on biosensors for measuring specific biological molecules. Among biosensors, enzymatic electrochemical biosensors have received particular attention due to their simple operation and enzymes’ inherent specificity. Researchers have extensively explored novel materials and biological designs to improve performance (i.e., sensitivity, linearity, limit of detection, and response time). However, in comparison, physical and geometrical design has not received the same attention. To this end, we compared platinum (Pt) microelectrodes with circular or fractal geometry with the same surface area (2D geometry). We also studied the effect of 3D geometry by nanostructuring both circular and fractal microelectrodes via electroplating Pt black. Fractal Pt black microelectrodes displayed the highest current density, charge storage capacity, and sensitivity towards H2O2. Next, we immobilized glucose oxidase onto various microelectrode geometries by microcontact stamping. Fractal Pt and Pt black glucose biosensors were 91.7% and 83.3% more sensitive than circular counterparts. Circular and fractal Pt black glucose biosensors were 63.0% and 55.9% more sensitive than Pt counterparts. Fractal geometry also provided better linearity and limit of detection. We modified enzyme layer thickness through multiple layer stamping and found a trade-off whereby increasing thickness increased sensitivity but also increased response time. Lastly, we developed a COMSOL Multiphysics numerical model to interpret the amperometric data and the impact of physical design on critical parameters. The work here will serve as a guideline for improving enzymatic electrochemical and other biosensors via physical design, which is simpler to modify than material or biological design.

Road Geometric Redesign used AutoCAD 2D A Case Jalan Majalengka-Rajagaluh

Majalengka-Rajagaluh road is a road located in several sub-districts which is a link to the city and also one of the connecting roads to Cirebon City. This design planning starts in Cigasong sub-district and continues to Rajagaluh sub-district with the length of Majalengka-Rajagaluh road is 5.3 kilometers. The geometric design results are visualized in the form of drawings using AutoCAD 2D. The design speed (Vd) was set at 60 km/h with a horizontal curve radius of 358 m, a maximum slope of 4%, and an elevation (e max) of 8%. Based on these design criteria, a spiral curve with a circular curve length (Lc) of 74.996 m was obtained. Furthermore, the results of the vertical alignment calculation of the length (L) of one type of convex curve in PPV were also calculated.

Designing tungsten armoured plasma facing components to pulsed heat loads in magnetic fusion machines

A possible design rule for preventing surface damage from thermal transients to solid tungsten armour is proposed and formulated for the plasma facing components (divertor, first wall) of magnetic fusion machines. The rule is based on combined results from laboratory experiments and operating fusion machines, and fundamental engineering principles such as the heat flux factor (FHF) and fatigue usage fraction (FUF). As an example, the rule would allow 2.104 transient heat loads cycles at a FHF of 10MJm-2s-½ before the lifetime is considered exhausted. The formulation of the rule using engineering principles allows combining loads of different magnitudes and various number of cycles. A practical example of the rule usage is provided, illustrating loads combination and how the rule may contribute to the component geometrical design. The proposed rule is only valid for surface loading conditions, hence is not usable for volumetric loading conditions such as runaway electrons. Setting a budget lifetime and a design rule does not preclude actual plasma operation beyond the design lifetime. It is actually normal that experimental devices explore a larger domain than the one defined at the time of the design.

Simulation model for electrical and agricultural productivity of an olive hedgerow Agrivoltaic system

Given the need to promote a more sustainable energy model that contributes to the fight against Climate Change and the consequent advancement of photovoltaics, Agrivoltaics is presented as a solution to the conflict over land use, since it makes it possible to reconcile agricultural production and photovoltaic power simultaneously on the same piece of land. However, it is a new production model and there are still many aspects to research. This work presents a mathematical model to simulate the spatial distribution of the solar radiation in the canopy of the crop of an agrivoltaic plant in which N-S solar trackers are alternately combined with olive groves in hedgerows. In this way, simulation has the advantage of predicting the expected behaviour of one or more configurations of agrivoltaic installations and, on the basis of this simulated behaviour, making decisions during the design phase to optimize their performance. To do this, various models have been integrated to simulate both the behaviour of irradiance on its way from the Sun to the crop, using geometric-vector analysis, and the irradiance absorption processes on its way through the canopy of the crop. Thus, the global model presented allows estimating the electrical and oil production of an agrivoltaic plant such as the one described. From this global model, electrical and oil productions have been systematically simulated for a set of agrivoltaic plants whose design parameters range around the intermediate values of an agrivoltaic facility with olive groves in hedgerows spaced 10 m apart and alternated with 3 m wide and 3 m hight N-S solar trackers. For this intermediate facility, the annual productions of oil and electricity are 789kg/year·ha and 891MWh/year·ha, respectively. Finally, the oil and energy productions of all the simulated agrivoltaic facilities and their design parameters have been interrelated obtaining mathematical equations to determine in a simple way the influence on the productions of the geometrical design variables of the agrivoltaic installation (height of the solar trackers, width of the collectors and distance between hedgerows). Therefore, the model presented makes it possible to advance in the evaluation of the possible integration of olive groves in agrivoltaic systems and their profitability, constituting an important benefit for the implementation of agrivoltaics in the Mediterranean regions where olive groves play a significant role in agricultural production systems.

Design of a new scintillator-based fast ion loss detector on the HL-2A tokamak

A new scintillator-based fast ion loss detector (FILD) has been devised for the HL-2A tokamak, with the objective of discerning the temporal evolution of energy and pitch angle among lost fast ions. A code named FILD Simulation (FSC) has been developed to assist in the design of the detector head and the interpretation of experimental data. By optimising the geometric design, the resolutions of energy and pitch angle are optimised to 5 keV and 3°, respectively. A branched imaging fiber bundle is used to relay the fluorescence image on the scintillator to two distinct instruments. One of these is a high-speed camera, while the other is a silicon photomultiplier tube (SiPM) array with a sampling rate of up to 1 MSamples/s. This configuration enables the attainment of superior temporal and spatial resolution, as well as high photon sensitivity.

An automatic generation approach of process model based on feature knowledge and geometric modeling

Traditional process planning applies knowledge to convert design information within the part model into process information. This information is then displayed by manually drawing two-dimensional (2D) process cards from multiple views, illustrating the geometric design and the process details. However, this method has revealed several issues, including poor efficiency, information misinterpretation, and the potential for manual drawing errors. This traditional approach hampers the integration of manufacturing information across engineering software. It exacerbates the digital divide between computer-aided design (CAD), computer-aided process planning (CAPP), and computer-aided manufacturing (CAM). To address these issues, this study proposes an automated approach for creating three-dimensional (3D) process models based on feature knowledge and geometric modeling. The 3-axis milling features are recognized as the machining objects from the boundary representation (B-Rep) part model. Geometric and parameter knowledge for modeling is derived from the machining step. In the proposed approach, two geometric modeling methods are investigated to construct feature state volumes (FSVs). The first method utilizes FSV modeling to simulate the shape of unmachined features before rough machining, while the second method utilizes FSV modeling to construct the shape of machined features before finishing machining. The case studies illustrate that the proposed approach can construct FSVs for various machining states and autonomously generate process models. In digital manufacturing, this approach assists process planners in intuitively evaluating the reasonableness of process routes. Additionally, it provides the essential driving geometry required for the autonomous generation of tool paths.

Redesign of Heat Transfer Pipes in Radiators, Air-Conditioners and Refrigerators for Higher Efficiency

Heat transfer is a surface phenomenon. Instead of straight hollow rectangular cross section tubes with heat transfer liquid passing through it, a triangular cross section tubes having the tip of the triangle facing front to receive the flow of air is the proposed new geometrical design. With minimum material maximum heat transfer as a whole is the aim of the new Radiator design.

Molecular-Scale Geometric Design: Zigzag-Structured Intrinsically Stretchable Polymer Semiconductors.

Orienting intelligence and multifunction, stretchable semiconductors are of great significance in constructing next-generation human-friendly wearable electronic devices. Nevertheless, rendering semiconducting polymers mechanical stretchability without compromising intrinsic electrical performance remains a major challenge. Combining geometry-innovated inorganic systems and structure-tailored organic semiconductors, a molecular-scale geometric design strategy is proposed to obtain high-performance intrinsically stretchable polymer semiconductors. Originating from the linear regioregular conjugated polymer and corresponding para-modified near-linear counterpart, a series of zigzag-structured semiconducting polymers are developed with diverse ortho-type and meta-type kinking units quantitatively incorporated. They showcase huge edges in realizing stretchability enhancement for conformational transition, likewise with long-range π-aggregation and short-range torsion disorder taking effect. Assisted by additional heteroatom embedment and flexible alkyl-chain attachment, mechanical stretchability and carrier mobility could afford a two-way promotion. Among zigzag-structured species, o-OC8-5% with the initial field-effect mobility up to 1.92 cm2 V-1 s-1 still delivers 1.43 and 1.37 cm2 V-1 s-1 under 100% strain with charge transport parallel and perpendicular to the stretching direction, respectively, accompanied by outstanding performance retention and cyclic stability. This molecular design strategy contributes to an in-depth exploration of prospective intrinsically stretchable semiconductors for cutting-edge electronic devices.

Differential growth and shape formation of a flower-shaped structure

Morphogenesis, which is a complex interplay of biological, chemical, and physical processes, facilitates differential growth in various biological systems, particularly in plant organs, such as petals and leaves. Although recent studies have increasingly delved into the mechanical aspects of these biological structures, there remains a lack of a comprehensive quantitative understanding of shape formation induced by differential growth in plant organs. Thus, this study addressed this gap by employing a multifaceted approach encompassing theoretical analyses and comprehensive finite element analysis of the effect of differential growth on the shape of a cylinder into a flower shape. Based on the derivation of the strain energy expressions for the axisymmetric and asymmetric configurations, the shape function of the growing flower-like structures were calculated through mathematical optimization. The findings of this study shed light on the influence of the growth function, geometric characteristics, and material properties. As the wave number increased, the final configuration tended to have smaller waves, whereas a longer cylinder buckled more easily and the thickness had a minimal effect. This study offers insights that can pave the way for innovative geometrical designs, thereby providing inspiration for applications on both micro-and macroscales, such as in the realms of self-assembly of soft robotics and flexible electronics.

In-situ monitoring of multi-physical dynamics in ceramic additive manufacturing

Ceramic additive manufacturing is an innovative technology for developing complex ceramic structures, while a direct understanding of the physical phenomena occurring in sequential layers remains challenging, affected by the material design such as the presence of inorganic particles and their contents. This study provides a direct analysis of how the ceramic particles influence fabrication behavior utilizing an in-situ monitoring system. The force profile provides immediate feedback on fractures and geometric design, with the fluctuation in force directly corresponding to specific structural characteristics and stability during the fabrication. Furthermore, the multi-physical dynamics was investigated with a unit signal based on the effect of ceramic on the rheological-curing-mechanical behavior. For example, the mechanical behavior was characterized in real-time, as shown through an intensified peak of 6.6 kPa during the manufacturing of a ceramic composite, a 5.6 times increase compared to pure resin. The monitored data quantified the geometric dynamics and the multi-physical mechanism in real-time, achieved from the data on the overall fabrication status and the unit signal analysis of continuous manufacturing. This method can improve the reliability of ceramic additive manufacturing by providing insight into how ceramics impact fabrication behavior on sequential layers in real-time.

GRNAde: A Geometric Deep Learning Pipeline for 3D RNA Inverse Design.

Fundamental to the diverse biological functions of RNA are its 3D structure and conformational flexibility, which enable single sequences to adopt a variety of distinct 3D states. Currently, computational RNA design tasks are often posed as inverse problems, where sequences are designed based on adopting a single desired secondary structure without considering 3D geometry and conformational diversity. In this tutorial, we present gRNAde, a geometric RNA design pipeline operating on sets of 3D RNA backbone structures to design sequences that explicitly account for RNA 3D structure and dynamics. gRNAde is a graph neural network that uses an SE (3) equivariant encoder-decoder framework for generating RNA sequences conditioned on backbone structures where the identities of the bases are unknown. We demonstrate the utility of gRNAde for fixed-backbone re-design of existing RNA structures of interest from the PDB, including riboswitches, aptamers, and ribozymes. gRNAde is more accurate in terms of native sequence recovery while being significantly faster compared to existing physics-based tools for 3D RNA inverse design, such as Rosetta.

Evaluation of the Implementation Status of the Nepal Rural Road Standards (NRRS) Concerning Geometrical Parameters: A Case Study of Morang District of Nepal

Maintaining the effectiveness of the transportation system is essential to economic growth. Poor road upgrading methods in many developing nations, however, are making it impossible for traffic to flow freely. Nepal developed the Nepal Rural Road Standards (NRRS) of 2055, District Transportation Master Plan (DTMP), and Municipality Transportation Master Plan (MTMP) to regulate the construction of rural road infrastructure. These guidelines provide guidelines for rural road planning, design, building, and maintenance, among other aspects. However, each geometric design has certain features, and parameter requirements depending on the region and location to be applied. This study aims to compare the geometrical features of the rural roads that have been built with the Nepal Rural Road Standards (NRRS) 2055, second revision (2071). Using a random sampling approach, six rural roads in the Morang district were selected for the data collection. To gather geometrical data, field observations and measurements were made at random chainages. This study evaluates various geometric parameters using linear and angular field measurements. Mapping conducted via smart road software ensures road geometry compliance, including aspects such as curve radius, shoulder width, gradient, sight distance, carriageway, and additional widening. The findings demonstrate that strict adherence to established standards substantially enhances road safety. Based on the results of the field observation, the geometric elements have been built according to design specifications, except for the additional widening at shoulder width and horizontal.

Performance analysis of a novel gas-liquid separator with industrial application

This paper presents a novel gas-liquid separator characterized by its distinctive geometric design, capable of handling different volume fractions and mass flow rates. The separator's performance is comprehensively assessed across various gas volume fractions, bubble sizes, and mass flow rate fluctuations. The study reveals that variations in vapor volume fraction substantially affect both separation efficiency and pressure loss. An increase in vapor volume fraction from 0.1 to 0.5 leads to a 25% reduction in separation efficiency and a 3.3-fold decrease in pressure loss. In contrast, changes in mass flow rate exert a relatively minor influence on separation efficiency. Specifically, increasing the mass flow rate from 15 to 30 kg/s results in a mere 4% decrease in separation efficiency, whereas pressure loss increases by a factor of 3.2.Additionally, a reduction in bubble size from 1000 µm to 200 µm causes a 33% increase in pressure loss and a 14% decrease in separation efficiency. The incorporation of a meshpad in this design promotes the formation of a forced vortex, thereby enhancing the separation process.

Electrochemistry of Phase-Change Materials in Thermal Energy Storage Systems: A Critical Review of Green Transitions in Built Environments

This article reviews recent research on phase-change materials (PCMs) used in thermal energy storage systems with the aim of enhancing their performance. The study explores various methods to improve heat transfer in PCMs, such as microencapsulation, infill materials, fins and nanofluids. Additionally, it evaluates techniques to boost heat transfer in latent heat thermal energy storage (LHTES) systems and investigates ways to increase thermal conductivity using porous and low-density materials. PCMs store thermal energy, making them suitable for use in solar energy systems when solar energy is not available. The need for eco-friendly alternatives to conventional heating and cooling in global construction and the significant energy consumption of buildings has driven research on this topic. As such, this study additionally examines current advancements in free cooling systems with latent heat storage to identify the key factors affecting their effectiveness. The findings show that using PCMs for overnight cooling maintains the room temperature within the comfort zone and reduces the cooling loads in various climates. Using machine learning methods, this study also compares recent advancements in the use of PCMs in various solar energy systems, including solar thermal power plants, solar air purifiers, solar water heaters and solar appliances. Results derived feature key factors crucial for the optimal selection of PCMs and the challenges associated with sustainable green transitions in built environments. HIGHLIGHTS This review provides an in-depth examination of PCM thermal energy storage systems. This study investigates the use of fillers, nanofluids, and nanoparticles for enhanced heat transfer. Analytical methods for boosting the PCM thermal conductivity are briefly outlined. Geometric design and thermal conductivity enhancement affect the Latent Heat Thermal Energy Storage (LHTES). The assessment also evaluates advanced free-cooling systems using the LHTES. PCMs help to store heat energy in solar systems and bridge supply gaps. GRAPHICAL ABSTRACT

Data-driven approach for design and optimization of rotor–stator mixers for miscible fluids with different viscosities

Rotor–stator mixers (RSMs) are essential equipment used in the food, pharmaceutical, and cosmetic industries. The performance of RSMs is conventionally analyzed using three approaches based on empirical correlations and experimental and numerical analyses. This paper introduces a new approach based on a multifidelity data-driven framework for designing and optimizing RSMs that systematically combines elements of experimental and high-resolution computational fluid dynamics (CFD) models to train a machine learning model to predict RSM performance. It was subsequently coupled to an optimization solver based on a genetic algorithm. The developed framework was applied to a small-scale RSM with variable rotor blade radius, rotor speed, stator mesh width, and mass flow rate that is operated to mix two miscible fluids with different viscosities. The RSM was optimized at two regimes of low and high viscosities to achieve the best performance in terms of shaft power and mixing indices. The results demonstrate the successful application of the developed frameworks. The optimization of the mixing of high-viscosity fluids yielded a higher improvement than that for low-viscosity fluids. A decrease in shaft power of approximately 50% was obtained for the high-viscosity fluids, whereas the mixing indices increased up to 20% by the optimization of the geometrical input design parameters. The proposed framework can be advantageous for designers and operators at the industrial scale.

A Python toolkit for integrating geographic information system into regulatory dispersion models for refined pollution modeling

AERMOD is designated as U.S. Environmental Protection Agency (EPA)'s preferred air dispersion model for refined transportation project hot-spot analyses beginning in 2020. One of the key challenges in its modeling process is spatially encoding roadway geometry, especially when simulating highways with complex geometric designs. This research proposed an open-source Python package, GTA, which enables conversion of publicly available roadway Geographic Information System (GIS) layers into defined sources, and source-based emission rates from MOtor Vehicle Emissions Simulator (MOVES) output for AERMOD modeling. The research selected a suburban area in Atlanta, and conducted a comprehensive analysis in terms of annual PM2.5 concentration results and the speed of preparing AERMOD input files for highway network modeling both manually and using software developed based on the proposed methodology. The results prove that the proposed methodology significantly expedites the AERMOD input preparation process, and facilitates convenient testing of multiple modeling configurations for multi-scenario or sensitivity analysis.

Roundabout Safety Benefits, Design Considerations and Safety Evaluation Techniques

Roundabouts are increasingly replacing conventional signalized intersections due to their potential to enhance traffic safety and operational efficiency. This paper examines and reviews the safety benefits, design considerations, and evaluation methods for roundabouts. Studies consistently show significant reductions in crashes at roundabouts relative to other at-grade intersection control systems, particularly severe injury crashes, with reductions ranging from 37% to 88%. Roundabouts reduce conflict points, lower vehicle speeds, and improve safety for both motorized and vulnerable road users. The methodology for this paper involved a comprehensive review of literature on roundabout design and safety evaluation techniques. Data from global studies were analyzed to identify key design elements such as geometric layout, signage, and pedestrian provisions, which contribute to roundabout safety. Various safety evaluation methods, including crash data analysis, traffic conflict techniques, and surrogate safety measures, were also assessed for their effectiveness in evaluating roundabout performance. Findings indicate that proper geometric design, clear signage, and the use of innovative features like right-turn bypass lanes and roundabout metering systems can enhance safety and traffic flow. Based on these findings, the paper recommends integrating these design elements, prioritizing the safety of vulnerable users, and utilizing advanced safety evaluation techniques, including simulation modelling and intelligent transportation systems (ITS) to further optimize roundabout performance.

Radial gradient characteristics formed by the interstitial space of MWCNT yarn owing to twisting

The interstitial space of a multiwalled carbon nanotube (MWCNT) yarn is key to creating electric double-layer capacitance for harvesting energy. Despite various fabrication methods for MWCNT yarns, the formation mechanism of the interstitial space inside the yarns is poorly understood. Herein, the twisting process of a cylindrical MWCNT bundle into a yarn was simulated using the mesoscale coarse-grained particle dynamics model. A larger fraction of interstitial space was observed in the sheath region of the yarn, where large-diameter MWCNTs were mainly distributed. Small-diameter MWCNTs first swirled toward the inner core during the twisting process, causing the large-diameter MWCNTs to be sparsely distributed throughout the sheath region. The proposed methodology and its results can be applied to the geometric design of twisted MWCNT bundles to maximize the fraction of the interstitial space therein.

Microbial community interactions on a chip

Multispecies microbial communities drive most ecosystems on Earth. Chemical and biological interactions within these communities can affect the survival of individual members and the entire community. However, the prohibitively high number of possible interactions within a microbial community has made the characterization of factors that influence community development challenging. Here, we report a Microbial Community Interaction (µCI) device to advance the systematic study of chemical and biological interactions within a microbial community. The µCI creates a combinatorial landscape made up of an array of triangular wells interconnected with circular wells, which each contains either a different chemical or microbial strain, generating chemical gradients and revealing biological interactions. Bacillus cereus UW85 containing green fluorescent protein provided the "target" readout in the triangular wells, and antibiotics or microorganisms in adjacent circular wells are designated the "variables." The µCI device revealed that gentamicin and vancomycin are antagonistic to each other in inhibiting the target B. cereus UW85, displaying weaker inhibitory activity when used in combination than alone. We identified three-member communities constructed with isolates from the plant rhizosphere that increased or decreased the growth of B. cereus. The µCI device enables both strain-level and community-level insight. The scalable geometric design of the µCI device enables experiments with high combinatorial efficiency, thereby providing a simple, scalable platform for systematic interrogation of three-factor interactions that influence microorganisms in solitary or community life.