User-defined Functions Research Articles

Experimental and 1D Modeling Analysis of Thermoelectric Generation to Improve the Performance of Compressed Natural Gas Heavy-Duty Engines Used in Commercial 22-Ton Trucks

<div>A significant amount of chemical fuel energy in internal combustion engines is wasted through exhaust heat. Waste heat recovery (WHR) systems can transform the heat into electrical energy using thermoelectric generators (TEG). This work utilizes a 1D CFD model to demonstrate the potential of TEG-WHR in improving the thermal efficiency of mass-production, compressed natural gas (CNG) engines used in commercial 22-ton heavy-duty trucks. First, the TEG with heat exchanger experiments are performed to measure thermal and electrical performance data under different fin pitches and inlet gas conditions (Re number, temperature, gas flow rate). These data are used to develop and validate a TEG model, which considers user-defined functions of heat transfer and flow friction coefficients to reproduce measured thermal/electrical characteristics of the integrated TEG with its heat exchanger. The engine experiments are conducted based on the speed–torque map (51 test conditions) of the JE05 heavy-duty cycle using the turbocharged engine equipped with a multi-port injection system. The engine model is calibrated and validated against test data under base conditions (using production valve timings), optimal variable valve actuation (VVA), and variable compression ratio (VCR). Finally, the high-fidelity engine and TEG models are integrated to predict the electrical power generated by a compact TEG-WHR (three-layer, size: 1.3 × A4-paper). The integrated model considers a tradeoff between TEG-generated power and engine pumping loss. Simulation results show that the compact TEG can generate effective 20–701 W electrical powers, translating to about 0.03–1.07% brake thermal efficiency improvement.</div>

Co-combustion of coal and sawdust in a three-dimensional industrial scale BFB boiler (BG-043, 67TPH): a numerical approach

ABSTRACT Experiments in large-scale CFBC boilers are expensive and time-consuming, while simulations are economical, time-saving, and provide better control over the physical process. In the current research, mathematical modeling of industrial scale CFBC boiler (BG-043, 67TPH capacity, ACC cement factory Bargarh, Odisha, India) using coal and sawdust blended fuel (90% coal + 10% sawdust) is performed by considering the four distinct (coal, sawdust, sand, and mixture gas) phases using Eulerian–Eulerian multifluid model. Heterogenous chemical reactions kinetics are implemented using user-defined functions. The numerical methodology is validated with the onsite industrial data. The comparison of pressure drop, fluidized bed height, axial velocity profiles, sand, and mixture gas temperature variations, gas compositions, and pollutant emissions (SO2 and NO) using solo coal and sawdust blended fuel are presented in the result section. Hydrodynamics study reveals the recirculation of sand particles in the fluidized bed region of the boiler. The comparison of solo coal and sawdust blended fuel combustion study reveals a 10.61% reduction in pressure drop, 12.13% increase in O2 mass fraction, 9.63% reduction in CO mass fraction, 19.64% reduction in SO2 mass fraction, and 8.67% reduction in NO mass fraction while using the 10% sawdust blends with 90% coal.

Investigating air compressibility effects in numerical modeling of oscillating water column wave energy converters: a case study on performance and accuracy

ABSTRACT Wave energy, as a clean and abundant resource, offers significant potential for sustainable power. Oscillating Water Column (OWC) is a key technology in this domain. In studies related to OWC, air compressibility can be a significant parameter. This research examines the error caused by neglecting the effects of air compressibility in numerical modeling. To this end, a numerical solution for a 1:10 scaled OWC model was developed based on RANS equations and the Volume of Fluid (VoF) method for free surface water. The wave conditions studied correspond to those in the Caspian Sea. For validation, the pressure within the chamber was compared with experimental results. The results indicated that the error for the incompressible model is 9.89% and for the compressible model is 8.43%. To account for air compressibility effects, a User-Defined Function (UDF) was added to the numerical solution, which adjusts the air density according to isentropic pressure equations. The results showed that considering air compressibility can lead to up to a 5.71% overestimation of the converter’s output power at certain incident wave frequencies. Additionally, at resonance conditions where the incident wave frequency matches the natural frequency of the converter, the effect of air compressibility is minimized.

Investigation on the influence of rotational speed on oil film stability of hydrostatic rotary table

PurposeThe purpose of this study is to investigate the influence of rotational speed on the oil film stability of the hydrostatic rotary table having double rectangular oil pads. The oil film stability is evaluated based on the oil film stiffness under constant load condition and the displacement response amplitude of the oil film under disturbance load condition.Design/methodology/approachThe oil film stability theoretical equations of the double rectangular oil cavity are deduced such as oil film stiffness, damping and dynamic equations. A simulation model is developed to analyze the relationship among oil film temperature, oil film pressure fields and oil film stability. The user-defined function programs are used to control the rotational speed, lubricant viscosity and oil film thickness during the simulation. In addition, an experimental rig is built to test the simulation results.FindingsThis study shows that oil film stability decreases with increasing rotational speed under constant load and disturbance load. The trend of oil film stability decreased slowly within 30 r/min, and then rapidly. However, since the hydrodynamic pressure effect, the decrease rate of stability is mitigated under constant load and high rotational speeds.Originality/valueThe conclusions can provide a theoretical basis for improving the oil film stability of machines with similar hydrostatic support structure.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0267/

Study of Airflow Dynamics and Particle Transport in the Upper Respiratory System using Numerical Simulation

The increase in pollution levels in recent years has increased the prevalence of pulmonary diseases. The accumulation of pollutant particles in the pulmonary tract is speculated to be one of the major reasons for the increase in chronic cases. This necessitates the study of the mechanism of particle deposition in human airways to develop better drug delivery systems. Aerosolized forms of drugs are commonly used to treat pulmonary diseases. The current study employed computational fluid dynamics (CFD) and discrete element method (DEM) techniques to study airflow patterns and particle deposition phenomena. An idealized 3D CAD model was developed based on available literature. A discretized finite-volume model was tested to ensure an independent solution. A user-defined function (UDF) was used to simulate realistic breathing dynamics for the respiration cycle. The aerosol particles of the calculated volume were mixed into the airflow domain. The analysis was conducted using ANSYS FLUENT CFD solver. This study found several regions of high turbulence in the upper human airways, with secondary flow structures exhibiting bifurcations and the glottal region. The study also found that the oral cavity and oropharynx regions with higher turbulence intensity had a concentrated deposition of particles. Most of the aerosol particles (5μm) were transported into the alveolar sacs, where they were absorbed into the bloodstream. The oral cavity and oropharynx have the highest pressure and particle deposition efficiency, while the trachea plays a crucial role in particle deposition during inhalation due to weak oscillatory flows and turbulence, especially in the tracheal region and lower respiratory tract. The oral cavity has the highest efficiency at 7.32%, while the trachea has the lowest at 0.4%. The overall deposition efficiency across all regions is 9.078%.This study did not account for the breakup of aerosol particles. Aerosol particles can break apart due to airflow and collisions, affecting their size and deposition efficiency. Ignoring this breakup could lead to inaccurate results, making accurate dosimetry essential for inhalation studies

Using ansys fluent udf for numerical study of the movement of the rollers of a downhole positive displacement pump

In order to improve the design and increase the technical characteristics of pump and compressor equipment, computational modeling of fluid dynamics is used. Numerical research techniques of positive displacement machines are quite diverse and are widely used for vane and gerotor pumps. The roller rotary pump considered in this work is used for oil production in the sidetracks of oil wells. The difference in the design is the use of rollers as partitions separating the working chambers of the pump. The authors of the article propose a method for studying the movement of rollers in the Ansys (Fluent) software package, and related issues of creating userdefined functions (UDF) to describe reciprocating motion using the macro DEFINE_CG_MOTION (name, dt, vel, omega, time, dtime). It is shown that the result of calculating the movement speed in ansys fluent differs from the graph of the given function. A sine law is substantiated to describe the speed of movement of the roller’s center of mass. The method for determining the coefficients in a sinusoidal dependence is described and it is shown how these coefficients affect the movement of the roller. The results obtained in the study can be used when performing verification of analytical calculation methods with finite element modeling data using UDF Ansys, and will also help young researchers understand the writing of UDF DEFINE_CG_MOTION. Keywords: fuel and energy complex; oil and gas industry; well equipment; volumetric pump; Computational Fluid Dynamics (CFD); numerical simulation; moving mesh; User Define Function (UDF).

Effect of Different Pressures on Polymer Flow at a Contraction Path: A Real-Time Numerical Approach

The complexity of polymer flow through a contraction arises from the simultaneous occurrence of shear and elongational strains near the entrance of the contraction path (die). Although this phenomenon has been extensively studied, the effect of plunger motion on the flow toward the contraction path remains underexplored. This study investigated the rheological behavior of thermoplastic polymers at a contraction flow path to enhance the understanding of their flow and rheological behavior, including variations in velocity, pressure, viscosity, and shear rate under varying loads. Polypropylene (PP), a semicrystalline polymer with a low melting point, was used as the test material. The operating temperature was set to 180 °C, and the displacement of the plunger, marked with black lines at its initial and final heights, was recorded under loads of 0.3, 0.6 and 0.85 MPa. The displacement rates were analyzed using MATLAB. A dynamic mesh approach in ANSYS 19 was employed to simulate the real-time motion of the plunger, incorporating a user-defined function developed in C language to control the dynamic boundary motion. The numerical approach successfully simulated the rates of plunger displacement (speed) and predicted the viscosity of PP within the paths (barrel and die). Results indicated that the plunger speed increased with pressure. The pressure generated by the plunger created a driving force that overcame the resistance to flow within the barrel. Higher pressure from the plunger resulted in a greater driving force, which increased the flow rate of the polymer melt through the barrel. On the other side, as the polymer melt flowed from a large cross-sectional area to the contraction flow area, the velocity of the polymer molecules increased, resulting in a pressure drop in the PP melt. Polymer molecules became oriented and stretched in the flow direction upon entering the contraction area, further increasing the shear rate. Consequently, the reduced cross-sectional area in the contraction increased the flow rate, elevated the shear rate, and decreased the viscosity, facilitating polymer flow through the contraction.

Determination of Wind Force Acting on an Object in the Shape of a Bent Pipe

The aim of the paper is to determine the aerodynamic forces acting on a torus-shaped structure fragment at high wind velocity which are impossible to obtain from the existing standard EN 1991-1-4 (the so-called wind standard). The most important problem is the correct modeling of turbulence and laminar-turbulent transition in the conditions of flow interference resulting from the presence of other obstacles. For this reason, forces are obtained by two methods: Fluid-Structure Interaction (FSI, force transfer) and User-Defined Functions (UDF). Variations of the total aerodynamic lift force of the half of the torus with angle β and velocity of wind w, and the formula for estimating the horizontal force Pz perpendicular to drag force are presented. Additionally, useful engineering parameters (such as pressure distribution and air velocity field) are determined. The forces of wind influence on two cylinders and a torus-shaped object are obtained and compared

Convective heat transfer improvement for a horizontal grooved surface by the piezo-fan integration

In this study, the thermal and hydraulic performances of horizontal grooved surfaces subjected to the piezo-fan ( PF) is numerically investigated. A total of four grooved surfaces with varying dimensionless edge length of the square groove cross-section ( EL = 0.25, 0.5, 0.75 and 1) and a corresponding baseline flat surface ( EL = 0) are considered. Two kinds of numerical models are utilized to capture the turbulent characteristics and temperature distribution. The dynamic mesh technique and user-defined function are employed to descript the vibration trajectory of the PF. The focus of this study is on assessing the impact of PF in the design of an active heat sink. It is confirmed that, due to the change in surface geometry, the flow cannot follow the surface contour perfectly, leading to a pressure drop and a separation of flow from the grooved surface. The integration of PF into a horizontal grooved surface is a highly efficient means for improving heat transfer performance. Its role in heat transfer enhancement is most significant when the dimensionless edge length is EL = 0.75. With the presence of PF, the effective area-averaged convective heat transfer coefficient ( harea,eff) both on flat and grooved surfaces are generally larger than the corresponding one without the PF. Of particular is that the harea,eff of both types of target surfaces reach their maximum within the specified zone S4 (4 APP × 4 WPF), with the grooved surface being approximately 14% to 28% higher than the flat surface. Moreover, the numerical simulation method has been validated through the comparison with a simple heat transfer experiment.

Numerical Study on the Wave Attenuation Performance of a Novel Partial T Special-Type Floating Breakwater

Floating breakwaters (FBs) play an important role in protecting coastlines, marine structures, and ports due to their simple construction, convenient movement, cost-effectiveness, and environmental friendliness. However, the traditional box-type FBs are flawed due to their requiring large sizes for wave attenuation and their overly high level of wave reflection. In this paper, a novel partial T special-type FB with wave attenuation on the surface and flow blocking below the water has been presented. First, the User-Defined Function (UDF) feature in ANSYS Fluent was employed to compile the six degrees of freedom (6-DOF) motion model. A two-dimensional viscous numerical wave flume was developed using the velocity boundary wave-generation method and damping dissipation wave-absorption method, with fully coupled models of the FBs developed. A VOF multiphase flow model and a RANS turbulence model were employed to capture the free flow of gas–liquid two-phase flow. Then, the performance of wave attenuation of the new FB was compared with that of the traditional box-type FB of the same specifications. The simulation results showed that the transmission coefficient of the new FB is significantly lower than that of the box-type FB, and the dissipation coefficient is notably higher, demonstrating excellent performance of wave attenuation, particularly for long-period waves. As wave height increases, the novel FB benefits from its wave attenuation mechanism, with a lower reflection coefficient compared to the box-type FB. Finally, through parametric analysis, some design recommendations of the novel FB suitable for practical engineering applications in deep-sea aquaculture are presented.

A data-driven framework for biomarker discovery applied to optimizing modern clinical and preclinical trials on Alzheimer's disease.

PET is used to measure tau protein accumulation in Alzheimer's disease. Multiple biomarkers have been proposed to track disease progression, most notably the standardized uptake value ratio of PET tracer uptake in a target region of interest relative to a reference region, but literature suggests these region choices are nontrivial. This study presents and evaluates a novel framework, BioDisCVR, designed to facilitate the discovery of useful biomarkers, demonstrated on [18F]AV-1451 tau PET data in multiple cohorts. BioDisCVR enhances signal-to-noise by conducting a data-driven search through the space of possible combinations of regional tau PET signals into a ratio of two composite regions, driven by a user-defined fitness function. This study compares ratio-based biomarkers discovered by the framework with state-of-the-art standardized uptake value ratio biomarkers. Data used is tau PET regional measurements from 198 individuals from the Alzheimer's Disease Neuroimaging Initiative database, used for discovery, and 42 from the Mayo Clinic Alzheimer's Disease Research Center and Mayo Clinic Study of Aging (MCSA), used for external validation. Biomarkers are evaluated by calculating clinical trial sample size estimates for 80% power and 20% effect size. Secondary metrics are a measure of longitudinal consistency (standard deviation of linear mixed-effects model residuals), and separation between cognitive groups (t-statistic of the change over time due to being cognitively impaired). When applied to preclinical (secondary prevention with CU individuals) and clinical (treatment aimed at cognitively impaired individuals) trials on Alzheimer's disease, our data-driven framework BioDisCVR discovered ratio-based tau PET biomarkers vastly superior to previous work, both reducing measurement error and sample size estimates for hypothetical clinical trials. Our analysis suggests remarkable potential for patient benefit (reduced exposure to health risks associated with experimental drugs) and substantial cost savings, through accelerated trials and reduced sample sizes. Our study supports the leveraging of data-driven methods like BioDisCVR for clinical benefit, with the potential to positively impact drug development in Alzheimer's disease and beyond.

Numerical investigation of aerodynamic performance in a morphing wing with flexible leading edge using computational fluid dynamics

In this study, a numerical investigation into the sustained aerodynamic performance of a morphing wing equipped with a flexible leading edge, employing a 2-dimensional NACA0012 airfoil configuration, is conducted. The compressible governing equations of the flow are employed, simulating 2 distinct states: the airfoil without motion and the airfoil featuring a flexible leading edge with a chord length of 0.856 m, assessing various angles of attack utilizing the k-ω SST turbulence approach within Fluent software. Dynamic mesh, facilitated by a user-defined function, is utilized in Fluent software to simulate the movement of the airfoil wall at the leading edge. The study thoroughly analyzes the flow behavior concerning diverse angles of attack and deviations, evaluating their impact on aerodynamic coefficients, velocity, and pressure fields under steady-state settings. Validation of the chosen numerical approach demonstrates close alignment of the front and back coefficients with experimental settings. Outcomes from the steady-state flow simulation of the morphing wing reveal that positive deflection angles correspond to increased lift coefficients and decreased drag coefficients, with lift coefficient increases of up to 15% and drag coefficient reductions of up to 10% at specific angles. Meanwhile, the negative deflection angles have shown a decline in lift coefficients, with the drag coefficients increasing with the decrease in deflection angle. All these observations show that at the flexible leading edge, there is a considerable improvement in aerodynamic efficiency. Hence, it should find more applications in different regimes of flight.

Simulation of Stack-Integrated Autothermal Reformer and Solid Oxide Fuel Cells for Operation in Aircraft Engines

Renewable liquified natural gas provides a potential sustainable aviation fuel, but with a volumetric energy density around 70% of conventional jet fuel. As such, alternative aircraft power plants such as hybrid gas turbine (GT) / solid oxide fuel cells (SOFCs) have been proposed to increase fuel conversion efficiency and support hybrid electric propulsion concepts. To enable reliable SOFC operation within aircraft gas turbine flow paths, stack architectures must be identified that sustain very high-power densities with direct inline air feeds from the gas turbine compressor outlet. Typical aircraft compressor outlet temperatures are below SOFC operating temperatures but high enough to light-off a catalytic autothermal reformer (ATR). The ATR combined with an air heat exchanger (HX) can preheat anode and cathode streams to desirable inlet temperatures above 500 °C for intermediate-temperature SOFCs that utilize gadolinia-doped ceria (GDC) electrolytes or thin-film, yttria-stabilized zirconia (YSZ) electrolytes. By packaging the inline ATR/HX within the SOFC stack and mixing partial anode exhaust recycle and bleed air with the ATR fuel stream, a volumetrically efficient inline stack architecture is being designed for demonstration at conditions simulating an aircraft gas-turbine compressor outlet. The combination of the ATR/HX and the high-power-density SOFC imposes significant temperature gradients within the stack that can impact performance. To assess suitable operating conditions and preferred designs for the ATR/HX/SOFC operating on renewable natural gas, a 3-D multi-physics CFD model has been developed. Simulation results for SOFCs with thin-film YSZ or GDC electrolytes show the challenge maintaining high-power densities while maintaining the full stack within expected temperature limits for expected cell materials.The ATR/HX/SOFC stack design includes the upstream ATR/HX, 3.6 cm in length. The ATR flow path is filled by a porous mesh with a washcoat-supported Pt catalyst for light off of CH4/bleed air/H2O inlet mixtures. The air-side flow paths in the ATR/HX are etched parallel channels that extract heat from the exothermic ATR reactions. The ATR/HX outlets feed the SOFC anode and cathode flow paths respectively. For this study, the SOFC membrane electrode assembly (MEA) 10 cm in length, consists of a porous Ni-YSZ anode-support (400 mm thick), dense YSZ or GDC electrolytes (≤ 20 mm thick), and a perovskite-YSZ composite cathode (35 mm thick). The anode flow passages over the support involve a high-porosity mesh that enables current collection. The cathode flow channels are etched ribs that enable high air flow rates to support high power density with adequate SOFC stack cooling. The ATR/HX/SOFC design has been incorporated into an ANSYS Fluent model to explore how integration of the ATR/HX in the stack can enable high-power performance of the SOFC while supporting light-off of the ATR fuel stream at aircraft compressor outlet conditions. The ANSYS Fluent model uses customized user-defined functions to handle the heterogeneous catalytic CH4oxidation surface chemistry for the ATR (supported Pt catalyst [1]) and for internal CH4 reforming in the Ni/cermet anode support in the SOFC [2]. The model simulates non-isothermal operation of a single ATR/HX/SOFC cell, representative of a full stack, at various inlet flow temperatures, pressures, flow rates, and fuel stream compositions, which are set by anode exhaust recycle fraction.CFD model results for thin-film YSZ-electrolyte MEAs illustrate a strong dependence of SOFC power density on the anode recycle fraction and cathode bleed air splits into the ATR fuel stream. For a 400 °C air inlet, the short ATR/HX is capable of achieving near-equilibrium CH4 conversion to an H2-rich reformate while preheating the cathode inlet up to 500 °C. Simulations over a range of anode recycle fractions show that lower recycle fractions increase ATR outlet temperatures and H2 mole fractions with SOFC power densities reaching 2.0 W cm-2, but at the risk of excessive anode temperatures and large temperature gradients across the length of the MEA. Increased cathode excess air ratios can lower the temperatures at the expense of stack power density. Higher anode recycle fractions decrease the temperature rise across the length of the MEA, but also at the expense power density. Further studies with GDC electrolytes based on recent GDC SOFC model developments [3] will explore how high-power densities of GDC can be supported within its operating temperature constraints.

Validation of a general-use high flux isotope reactor–specific metaheuristic optimization framework for isotope production target design

Currently, advanced optimization methods are limited for isotope production (IP) campaigns at the US Department of Energy’s High Flux Isotope Reactor (HFIR) located at Oak Ridge National Laboratory (ORNL), leading to years of conservative and historical approaches with minimal innovation. Moreover, the growing demand for new and existing isotopes is beginning to challenge the capacity of HFIR. This work explores the development and integration of metaheuristic (MH) optimization techniques for more efficient target design and irradiation strategies. As a test case, the optimization framework was applied to a routinely produced isotope at HFIR, 188W, with the objective of maximizing the specific activity (SA), a key production metric. The framework includes Gnowee, a Python-based MH optimization algorithm, coupled with the Monte Carlo N-Particle version 6 (MCNP6) and Oak Ridge Isotope Generation (ORIGEN) activation/depletion/decay codes to design, simulate, and evaluate thousands of potential target design and irradiation scheme candidates. The framework relies on mock input files, design and irradiation variables for the algorithm to select, as well as a user-defined objective function to score each candidate based on the returned SA. Given the inherent complexities and computational time required when modeling and simulating the full HFIR model, a novel simplified MCNP6 model is presented in this article to increase the computational efficiency of the framework. The variables explored include irradiation location, number of cycles, and the number of W samples. Over 1,000 simplified model candidates were simulated in the same amount of time as a single full HFIR model run. By comparing the simplified model optimization’s top candidate(s) with the full HFIR model results, the framework was verified to accurately explore the design space and converge on the top performing candidates. Lastly, past experimental data was compared to the data generated by the framework/model and both show that fewer W rings return higher SA, as expected. The verified and validated techniques provide a standardized solution to increase IP efficiencies by exploring thousands of unique target designs and irradiation strategies in a similar time as that required to run a single case in the full HFIR MCNP6 model. Both the novel simplified model and the full HFIR model show a more than 30% increase in SA if all presented modifications are applied to the current design and strategy. Thus, the objective of building a general-use, computationally efficient optimization framework for HFIR IP was accomplished, and has the potential to be applied to other IP campaigns.

The Neuromusculoskeletal Modeling Pipeline: MATLAB-based Model Personalization and Treatment Optimization Functionality for OpenSim.

Neuromusculoskeletal injuries including osteoarthritis, stroke, spinal cord injury, and traumatic brain injury affect roughly 19% of the U.S. adult population. Standardized interventions have produced suboptimal functional outcomes due to the unique treatment needs of each patient. Strides have been made to utilize computational models to develop personalized treatments, but researchers and clinicians have yet to cross the "valley of death" between fundamental research and clinical usefulness. This article introduces the Neuromusculoskeletal Modeling (NMSM) Pipeline, two MATLAB-based toolsets that add Model Personalization and Treatment Optimization functionality to OpenSim. The two toolsets facilitate computational design of individualized treatments for neuromusculoskeletal impairments through the use of personalized neuromusculoskeletal models and predictive simulation. The Model Personalization toolset contains four tools for personalizing 1) joint structure models, 2) muscle-tendon models, 3) neural control models, and 4) foot-ground contact models. The Treatment Optimization toolset contains three tools for predicting and optimizing a patient's functional outcome for different treatment options using a patient's personalized neuromusculoskeletal model with direct collocation optimal control methods. Support for user-defined cost functions and model modification functions facilitate simulation of a vast number of possible treatments. An NMSM Pipeline use case is presented for an individual post-stroke with impaired walking function, where the goal was to predict how the subject's neural control could be changed to improve walking speed without increasing metabolic cost. First the Model Personalization toolset was used to develop a personalized neuromusculoskeletal model of the subject starting from a generic OpenSim full-body model and experimental walking data (video motion capture, ground reaction, and electromyography) collected from the subject at his self-selected speed. Next the Treatment Optimization toolset was used with the personalized model to predict how the subject could recruit existing muscle synergies more effectively to reduce muscle activation disparities between the paretic and non-paretic legs. The software predicted that the subject could increase his walking speed by 60% without increasing his metabolic cost per unit time by modifying existing muscle synergy recruitment. This hypothetical treatment demonstrates how NMSM Pipeline tools could allow researchers working collaboratively with clinicians to develop personalized neuromusculoskeletal models of individual patients and to perform predictive simulations for the purpose of designing personalized treatments that maximize a patient's post-treatment functional outcome.

Combining pin-fins and superhydrophobic surfaces to enhance the performance of microchannel heat sinks

Electronics cooling and thermal management presents an immense challenge to the electrification of society. From mobile devices to stationary systems, power densification of electronics platforms is putting pressureon thermal systems. This research uniquely combines superhydrophobic surfaces with pin-fin structures to investigate their combined effects on thermal performance and fluid dynamics. We examine the impact of superhydrophobic surfaces on different internal walls for both finned and non-finned microchannels. Three-dimensional finite volume method simulations are used to analyze fluid flow and heat transfer, with surface wettability modeled using a custom user-defined function. The results of the simulations were first validated against experimental data. Thermal-hydraulic performance for finned and non-finned microchannels was studied for both conventional and superhydrophobic surfaces. Superhydrophobic properties on different internal surfaces of the microchannel yielded different outcomes for finned versus non-finned designs. We show that superhydrophobic surfaces are effective in enhancing the performance of finned channels at high Reynolds number (Re). At Re = 500, finned microchannels with superhydrophobic side walls have the same performance factor (η) as a conventional microchannel without fins with a 9.4 °C lower average base surface temperature. Additionally, superhydrophobic side walls increase the pressure drop and Nusselt number by 8.9 % and 6.6 %, respectively, compared to conventional non-superhydrophobic finned surfaces. Conversely, superhydrophobic top and bottom surfaces reduce the pressure drop and Nusselt number by 13 % and 18.5 %, respectively. Our findings reveal that the location and intensity of vortices, influenced by fins, vary with different superhydrophobic surface configurations.

A comprehensive study on tuberculosis prediction models: Integrating machine learning into epidemiological analysis

Tuberculosis (TB), the second leading infectious killer globally, claimed the lives of 1.3 million individuals in 2022, after COVID-19, surpassing the toll of HIV and AIDS. With an estimated 10.6 million new TB cases worldwide in 2022, the gravity of the disease persists, necessitating urgent attention. Tuberculosis remains a critical public health crisis, and efforts to combat this infectious disease demand intensified global commitment and resources. This study utilizes predictive modeling techniques to forecast the incidence of Tuberculosis (TB), employing a range of machine learning models. Additionally, the research incorporates impactful visualizations for comprehensive data exploration, analysis and comparison. Various machine learning models are developed to anticipate TB incidence, with the optimal performing model to customize a user-defined function. This research provides valuable insights into the potential determinants influencing TB incidence, contributing to the identification of strategies for preventing the spread of Tuberculosis.

Paired piecewise linear regression model with fixed nodes

In this paper we develop a method for constructing a paired regression model in the class of piecewise linear continuous functions with fixed nodes. The concept of linear division of the correlation field, its partial sections and its nodes is introduced into consideration. Using the linear division of the correlation field, a class of piecewise linear functions with fixed nodes is determined. The linear division is revealed during the visual analysis of the correlation field. Using the least squares method, a system of linear equations is compiled to find point estimates of the parameters of the approximating function. With the exception of two unknown angular coefficients (unknown) this system is reduced to a tridiagonal system of equations, the unknowns of which are the nodal values of the approximating function. The tridiagonal system is solved by the run-through method. An algorithm was constructed to demonstrate the operation of the developed method. Its initial data is arrays of the corresponding values of the explanatory and dependent variables, as well as an array of numbers of the right ends of the intervals defining the nodes. An array of fixed nodes is constructed from an array of values of the explanatory variable and an array of numbers of the right ends of the intervals. Next, an array of point estimates of the parameters of the approximating function is constructed. This algorithm is implemented in Python in the form of user-defined functions.

Performance analysis and improvement of a novel reed valve in compressors using fluid–structure interaction method

The reed valves used as suction valves in reciprocating compressors are more susceptible to damage due to the limitation of the lift limiter which can't completely block the entire valve plate. This article proposed a novel reed valve featuring a redesigned shape aimed to solve this issue. Compared to conventional reed valves, the proposed valve could effectively mitigate the highest stress occurring at the root of the suction valve. To thoroughly investigate the characteristics of this valve type and improve its performance, a three-dimensional fluid–structure interaction (FSI) model was established and validated using experiments. The leakage through the valve gap in the FSI model was solved using a combination of user-defined function (UDF) and Scheme file in Fluent. Based on this FSI model, the dynamic characteristics and stress distribution of the valve were mainly analyzed. The effect of the lift limiter on the performance of the valve was analyzed, and a suitable lift was determined. Moreover, the influence of thickness and shape parameters, was also analyzed and an efficient improved scheme was subsequently proposed. Through this scheme, the maximum stress of the valve was reduced by 23.77% compared with that of the original valves. This article provides important information for the design and optimization of complex-shaped reed valves.

Non-equilibrium condensation flow characteristics of wet steam considering condensation shock effect in the steam turbine

A non-equilibrium condensation flow occurs in steam turbines, accompanied by condensation shock. At present, there are limited studies on the influence of condensation shock on the flow and condensation characteristics of wet steam, and the unsteady influence of condensation shock on the flow field of wet steam always have been ignored. In this paper, the unsteady flow characteristics of condensation were presented by considering the condensation shock effect. First, the condensation flow models and corresponding source terms were programmed and loaded with UDS (user-defined scalar) and UDF (user-defined function), respectively, and the governing equations were discretized using a high-resolution calculation method. The calculated results agreed well with the reported experimental results. Based on the models, the non-equilibrium condensation flow characteristics with inlet and outlet pressures in Laval nozzle considering the condensation shock effect were analyzed. Finally, during the unsteady phase change process, the effects of back pressure and saturation of the inlet on the liquid phase parameters were examined considering the condensation shock effect in the Dykas cascade. The results show that a decrease in the back pressure and an increase in the inlet pressure improve the condensation shock intensity in Laval nozzle. With the increase of condensation shock intensity, the nucleation rate increases. Moreover, in Dykas cascade, with the increase of back pressure from 48.8 kPa to 73.2 kPa, the maximum wetness decreases from 4.8 % to 2.1 %, whereas with the increase of relative saturation from 0.58 to 0.88, the maximum wetness increases from 2.4 % to 3.6 %. The results obtained in this paper are of significance to accurately analyze the actual situation of non-equilibrium condensation flow of wet steam and to develop methods for reducing wet steam loss in turbine stage.