ANSYS Simulation Research Articles

Improved Sensitivity of MEMS-based Piezoresistive Pressure Sensor using Silicon Nitride Diaphragm

In this paper, Piezoresistive Pressure Sensor (PPS) with four Polysilicon piezoresistors on Si3N4 diaphragm with improved sensitivity is successfully designed by using MEMS technology. Sensing is accomplished via deposited polysilicon resistors like metal resistors. The analytical model of PPS is optimized for location and geometry of the piezoresistors and the sensors based on different aspect ratios (both square and rectangular) have been investigated. The performance parameters like maximum deflection, maximum induced stress on the diaphragm have been compared using ANSYS and MATLAB simulation programming based on mathematical model. By interpreting the proper selection of the geometry of a thin Si3N4 diaphragm, the maximum deflection, maximum induced stress and highest sensitivity for this sensor are obtained for the diaphragm when aspect ratio is minimum. It has been found that sensitivity of the sensor is achieved when the piezoresistors are symmetrically placed at 65 m from the edges of the diaphragm. The analysis describes that the sensor based on square diaphragm is more sensitive than the rectangular one. It is influenced more powerfully by diaphragm thickness. The applied pressure range is considered from 0.5 kPa to 40 kPa. From the simulation results, the shape and the sensor design can be optimized for a highly sensitive PPS.

A Ball-Contacting Dynamic Vibration Absorber with Adjustable Stiffness and Nonlinear Characteristics

Structural vibration has always been a major concern in the engineering field. A dynamic vibration absorber in the form of contacts with adjustable stiffness (CDVA) offers effective vibration suppression and can improve conventional dynamic vibration absorbers with high sensitivity to frequency deviation and difficulty in adjusting the frequency. In this research, first, based on the theoretical model of the contact between a rubber ball and an inner cone, the feasibility of changing the axial contact state to change the structure’s natural frequency was verified using an ANSYS simulation. A theoretical model of the static contact stiffness between the ball and the inner cone was constructed using Hertzian contact theory and Hooke’s law, and a theoretical model of the cubic nonlinear elastic restoring force was used to characterize the stiffness properties of the rubber ball during compressive rebound. The steady-state frequency response equations of the main vibration structure were derived using the averaging method in conjunction with the two-degree-of-freedom dynamics model, and the stability of the solutions to the frequency response equations was obtained in conjunction with the stability determination criterion. Then, the impact of the CDVA’s design parameters on the nonlinear dynamic response of the primary vibration structure was simulated and analyzed. The resulting findings can serve as guidance for designing dynamic vibration absorber parameters. Based on the principles of ball-inner cone contact, a dynamic vibration absorber structure was proposed. A design test was conducted to verify the correctness of the contact stiffness model, and an experimental study was carried out to investigate the law of change in the dynamic stiffness and damping of the principle structure of CDVA under dynamic excitation conditions. Finally, the vibration test platform of the solidly supported beam structure was constructed, and vibration suppression tests of the CDVA in different compression states were conducted to investigate the tunability and feasibility of CDVA vibration suppression. The results showed that the dynamic vibration absorber had good vibration absorption characteristics and could be used for single-mode vibration suppression of multimodal main structures.

Metaoptics for aberration correction in microendoscopy.

Compact and minimally invasive scanning fiber endoscopy probes with micron-level resolution have great potential in detailed tissue interrogation and early disease diagnosis, which are key applications of confocal reflectance imaging at visible wavelengths. State-of-the-art imaging probes commonly employ refractive lens triplets or gradient refractive index (GRIN) lenses as the micro-objective. However, off-axis aberration emerges as a critical factor affecting resolution, especially at the extremities of the imaging field. In response to this challenge, we propose what we believe to be a novel design integrating a metasurface with the GRIN micro-objective to address optical aberrations during beam scan. The metasurface acts as a corrector element for optical aberrations in a fiber-scanning endoscope using the same fiber for excitation and collection. Modeling such hybrid refractive-metasurface designs requires the coupling of simulation techniques across macroscale and nanoscale optics, for which we used an Ansys simulation workflow platform. Operating at a wavelength of 644 nm, this metaoptical element serves as a thin and compact aberration correction surface, ensuring uniform resolution across the entire imaging field. Experimental results from our scanning fiber endoscopy system demonstrate a notable enhancement in optical performance both on-axis and off-axis, achieving a resolution of 3 µm at the center of the imaging field. Impressively, the resolution experiences only a modest degradation by a factor of 0.13 at the edge of the field of view compared to the center.

Advancing MRI capacitors: Design, fabrication, and characterization

AbstractIn today's healthcare landscape, MRI (magnetic resonance imaging) plays a pivotal role in early diagnosis and treatment decisions. However, the quest for higher frequencies to achieve micron‐level resolutions poses technological challenges. This paper focuses on coils and capacitors, with special attention to air gap considerations for movable electrodes. The paper delves into the development of adjustable capacitors using high‐fired NP0 ceramic, tailored for 128‐MHz MRI systems. These capacitors boast impressive specs: a 3‐kV breakdown voltage (VBreakdown), a 3‐pF minimum capacitance (Cmin), a 30‐pF maximum capacitance (CMax), and a 1.5‐pF stepwise capacitance variation (Cvariation step). Notably, they enhance breakdown voltage while preserving frequency stability with MgTiCa ceramic between the fixed and mobile electrode, critical for adaptive blocks. Leveraging geometrical parameters analyzed through the ANSYS simulator, the authors meticulously designed an optimized 25–40 pF capacitor with a 15‐mm height and 1600 mm2 surface area. Post‐fabrication and sintering, extensive testing using a vector network analyzer across 10 MHz to 100 MHz validated performance against simulated expectations.

Impact of Process Technology on Properties of Large-Scale Wind Turbine Blade Composite Spar Cap

As wind turbine blade length increases, reconciling lightweight design with strength necessitates continuous advancements in process technology. The impact of three different process technologies–vacuum-assisted resin transfer moulding (VARTM), prepreg, and pultrusion–on the properties of wind turbine blade composite spar caps was investigated using scanning electron microscopy, dynamic mechanical analysis, differential scanning calorimetry, thermogravimetric analysis, and static and fatigue testing. The results demonstrated that the fibre weight content and 0° tensile modulus of the VARTM and pultrusion composites increased as compared to those of the prepreg samples. Subsequently, the properties of a 94-m blade were analysed using the Ansys Composite PrepPost (ACP) and static structure modules in Ansys simulations, and the weights of the spar cap were compared with test data of materials under different process technologies. The results showed that the masses of the spar cap of a 94-m blade in the pultrusion, VARTM, and prepreg processes were 7965, 9170, and 9942 kg, respectively. The quantitative influence rules on the weight of the wind turbine blade spar cap prepared through different process technologies were formulated. The findings of this study are promising and are expected to aid the development of wind turbine blade process technologies.

A global centralized magnetic flux leakage small defect detection network

Abstract To solve the problem that magnetic-flux-leakage (MFL) small defects are difficult to accurately detect by machine learning methods, a global centralized magnetic flux leakage small defect detection network (RCFPNet) is proposed. RCFPNet consists of simulation data enhancement, improved feature extraction (backbone), an improved centralized feature pyramid (CFP) and a detection head network. The MFL defect data of various scales and shapes are simulated by ANSYS simulation software and superimposed with the actual detected MFL defects to expand the dataset. The Repvgg module is used to replace the 3*3 convolution of the backbone to improve the detection speed. An improved spatially explicit vision center scheme (EVC) and a global centralized regulation rule (GCR) for feature fusion networks are proposed for feature fusion networks. RCFPNet is based on an improvement of the YOLOv5 network. Experiments have proven that RCFPNet has improved detection speed and accuracy and has achieved good results in the detection of magnetic leakage small defects. Experiments show that when the IOU = 0.5, the accuracy rate of this algorithm is 96.1%, and the reasoning time is 8.9 ms.

A study of the vibrations of a rotor bearing suspended by a hybrid spring system of shape memory alloys

Abstract The study of rotor-bearing vibration is crucial across various fields, encompassing applications such as rotating machinery, wind turbines, washing machines, and elevators. However, operational challenges can arise from these machines’ propensity to vibrate under specific conditions. To address this issue, the current research investigates the utilization of shape memory alloy (SMA) springs as intelligent materials in the rotor suspension system. SMA’s unique property of changing stiffness with temperature-induced phase shifts is harnessed, leading to the construction of a test rig for validating vibration characteristics. A novel hybrid bearing is devised to effectively manage vibrations, particularly in resonance zones. To the authors’ knowledge, this new model is never reported in the literature. Then, an accelerometer is employed to measure the rotor shaft response corresponding to disc position vibration signals. Furthermore, a numerical model is developed to validate experimental results, taking into account the phase change of SMA springs and the disc’s influence on the rotor bearing’s natural frequency. Temperature variations from 20 to 80°C resulted in a 13% change in natural frequency for the hybrid spring configuration. The experimental findings align closely with ANSYS simulations, displaying an acceptable error ratio, with the highest error remaining within 20% thresholds.

Implementation of additive-manufactured hydroforming die for thin metal bellow production – a stride towards additive manufacturing in rapid tooling approach

ABSTRACT The hydroforming die was designed based on the required operating conditions. The Fused Deposition Modeling process, Acrylonitrile Butadiene Styrene material, and sparse mode style were used for the fabrication. The first attempt at using the hydroforming die to create SS316 bellow (0.3 mm thickness x 2 ply) failed due to excessive pressure concentration at the convolution region. The die was redesigned to enhance overhanging convolution imprints and reduce their length to 50% of the original design, followed by an ANSYS simulation to identify critical failure regions. The second trial of the hydroforming die for producing SS316 bellow (0.2 mm thickness x 1 ply) was successful in a brief run. However, the formed metal bellow displayed an increased convolution width, attributed to the reduced convolution imprint length in the redesigned die. The stress analysis indicated maximum Von Mises stress at the convolution imprint and minimum stress at the die’s outer boundary. The sparse mode die showed 18.104% lower material consumption and 16.225% shorter build time than the solid mode, with a porosity difference of 30.668%. A 6.66%-dimensional error occurred due to oversizing in the topmost convolute, suggesting a 30% reduction in convolution imprint length to mitigate this error in future designs.

Tailoring flow straighteners’ architectures through additive manufacturing to enhance power performance and scale-up microbial fuel cell technology

In an aim to scale up the microbial fuel cell (MFC), this research is a first attempt to investigate the impact of two lattice structures flow straighteners: gyroid and X lattice to compare with the conventional honeycomb flow straightener, fabricated via additive manufacturing. The study focused on assessing their effect on the degradation of domestic wastewater and power generation in a dual chamber recirculation MFC. Other than the geometry, structures were also tested at flow rates of 20 mL/min, 60 mL/min, and 100 mL/min. Our study found that MFC equipped with a gyroid structure flow straightener produced the highest power density of 2871.89mWm−2, followed by the X lattice flow straightener of 2626.56 mWm−2 and 2096.03 mWm−2 with honeycomb flow straightener. ANSYS simulations revealed that this increased power density is attributed to the enhanced mixing of wastewater. Traditional honeycomb-based flow straighteners showed straight streamlines, causing bacteria to settle and leading to lower output voltage. The novel X lattice and gyroid lattice designs ensured uniform substrate mixing, addressing the issue of substrate settling and consequently boosting the MFC's power performance. An optimized flow rate of 60 mL/min yielded the best output. Overall, this study successfully introduced two novel lattice structures for flow straighteners, demonstrating their potential in enhancing power performance and the scalability of this technology when produced using additive manufacturing.

Development of the drone frame kit made up of natural fiber

Increased environmental consciousness and demand for sustainable materials have encouraged the use of more renewable and environmentally acceptable resources as reinforcement, for the natural fiber like the (Pineapple Leaf Fiber) PALF and Kenaf fiber material. These materials are natural fiber which are environmental friendly and biodegradable. This environmental friendly resources has been a demand in all industries including the aerospace industry. So, this project is to develop a drone frame kit made up of natural fiber. There are very less studies on the drone frame kit made up of natural fiber. Drones are mostly made up of synthetic fiber which is not biodegradable. Three designs of the drone frame kit had been designed by Fusion 360 software where the best frame kit with least stress distribution, least total deformation and least strain will be chosen to develop the frame. Ansys simulation can be used to analyze the frame kits for the finite element analysis. In the Ansys simulation the static structural part had been chosen to make the analysis where few boundary conditions added, and the mesh dependency test was done to get the best result. PALF and Kenaf had be chosen to be analyzed because those natural fiber having high tensile strength compared to other natural fiber. So as the project is to build a drone, there had been an idea of developing the frame kit natural fiber like the PALF and the Kenaf material. In conclusion, each and every design having their own uniqueness where the best design with least stress was the design with circular shape.

A High Vacuum, High Electric Field Pulsed Power Interface Based on a Ceramic Insulator

Improving the flashover voltage in a vacuum interface between a pulsed-power system and a vacuum region has been a goal for many years. The interface problem is difficult because of the electrical, mechanical, and vacuum issues that must be satisfied simultaneously. In this paper, according to the theories of vacuum flashover and the design rules for high electric field insulators, a ceramic insulated vacuum interface is presented. The electrostatic field along the ceramic surface was obtained by ANSYS simulations. By optimizing the field shaper and shielding rings, the electric fields were well distributed and the fields around the cathode and anode triple junctions were effectively controlled. The high voltage test was carried out on a ~40 GW, ~100-ns pulser, and results show that the vacuum interface can work stably with the hold-off voltage of 600 kV. The experimental results agree with the theoretical and simulated results. Finally, the influence of the surface treatment on the ceramic flashover characteristics was also discussed.

Research on characteristic quantity and intelligent classification prediction of metal magnetic memory detection signal

<abstract> <p>Metal magnetic memory (MMM) is an innovative, nondestructive testing method. It can detect both stress concentrations and macroscopic defects. The three-dimensional force-magnetic coupling model was established by the ANSYS simulation software, the evolution process of different defect depths was studied in detail, and the change of the signal characteristic was analyzed. The results showed that the variation trend and amplitude characteristic of MMM signals resulted in obvious differences among different defect types. Meanwhile, the impacts caused by the defect parameters and the type are complex, which cannot be decoupled or calculated by a certain formula. The accuracy of the simulation data was verified by experiments. To solve the classification prediction problem in MMM detection, the signal peak and valley <italic>H</italic><sub><italic>p-v</italic></sub>, the signal width <italic>W</italic>, the gradient <italic>K</italic><sub><italic>y</italic></sub>, and the peak energy <italic>H</italic><sub><italic>y</italic></sub> were selected as characteristic parameters to evaluate different defect types according to the change in the signal waveform. Finally, using these vectors as the input variables, the radial basis function neural network (RBFNN) pre-classification test model was established to realize the classification recognition of pit defects, crack defects, and porosity defects. The results show that the accuracy of the training and test sets, and it is feasible to use this model to complete the intelligent classification of defects.</p> </abstract>

Synergizing ANSYS Simulations and Machine Learning for Transient Thermal Analysis in Aluminium Alloys

Time-dependent thermal analysis plays a pivotal role in the manufacturing industry as it greatly influences the overall performance of the final product. This study delves into transient thermal analysis of an aluminum alloy concerning both temperature and time. Employing ANSYS, a finite element-based software, an axisymmetric model is constructed. This model encompasses a mold made of sand and a pattern filled with aluminum alloy. The analysis focuses on temperatures ranging from 650 to 1050°C, examining the temperature changes in the mold and pattern after 1500 seconds, primarily due to the convection process. Parameters like heat flux and directional heat flux are also determined. Subsequently, machine learning models are utilized to interpret the data acquired from ANSYS, enabling the extension of the results to a broader temperature range of 1150 to 1550°C. This study is instrumental in facilitating the effective design of transient thermal analysis for various alloys at different temperatures.

Comparison of Crossflow Turbine Performance through Nozzle Position Variations Using ANSYS Simulation

The performance comparison of Crossflow turbines is greatly influenced by the position of the nozzle in the conversion of water energy into mechanical energy that occurs through the blades, runners, and shafts of Crossflow turbines. The study aims to directly examine the visualization of water fluid dynamics across the turbine runner blade and enhance the performance of the Crossflow turbine by varying the nozzle position. This study intends to investigate the impact of water flow dynamics and emission on the performance of Crossflow turbines with a combined horizontal-vertical nozzle position, specifically focusing on the magnitude of the number of turbine blades driven and the size of the runner blade area. The objective of investigating nozzle position variations in Crossflow turbines is to determine the specific nozzle position at which the turbine blade may efficiently extract maximum energy from the water flow, hence optimizing turbine performance. The research method using models made using CAD software is AutoCAD by exporting to IGES or IGS format to be compatible with ANSYS. The simulation of this research is with post-processing. There are three, namely making animations, making contours, and taking data to compare cross-turbine performance using variations in nozzle position. Crossflow turbine performance with horizontal nozzle position torque and turbine power is lower, and there is an increase in a vertical position. Then, the horizontal and vertical nozzle position is very good because the nozzle is more effective with maximum turbine performance, namely 13.811-watt turbine power 1,099 turbine torque at 120 rpm.

Comparison of Crossflow Turbine Performance through Nozzle Position Variations Using ANSYS Simulation

The performance comparison of Crossflow turbines is greatly influenced by the position of the nozzle in the conversion of water energy into mechanical energy that occurs through the blades, runners, and shafts of Crossflow turbines. The study aims to directly examine the visualization of water fluid dynamics across the turbine runner blade and enhance the performance of the Crossflow turbine by varying the nozzle position. This study intends to investigate the impact of water flow dynamics and emission on the performance of Crossflow turbines with a combined horizontal-vertical nozzle position, specifically focusing on the magnitude of the number of turbine blades driven and the size of the runner blade area. The objective of investigating nozzle position variations in Crossflow turbines is to determine the specific nozzle position at which the turbine blade may efficiently extract maximum energy from the water flow, hence optimizing turbine performance. The research method using models made using CAD software is AutoCAD by exporting to IGES or IGS format to be compatible with ANSYS. The simulation of this research is with post-processing. There are three, namely making animations, making contours, and taking data to compare cross-turbine performance using variations in nozzle position. Crossflow turbine performance with horizontal nozzle position torque and turbine power is lower, and there is an increase in a vertical position. Then, the horizontal and vertical nozzle position is very good because the nozzle is more effective with maximum turbine performance, namely 13.811-watt turbine power 1,099 turbine torque at 120 rpm.

ANSYS Simulation of Enhanced Heat Transfer in Compact Pipes Using Al2O3-Water Nanofluids

Al2O3-Water nanofluids have become popular for their significantly higher heat transfer rates, which are related to their increased thermal conductivity. These fluids are particularly useful in tiny pipelines, especially in situations where effective thermal control is required. Because of this, they are particularly beneficial to sectors like aerospace and automotive, where the need for lightweight and compact heat exchanger designs is crucial. This research investigates several input factors, such as temperature and velocity, using ANSYS Fluent. The investigation's initial temperature was 290 K, and the pipe's entry velocity was 3.78×10-1 m/s. At 2.98×102 K, the exit temperature stabilized. However, a clear inverse link between the temperature at the pipe's output side and the velocity at its entrance side was found. This unique development served as the main focus of our investigation on how to optimize heat flow and thermal conductivity inside the pipe. We used a two-phase approach, incorporating the nanofluid phases phi-0 and phi-4, to increase our comprehension. This methodological decision departs from traditional research, which frequently uses simulations in a single phase. Our new method was inspired by the necessity for a more thorough investigation. The results of this study demonstrate the effectiveness of the two-phase method, showing a significant rise in heat flow and thermal conductivity when compared to traditional one-phase simulations used in earlier research. This emphasizes how our approach was original and significant, bringing fresh perspectives to the field of nanofluid heat transfer research.

IFM calculator: An algorithm for interfragmentary motion calculation in finite element analysis

BackgroundInterfragmentary motion (IFM) is a complex state that significantly impacts the healing process of fractures following implant placement. It is crucial to fully consider the IFM state after implantation in the design and biomechanical testing of implants. However, current finite element analysis software lacks direct tools for calculating IFM, and existing IFM tools do not offer a comprehensive solution in terms of accuracy, functionality, and visualization. MethodsIn our study, we developed a Python-based algorithm for calculating IFM that addresses limitations. Our algorithm automatically calculated IFM distances, sliding distances, gaps, as well as the angles and rotation of the two fracture surfaces using all nodes on both sides of the fracture ends. Researchers could input data and selected desired parameters in the interface. The algorithm then performed the necessary calculations and presented the results in a clear and concise manner. The algorithm also provided comprehensive data export capabilities, allowing researchers to customize analyses based on specific needs.To provide a more intuitive demonstration of the calculation process and usage of IFM-Cal, we conducted simulations in Ansys using two rectangular blocks to compare the accuracy and function of three different methods (Point based method, contact tool and IFM-Cal). ResultsThe point-based method and the contact tool could not accurately calculate IFA, while IFM-Cal could provide a comprehensive evaluation of IFA. In simulation 1, the IFM distances calculated using the point sampling method, contact tool, and IFM-Cal were 2.00 mm, 3.15 mm, and 2.00 mm, respectively. In simulation 2, both the point sampling method and contact tool failed to calculate the interfragmentary angle (IFA), while the IFM-Cal algorithm estimated an angle of -7.87°, which had a small error compared to the ground-truth value of 7.9°. ConclusionWe have developed an algorithm for computing IFM which can be utilized in finite element analysis and biomechanical experiments. By conducting comparative simulations with other existing algorithms, we have demonstrated the superior accuracy and expanded evaluation capabilities of our algorithm.

Liquefaction test and seismic load simulation of saturated sand subgrade with different salt contents

On the basis of the highway subgrade construction of North Hobson Salt Lake mining area in Qinghai Province, the soil samples of high saline saturated sand adjacent to the salt lake were remolded, and four types of saturated sand containing 0%, 10%, 20%, and 30% salt were configured respectively, so as to explore the liquefaction effect of saline saturated sand under seismic load. After the indoor geotechnical test, the soil samples were reshaped, The liquefaction test of saline saturated sand was carried out by using the GDS dynamic triaxial device to simulate seismic load to investigate the liquefaction mechanism of saturated sand under different salt contents and verify the liquefaction discrimination standard, then based on the data of dynamic elastic modulus, dynamic shear modulus, damping ratio coefficient, and soil density obtained from previous soil tests and dynamic triaxial tests, four subgrade models with different salt contents were constructed using ANSYS simulation software according to actual engineering, and the settlement and deformation of the subgrade were analyzed by inputting EL-concrete seismic waves. The results show that the maximum value of axial stress of saturated sand decreases with the increase of salt content; the load vibration times of saline saturated sand reaching the initial liquefaction state are more than that of common saturated sand; the higher the salt content, the weaker the liquefaction resistance of saturated sand; when the pore pressure ratio coefficient reaches 1, the axial double amplitude strain εd of the soil also reaches 5%, and the soil reaches the initial liquefaction state; the area of shear stress and strain hysteresis curve increases with vibration load, and the elastic modulus decreases gradually; the shear dilation and compaction effects occur in each hysteresis cycle, and the former is greater than the latter, the research results have guiding significance for similar studies in highly saline saturated sand areas.

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Investigation of the thermal analysis of a wavy fin with radiation impact: an application of extreme learning machine

The combined impact of radiation and convection on the heat transfer of a wavy fin is scrutinized in the present analysis. The novelty of this research work is that it proposes a deterministic machine learning model known as an extreme learning machine to address the heat transfer problem of a wavy fin. The effect of radiation on convective heat transfer and the Rosseland approximation for the radiation heat exchange have been considered in the investigation. The nonlinear ordinary differential equation (ODE) is converted to its nondimensional form using the appropriate dimensionless variables. Runge-Kutta-Fehlberg's fourth-fifth order technique (RKF 45) is used to solve the nondimensional ODE numerically. The roles of convection-conduction, radiation-conduction, thermal conductivity, and radiation parameters have been discussed for satisfying a prescribed temperature distribution in rectangular and wavy fins with graphical visualization. A rise in convection-conduction and radiation-conduction variables decreased the thermal distribution of both the wavy fin and rectangular fin. Further, ANSYS simulation analyzes the variation of temperature and total heat flux in both rectangular and wavy fins. The study demonstrates the effectiveness of the model selected through the obtained results, which indicate the potential of the regression model for providing an accurate prediction.