bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Local Concentration to Model the Progress of Acoustophoretic Assembly of Microspheres in Planar Standing Waves
Authors: Wang Y. Jenny , Anthony Brian W.
Published: February 2024

Acoustophoretic assembly uses a standing acoustic field to move dispersed small particles into a geometric pattern. The technique relies on the acoustic radiation force, which arises from the interaction between the acoustic field and the particles, and drives the particles towards areas of low acoustophoretic potential. Acoustophoretic assembly shows potential for a wide range of applications, including organizing filler materials in composites, creating metamaterials, and fabricating functional biological tissue. However, the method has not yet been incorporated into large-scale manufacturing processes. One barrier is the incomplete understanding of the assembly process. While an ideal final pattern geometry can be calculated from the acoustic field and the material properties, there are currently no widespread metrics for measuring the progress of the pattern formation. As a result, it is difficult to know how long the acoustic field should be applied during manufacturing.

Our approach uses the local particle concentration to model the acoustophoretic assembly process. When the acoustic field is applied, the acoustophoretic patterns coalesce as a whole from the initial state of randomly dispersed particles. Over time, the pattern becomes more distinct as the particles become more tightly grouped together. Thus, the process of acoustophoretic assembly can be considered a change in the local concentration of particles.

We show that an expression for the time-dependent local particle concentration can be derived from the force balance on the particles and a control volume analysis. The analysis is applied to microspheres in a planar acoustic standing wave, and an analytical expression is obtained. To validate the theoretical results, experiments were carried out using polystyrene microspheres in a glycerol-water mixture.

As expected, the particle concentration increases over time at regions with the lowest acoustophoretic potential, while the concentration decreases at regions with the highest acoustophoretic potential. We use the local concentration to define measurements for the quality of the assembled microsphere pattern. When the acoustic field is initially applied, the quality of the pattern changes quickly. At longer times, the quality of the pattern plateaus, and there is a diminishing return to pattern quality with each additional unit of time. This suggests that a cut-off time for pattern assembly can be implemented based on the acoustic and material properties.
Online Development Plan for an Applied Thermodynamics Course
Authors: Fadda Dani , Vinay Roopa , Rios Oziel
Published: February 2024

Online course development in higher education requires careful planning by faculty and instructional designers so materials are offered in a pre-meditated and thought-out way. An applied thermodynamics class is developed for online offering in the Fall semester of 2023 using the backward design method. This method allows faculty to create a development plan for their course before creating online content. The purpose of this paper is to illustrate that developing classes for online delivery requires careful attention to best practices that can capture the student’s attention and enhance their learning experience. The outcome of this work is a structured design experience, which is preferred and completely different from the rush to online teaching, which occurred during the COVID-19 pandemic.
Measurements of Natural Ventilation Within a Model Sports Stadium Using Magnetic Resonance Imaging and Planar Laser Induced Fluorescence
Authors: Ellwein Bryn , Gehl Jack , Iliff Scott , Ederle Pierce , Benson Michael , Banko Andrew
Published: February 2024

The natural ventilation dynamics of a model sports stadium are investigated experimentally. Specifically, a laboratory scale idealized sports stadium model is considered with generic ventilation features such as an asymmetric roof opening, roof slits, and entrance and egress tunnels. Time-resolved 2D concentration measurements external to the stadium are conducted using planar laser induced fluorescence (PLIF). Time-averaged 3D measurements of the flow velocity field internal and external to the stadium are performed using magnetic resonance imaging techniques. Both experimental techniques utilize the same water channel facility operated at fully turbulent Reynolds numbers based on the stadium height. A passive scalar contaminant is injected in the vicinity of the stadium to understand how contaminant infiltrates and exfiltrates the structure. The freestream wind angle is varied to quantify how alignment of various geometric features with the prevailing wind direction alters the internal flow structure within the stadium and couples to the contaminant transport. Results show that both the time-averaged and time-resolved concentration fields exhibit important sensitivity to the wind direction. The conclusions suggest that the novel combination of laser-based and medical imaging techniques provides a unique means to understand complex natural ventilation patterns with application to urban air quality and emergency response.
Singularity Based Method for Small Perturbation Unsteady Aerodynamics Using Higher Fidelity Steady State Pressure Profiles
Authors: Bottai Auriane , Jonson Michael L. , Campbell Robert L.
Published: February 2024

A low-cost, singularity-based method that builds upon the classic potential flow solution procedures is presented in this paper. The classic potential flow solution method distributes elementary solutions to the Laplace’s equation such as sources, vortices or doublets, on the aerodynamic surface. The strengths of those singularities are calculated to satisfy the non-penetration boundary condition and the flow smoothness at the trailing edge. The potential flow predictions are improved to include some compressibility and viscous effects by superposing additional singularities, which strengths are computed to match pressure profiles obtained from a higher resolution conmputational fluid dynamics (CFD) solver. Four variants of the procedure are presented and discussed. Classic potential solution methods can be based on the camber-line (e.g. Lumped Vortex Method in 2D for airfoil) or on the actual airfoil (respectively wing) surface (e.g. source-double panel method). Likewise, the four variants differ by the types of singularities used and/or the aerodynamic surface where the boundary condition is applied: Method 1 optimizes the camber-line shape so that when distributing discrete vortices along that curve, the correct pressure jump across it is obtained. Method 2 duplicates and offsets the geometric camber-line into an “upper” and a “lower” camber curves. Singularities are then distributed on those curves to match the pressure distribution across the airfoil upper and lower surfaces. Method 3 overloads the airfoil surface panels with multiple singularities to meet the pressure requirements. Finally, Method 4 combines continous and discrete singularities to achieve that goal. The methods are surveyed upon three airfoils: NACA006 (thin, symmetric airfoil), NACA4412 (thin, cambered airfoil) and a two-element airfoil, S207. The methods are compared in terms of accuracy in predicting pressure coefficient, aerodynamic loads and applicability for future unsteady simulations. Based on this steady-state survey, Method 4 is the most accurate and stable, with the appropriate choice of singularities. One key element for small perturbation analysis is to capture accurately the reference position, particularly the mean wake on which the vortices are shed, which method 4 is found to be capable of predicting.
Prediction of Delamination Location in Composite Structures With Different Ply Orientations: A Framework Integrating Finite Element Simulation and Deep Learning
Authors: He Junyan , Zhuang Linqi , Chaurasia Adarsh , Najafi Ali
Published: February 2024

In this paper, a framework integrating guided-wave-based finite element (FE) simulation and deep learning is developed to predict the location of internal delamination within a composite plate with different layup configurations. The data needed for training the prediction model are obtained through guided-wave-based FE simulations. Convolutional neural network (CNN) models are then built and trained to predict the location of the existing delamination. The possibility of using transfer learning is explored to account for composite plates with different layup combinations while minimizing additional data needed for CNN model training. It is found that once a baseline CNN model is trained by the data extracted from a specific composite layup case, transfer learning can significantly reduce the amount of data required to achieve similar levels of prediction accuracy for other scenarios with different layup orientations, thus greatly improving the efficiency and versatility of the proposed framework.
An Experimental Investigation of the Relationship Between Evaporator and Condenser Sizes With Oscillating Heat Pipe Start-Up
Authors: Miesner Spencer , Bautista Neyda , Wolk Kieran , Furst Ben , Daimaru Takuro , Sunada Eric , Roberts Scott , Bellardo John , Kuo Jim
Published: February 2024

Oscillating Heat Pipes (OHPs) are unique two-phase heat transfer devices with many advantages over standard and more widely adopted thermal control devices. Specifically, OHPs are able to operate passively, over a wide temperature range, and under high heat fluxes, with few design constraints. OHPs operate based on the process of evaporating and condensing a working fluid on opposite ends of a series of serpentine channels. The pressure difference causes an oscillating behavior of the fluid to travel along the direction of the channels enabling a high heat transfer rate. The capability of this technology has garnered much attention and interest for a variety of applications in different fields. While as a thermal management device, OHP technology shows much promise, there is still much to be understood about the fundamental principles of its operation. One of the most important aspects of OHP operation that is still not well understood is the phenomena known as “start-up”. Start-up is when the proper conditions of an OHP are created such that the operating, oscillatory process of an OHP is enabled to begin. In this work, experimental testing is performed to investigate the relationship between evaporator and condenser length on OHP start-up. In this study, combinations of small, medium, and large length evaporators and condensers were used on a 42-turn OHP with 1 mm square channels, charged with R134a to 50% fill ratio with the goal to quantify the minimum heat that would initiate start-up. Before this test could be performed, issues in consistency of the start-up of OHP had to be resolved. A method to “reset” the liquid-vapor distribution to overcome any adverse history from previous OHP operation developed is discussed. Then, a zero-heat input method of confirming a liquid-vapor distribution favorable to start-up is outlined. After developing this method to achieve a consistent start-up heat input in the OHP, tests were performed for nine different configurations of large, medium, and small evaporator and condensers, to determine their relationship with the minimum heat required to start-up an OHP. It was observed that both the size of the evaporator and condenser both influence the start-up heat load. That is, a large condenser and evaporator can reduce the heat load required to start-up. Additionally, the size of a condenser is much more influential than the size of the evaporator. The overarching discovery is that the process of start-up relies heavily on the history of the OHP i.e., the initial liquid-vapor distribution of the working fluid in the channels. In measuring start-up, it is important to recognize and address how the current state of the OHP can lead to inconsistent results.
Real Time Tire Wear Detection Using Intelligent Tires
Authors: Gupta Utkarsh , Gorantiwar Anish , Taheri Saied
Published: February 2024

Tires, the only vehicle component in contact with the road, are crucial in determining vehicle dynamics. However, as the tires travel substantially, different wear patterns such as feather, spotty, and camber wear are introduced in different parts of the tire’s tread due to contact with the road surface, improper tire inflation pressure, and tire alignment issues. This tire wear phenomenon affects vehicle performance and is detrimental to vehicle-road safety. This research has developed a framework for tire wear classification based on the “Intelligent Tires” concept. This intelligent tire comprises tri-axis accelerometers mounted on the tire’s inner liner for data corresponding to the tire-road contact interface. A vehicle was instrumented with different proprioceptive and exteroceptive sensors for testing and data collection. Tires with different tread depths have been tested under various test conditions of velocity, tire inflation pressure, road surface, and tire normal load. Multiple signal processing techniques in time, frequency, and spatial domains have been leveraged for feature extraction. These features serve as inputs to machine learning based classification algorithms to distinguish between normal and worn-out tires. Thus, the developed system capitalizes on intelligent tire data to predict the state of the tire as normal or worn-out, with real-time capabilities.
A Causal Approach to Model Validation and Calibration
Authors: Mandelli Diego , Gonzales Ronald , Wang Congjian , Abdo Mohammad , Welker Zachary , Balestra Paolo , Qin Sunming , Petrov Victor
Published: February 2024

All current developed methods for model validation are based on standard statistical analysis (to measure statistical differences between data populations) or machine learning (to identify response surface from data) methods. Both methods have to be purely data driven, that is they provide quantitative comparison measures between data sets (e.g., simulated vs. measured data) without explicitly considering the hypothesis behind them (e.g., boundary conditions) and the structure of the employed models. This can generate the erroneous conclusion that, when two data populations are close enough, the models that have generated them are similar. In addition, when simulated and experimental data differ beyond the acceptance criteria, model calibration techniques are used to tweak simulation model parameters to reduce the gap between simulated and experimental data. This gives the false expectation that a simulation model matches reality. The goal of this paper is to move away from current purely data-driven methods for validation and calibration toward more robust model-driven methods based on causal inference. The presented methods capture the causal relationships between data elements (e.g., simulated and experimental data) rather than looking at their associations, and they employ these relationships to measure differences between simulated and measured data. These causal differences then directly inform the calibration process rather than relying on the analyst educated guess.
Enhanced Chaotic Transition Prediction Using Hierarchical Clustering for the Lorenz System
Authors: Monir Solmaz Seyed , Hu Juhua , Tribelhorn Ben , Dillon Heather E.
Published: February 2024

In this research, we propose a novel way using unsupervised machine learning to improve the accuracy of predicting chaotic transitions in natural convection systems. Previous work has focused on the application of machine learning methods to natural convection systems for understanding turbulent convection transitions. We build on the prior work using the Lorenz system to investigate the potential of unsupervised machine learning models without expert inputs. The Lorenz system was selected due to its relatively simple equations and well-documented chaotic behavior. The Lorenz equations are a dynamic system for natural convection that are represented by a coupled system of ordinary differential equations.

Prior work had confirmed that clustering can predict transitions for this system, but the accuracy of predicting transitions could be improved. The prior studies had analyzed eight, expert-chosen features focused on descriptive statistics of the spectral density for the raw inputs to a machine learning algorithm. Our research team modified the prior machine learning methods to cover a large range of geometry and fluid parameters with high accuracy using only images of time series plots as the input to the algorithm. The images are phase plots consistent with those commonly used to observe the Lorenz system’s strange attractors. To account for a large range of geometry and fluid parameters, we converted high-dimensional time series data to phase plot images. This allowed us to capture intricate details within the data that might be missed using prior approaches. We then use deep neural networks to extract low-dimensional features for clustering, allowing us to identify hidden patterns and structures within the data.

This work builds on prior research that used k-means++ clustering to predict behavior in natural convection systems. The approach for this work goes beyond traditional flat clustering methods by using a convolutional neural network and density-based clustering with varying minimum cluster sizes to improve accuracy. The new method has also reduced the bias associated with selecting Rayleigh ratio values, improving the accuracy and reliability of our results. The improved method does not rely on expert selected statistical features either, a significant advantage for adapting the method to other natural convection systems.

The results are visually represented through histograms that show the key transitions in the chaotic system. The research team confirmed that the density-based clustering is a more efficient and accurate machine learning algorithm for this problem. The method presented in this paper also incorporates additional validation steps to ensure the accuracy and reliability of the results. The new method provides more detailed insights into the chaotic behavior of the Lorenz system. This has important implications for a range of fields, including natural convection, meteorology, fluid dynamics, and chaos theory.
RISE-Like Saturated Control for Non-Smooth and Switched Non-Linear Systems
Authors: Basyal Sujata , Ting Jonathan , Allen Brendon C.
Published: February 2024

A focus of decades of research has been to develop nonlinear control strategies to compensate for unstructured terms in a dynamic model that can be bounded by constants. Both continuous and discontinuous controllers have been developed; however, these controllers are limited to certain classes of smooth nonlinear systems, contain unsaturated functions of the system’s states, and/or are prone to chattering. An open problem is the development of chatter-mitigating and saturated controllers for a wide class of dynamic models, that compensate for uncertain terms in the dynamic model. In this paper, a continuous controller, that can be used for a wide range of nonsmooth and switched systems, is developed. To enable uncertainty rejection, a sliding mode (SM) term is included in a filtered tracking error but not in the controller itself. In addition to the filtered tracking error, an adaptive estimate is developed to compensate for the unknown control effectiveness matrix in the dynamics. Furthermore, the controller is designed to be saturated to increase the feasibility of the control system. A Lyapunov-like stability analysis is performed to prove that the proposed controller yields uniform trajectory tracking to an ultimate bound.
Evaluation of Myotubes Orientation Cultured on Scaffold Film by Micromarkers Matrix
Authors: Hashimoto Shigehiro , Sakai Shusei , Saito Shunsuke
Published: February 2024

A cell culture scaffold of elastic thin film with a micro-markers matrix on the back was prepared to evaluate myotubes contraction orientation. A matrix pattern of micromarkers (diameter 4 μm, height 2 μm, interval 30 μm) was fabricated on the back of a polydimethylsiloxane thin film (thickness 6 μm) using photolithography. The direction of the periodic movement of the micromarkers synchronized with the electrical pulses applied periodically to the medium via electrodes was determined from video-image analysis using optical microscopy. As reference data, the distribution of myotubes in the longitudinal direction was simultaneously determined from the microscopic image. Directional distributions of both micro-marker motion and myotube images in selected compartments were compared. Experimental results demonstrate that the functional orientation of myotubes can be assessed in vitro by tracking the direction of movement of matrix-patterned micromarkers.
The Failure Mechanism in CFRP Cross-Ply Curved Composite Laminates
Authors: Çevik Ahmet , Çöker Demirkan
Published: February 2024

This paper presents the experimental and numerical investigation of damage behavior in cross-ply curved composite laminates under transverse loading perpendicular to the horizontal arm. In the experiment, a high-speed camera is used to monitor the dynamic crack event occurring in the curved region of the specimens. The crack tip speed history is extracted from the high-speed camera images. High-speed camera observation reveals that the failure occurs in a sequential manner, starting from the inner side of the curved region and the subsequent failures occur in the outer side of the previous one. The digital image correlation (DIC) technique is used to obtain the strain field over the curved region during the experiment. The strain concentration is observed in the inner side of the curved region. The fractography is conducted with tested specimens using a digital microscope. Fiber breakage, fragmented matrix crack regions, delaminations, crack kinking and meandering crack path are observed in the micrographs of the post-mortem specimens. Explicit finite element analysis is conducted using ABAQUS/Explicit. To find the minimum required time step for the analysis, the modal analysis is carried out. To predict the matrix cracks observed in the micrographs, the user subroutine for LaRC04 failure criterion is implemented to ABAQUS. The cohesive zone method is used to simulate the delamination failure mode. The strength study is carried out by changing the transverse strength and interlaminar tensile strength (ILTS) of the laminae.
A CO2 Emissions Life Cycle Assessment of Additive and Conventional Manufacturing Based Lightweight Design in the Automotive
Authors: Dalpadulo Enrico , Pini Fabio , Leali Francesco
Published: February 2024

Within the road to decarbonization scenario, it becomes increasingly central to analyze the sources of emissions from different perspectives and select the more sustainable design approach for the development of new products. Among many sectors, lightweighting can reduce costs related to energy and fuel consumption. Potentially, it is also possible to reduce emissions, both for air and land transport, especially considering vehicles in the context of electrification and green transition. This paper provides an approach for the quantitative estimation of CO2 emissions along the lightweight design of vehicles components. The approach is based on a Life Cycle Assessment (LCA), which includes aspects ranging from product design and production to the use phase, and possible upgrading and recycling. Two lightweight design strategies are considered, using either conventional or unconventional technologies, which are respectively based on Design for Machining and Design for Additive Manufacturing. These methods can be scaled in high-end sectors, as both are characterized by high flexibility and customization, which allow the implementation of lightweight designs for small batch sizes. An automotive component is used as a case study, performing the product-process design based on Computer-Aided Technologies (CAX) for both approaches. The CO2 assessment is performed, considering all the drivers relating to the stages of the product life cycle. Additive Manufacturing is confirmed as more energy intensive, but the additional mass saving over the vehicle use phase returns emissions reduction compared to the whole life cycle.
Human Modelling and Design of Custom-Made Knee Implants: Definition of an Automatic Procedure
Authors: Ghidotti Anna , Vitali Andrea , Regazzoni Daniele , Rizzi Caterina
Published: February 2024

Total knee arthroplasty (TKA) is the surgical procedure of choice for end-stage osteoarthritis. Even if it is widely performed, there is still dissatisfaction with the surgical procedure in about 20–30% of patients. Factors such as malalignment of the implant and the size of the components have been reported as the most common reasons for post-operative complaints. Custom-made prostheses have been introduced to replicate each individual joint geometry and kinematics. In this study, a novel approach is proposed to automate custom-made knee implant design. The aim is to create a pipeline, where customized implants can be designed automatically for a large number of patients, reducing the time for design. Firstly, a manual procedure for designing the implant is defined. The lower part of the femur is extruded with a thickness that matches with the natural anatomy of the patient and cut planes are used to design the customized femoral implant. Then, an automatic procedure is developed. For the purpose, a statistical shape model of femur, based on 33 patients, is created and employed. The procedure is tested with 5 study cases showing the potential of the methodology. Results will be furtherly validated on a larger scale.
Experimental Determination of Electromechanical Coupling Matrices for Active Vibration Control of Composite Structures
Authors: Hameury Celia , Ferrari Giovanni , Balasubramanian Prabakaran , M. P. Silva Tarcisio , Amabili Marco , Buabdulla Abdulaziz , Franchini Giulio
Published: February 2024

Multiple input multiple output active vibration control architectures pose some common challenges to designers, such as the optimization of the number and of the position of sensors and actuators, and of the controller parameters. At a more fundamental level, however, the modeling of the electromechanical structure under control is a preliminary step necessary to perform all the optimizations described above. While some control algorithms try to prescind from a detailed modeling, some models are always required to simulate numerically the performance of the control.

Finite element or reduced order models are often employed to simulate and to estimate the relationship between electrical and mechanical inputs and outputs. However, building these models can rapidly become onerous, even for relatively simple bidimensional structures, for example composite beams, plates and shells. Therefore, an experimental method was developed for the determination of the electromechanical coupling matrices. Simple experimental modal analyses were performed to obtain parameters such as natural frequencies, damping ratios, modal shapes and frequency response functions. Afterwards, a least square error algorithm, implemented in MATLAB and in Python, was used to determine the matrices that correlate transducer voltages, generalized coordinates and modal coordinates. Modal coordinates are especially useful for the construction of multiple input multiple output active vibration control algorithms that operate in the modal space; however, in these cases the inversion or the pseudo-inversion of the participation matrices had to be performed as well.

The proposed method was tested on one cantilever sandwich beam and on one sandwich plate with free edges, equipped with two collocated couples of sensors and actuators and four non-collocated couples of sensors and actuators respectively. In particular, piezoelectric patches operating in flexural mode were employed as transducers. The method simulated correctly the uncontrolled electromechanical response of either structure, and its performance in this regard compared favorably with that of the finite element method.

Afterwards, multiple input, multiple output positive position feedback active vibration control algorithms based on these participation matrices were built for either system, and tuned according to established method described in the relevant literature. In either case, a number of modes double with respect to that of the couples of installed actuators and sensors was controlled satisfactorily. The controllers resulted stable and negligible spillover on uncontrolled modes was observed.
The Mechanical and Functional Behavior of Nitinol-Reinforced PLA Composites
Authors: Srinivas Pooja , Abu Al-Rub Rashid K. , Barsoum Imad , Zaki Wael
Published: February 2024

The current paper proposes the addition of nitinol at varying volume percentages (3, 10, and 15 vol%) to polylactic acid (PLA) matrix to study its effect on mechanical properties. In recent years, new types of PLA composites have been developed that incorporate nanomaterials such as CNTs, graphene, and other materials such as wood and kenaf fibers. Nitinol is an alloy with excellent shape memory and superelastic properties, which makes it highly desirable for use in biomedical and aerospace industries. In this work, the dissolution method was used to prepare PLA-Nitinol composite feedstock, which was extruded to fabricate composite filaments. The filaments were used in fused deposition modeling (FDM) printing to create cylindrical and cubic composite green samples. X-ray diffraction (XRD), scanning electron microscopy (SEM), and differential scanning calorimetry (DSC) were utilized to characterize the fabricated samples. Mechanical and functional behavior characterizations were carried out through quasi-static compression tests using a universal testing machine (UTM). The results show that composites of PLA and Nitinol exhibit improved mechanical properties compared to pure PLA, making them useful for a wide range of applications. Further research and development can result in new, highly functional materials with a broad range of potential applications. The current research paves the way for the development of printing metal-enriched filaments and get 100% metal parts using FDM technique.
Revisiting and Improving Pipe Wall Transmission Loss Estimation for Control Valve Noise Prediction
Authors: Eilers Daniel , Fagerlund Allen
Published: February 2024

The prediction of noise in industrial control valve applications is required to select the correct control valve design for the end user to keep their employees and equipment safe as well as meet any local noise ordinances. In a piping system any noise generated by a valve or other component will propagate within the downstream pipe. This internal acoustic field will couple to the pipe wall and cause it to vibrate, which in turn causes external radiation. The difference between the internal and external sound fields is called transmission loss. The estimation of the transmission loss can be a major contributor to the accuracy of noise prediction methods.

The theory that is the basis of the pipe wall transmission loss calculation in the international standard IEC 60534-8-3 Control Valve Aerodynamic Noise Prediction Method is reviewed and reanalyzed to correct an error. Then critical variables such as uniform mean flow, internal acoustic modal density, and structural modal density are reevaluated.

Based on the complete reanalysis, suggestions for improvements to the calculation methodology used in noise predictions are provided and the estimated change is quantified. Experimental data taken in a flow system designed to measure control valve noise was used to inspect a few variables and the overall prediction methodology. Future research areas are also suggested.
Impact on Wrinkled Graphene
Authors: Flanagan Asher , Park Jungkyu
Published: February 2024

We investigated wrinkle-free single layer graphene and graphene with various wrinkles to examine their fracture toughness during an impact with a silver nanoparticle using molecular dynamics simulations. The interaction between silver atoms is modeled using Embedded Atom Model (EAM) potential, while the interaction between carbon atoms in the graphene was modeled using 2nd generation Reactive Empirical Bond Order (REBO) potential. The interaction between silver atoms and carbon atoms is modeled by using the Lennard-Jones potential. The graphene is equilibrated at 300K. Three different amplitudes (0.4 nm, 2 nm, and 2.5 nm) and two different wavelengths (4 nm and 17 nm) are selected for the generation of wrinkles in graphene. Our simulations revealed that wrinkled graphene absorbs more kinetic energies of a silver particle during impact. The highest impact energy absorbed during the impact was 33 keV when the wrinkle has the wavelength of 17 nm and the amplitude of 2.5 nm. This indicates that wrinkled graphene possesses higher toughness compared to wrinkle-free graphene layers. The toughness against high-speed impact is shown to increase with an increase in wrinkle size in the graphene layer. In the case of wrinkled graphene, the kinetic energy of a silver particle was completely absorbed by the graphene when the particle failed to fracture the graphene layer while wrinkle-free graphene bounced back the silver particle with a finite amount of velocity when it couldn’t break the graphene layer. The results obtained from our research study will contribute to the accelerated development of futuristic, strong, lightweight materials for military applications.
A Computational Study of Sustainable Hydrogen Production Using High-Pressure Modular Gasifier
Authors: Chanda Sumit , Tasnim Anika Farhat , Reyes Daniel , Choudhuri Ahsan , Islam Nawshad Arslan
Published: February 2024

The article presents a computational study of a high-pressure gasifier using biomass and Municipal Solid Waste (MSW). The current work investigates the feasibility of using a high-pressure gasifier system for biomass and MSW gasification and understanding the gasification pathways for improved Hydrogen (H2) yield. A computational model for a simple vertically mounted fixed bed high-pressure gasifier was developed to achieve the current goal. Biomass and MSW compositions obtained from various US locations are used to investigate the effects of feedstock in maximizing the H2 yield. The primary goal is to characterize the gasifier operation at different operating temperatures and pressures. Air and Oxygen are used as gasifying agents. The operating temperature and the inlet pressure are varied between 400°K to 1100°K and 1 to 5 bar, respectively. The MSW samples gave better H2 yield at 0.3–0.35 equivalence ratios (ER) when using air as the gasification agent. Increasing the temperature promoted steam gasification reactions and produced more H2, but at higher temperatures, that effect diminished. Increasing pressure reduced the H2 yield in the beginning but started to improve the yield at higher pressures. An ER below 0.3 is recommended for oxygen-blown gasification to improve H2 yield.
Field Demonstration of Pinhole Insulation Technology for Energy Efficiency Retrofits in Connecticut
Authors: Chacko Celia , Gorthala Ravi , Patil Prathamesh
Published: February 2024

Building energy efficiency retrofits are a valuable tool to minimize household energy consumption, improve energy affordability and reduce carbon footprints. In Connecticut, low-and-moderate income households deal with challenges in sustaining their energy needs at a greater severity compared to the average household. Adding insulation to buildings with minimal wall insulation can significantly improve building envelopes and minimize heat losses to reduce energy consumption. This research investigates the use of a new, innovative, minimally invasive insulation technology for installing closed-cell spray polyurethane foam (SPF) into exterior wall cavities. SPF is a versatile insulating material known for its low thermal conductivity, density, and its high thermal resistance value, also known as its R-value. The technology is demonstrated in a low-income multifamily home pilot study in Connecticut. The technology effectiveness is validated through in-situ wall thermal measurements and energy modelling with EnergyPlus. The primary objective of this study is to determine the improvement in the thermal performance of the Pinhole Insulation® technology. Preliminary results have demonstrated an increase in in-situ Rvalue of 3.5 and heating savings of 19.30% for the shallow cavity site. This corresponds to annual savings of $3,215 for the site with a simple payback of 11.8 years.
Experimental Characterization of a Centrifugal Compressor in Second Quadrant Operation
Authors: Serena Alberto , Bakken Lars E.
Published: February 2024

The flow unsteadiness in turbomachines, presenting a characteristic behaviour, requires a deep understanding of the underlying flow fundamentals, a careful analysis through advanced experimental methods and a clear distinction on how the surrounding system might lead to instabilities.

A sustained deep surge condition might force a compressor into second quadrant operation, which can occur intermittently during surge cycles or continuously as a result of system malfunction or fast ESD with low inertia machines. In this unusual operating area, compressor system wise, the characteristic is often modelled with a simple approach, as a passive, valve-like component. Aerodynamically wise, corrections are possible accounting for specific phenomena, as incidence losses and blockage.

In similar researches, a booster is forcing a stable reverse flow, with the instrumentation rotated according to the expected direction. In this study, this is provided by a pressurized tank, representing a tuneable discharge volume as well as process equipment malfunction, i.e., check valve failure or leakage.

The test matrix covers a range of discharge pressures, flow rates and rotational speeds, both at constant-imposed speed and with no torque applied, at locked or free shaft, to investigate the effect of different parameters and phenomena.

The results document the characteristics under different operating conditions. The key contribution is the definition of a suitable approach for the collection of relevant and reliable data measurement, which lays an important foundation for further development of dynamic models for compressor system behaviour and allows to properly reduce complexity of surge protection devices, for operation in more favourable conditions.
A New Deviation Propagation Model Combining Dimensional Deviation and Welding Deformation of Panel Structures With High Local Stiffness
Authors: Gao Chang , Yu Haidong , Gu Bin
Published: February 2024

The geometrical accuracy of panel structures jointed by friction stir welding (FSW) is affected by dimensional deviation and assembly deformation, which leads to the assembly deviation difficult to be predicted and traced. The local stiffness of panel structures enhances significantly with the increase of thickness of the structures, and the deformation concentrates in the local assembly area. In this paper, a new deviation propagation model for panel structures considering dimensional deviation and local welding deformation is proposed. The dimensional deviations with multi-tolerance coupling effect are characterized by small displacement torsor (SDT). A virtual feature is constructed for the local welding deformation of panel structure. The deviation propagation model of panel structures is established. The contribution index of each deviation source to the assembly deviation is proposed, and the influence of dimensional deviation and assembly deformation on the geometric accuracy of assembly may be revealed. The FSW experiment is carried out on two plates and the reasonability of the deviation model is verified by comparing with the experimental data. The contribution of dimensional deviation and welding deformation is solved based on the deviation propagation model. The proposed deviation propagation model combining dimensional deviation and welding deformation may be useful for design of structural parameters and assembly process of panel structures.
Development and Implementation of an Augmented Reality Introductory Experience for Mechanical Engineering Freshman Students
Authors: Kay Danae , Koenig Zachary , Muci-Küchler Karim H.
Published: February 2024

Industry 4.0 is driving innovation at companies and in education. As more Industry 4.0 tools and technologies become accessible, engineering programs need to expose their students to these tools and technologies to better equip them to start their engineering careers. In support of this goal, the Mechanical Engineering (ME) program at Texas State University (TXST) included basic practical experiences involving selected Industry 4.0 tools in a freshman-level lab. One of those experiences uses Microsoft’s HoloLens 2 to introduce students to Augmented Reality (AR). Since AR devices are an emerging technology, the software applications currently available for devices like the HoloLens 2 are not cost-effective for implementing them in most academic courses or labs. To overcome this challenge, the ME program at TXST developed an AR application for the freshman-level lab using the Unity development platform. For that purpose, the CAD model of a product was created using SolidWorks, converted using Blender, and brought into the AR application that was developed. This paper presents the process and technical challenges of implementing the AR experience in the freshman-level lab and discusses student feedback and the plans for improving the application in the future. The authors hope that this information is useful for other mechanical engineering undergraduate programs that want to include AR experiences in the curriculum.
Predictive Control of the KINOVA Gen3 Robotic Manipulator Using a Nonlinear Model
Authors: Tereda Amanuel Abrdo , Yi Sun
Published: February 2024

In contemporary manufacturing processes, reliable but efficient pick-and-place robots are frequently used. The automation and optimization of the pick and place procedures utilizing various path-planning approaches thereby support the expansion of application areas. Yet, the design of a controller faces significant difficulties due to the nonlinearities inherent in robotic manipulators and the unpredictable nature of the ambient factors. In place of the classic model predictive control (MPC), this paper presents the application of the Nonlinear Model Predictive Controller (NLMPC) as an acceptable control mechanism for real-time optimization and robust stability of the KINOVA Gen3 robotic arm. The developed NLMPC-based method ensures that the robotic arm does not run into obstacles in the workplace or with itself while reaching, gripping, selecting, and placing the necessary items. To acquire the control input trajectory, the optimization in NLMPC is solved repeatedly. When input constraints are available, the modeled system tracks reference trajectories to achieve the aim of recognizing and organizing distinct objects. After the NLMPC is successfully developed, a simulation environment is built and finally brought to life by combining all the processes into one using a MATLAB Stateflow chart.
A Sustainable Solution: Preparation of Nanocellulose Reinforced Brewer’s Spent Grain as a Fully Bio-Based 3D Printable Composite
Authors: Al Tamimi Zainab , Chen Longyan , Ji Xiaoxu , Piovesan Davide , Madura Allen R. , Lehotsky Jacob
Published: February 2024

Brewer’s spent grain (BSG) is the largest waste generated from the brewing industry, accounting for ∼39 million tons yearly. Currently, the material has limited use for feeding farm animals and presents minimal market value. There has been a growing interest in the potential recycling of BSG as a manufacturing material. In this study, we are reporting the preparation of a fully bio-based 3D printable biocomposite based on recycled BSG material. The biocomposite is composed of BSG fine particles that are blended with nanofibrillated cellulose (NFC) hydrogel. Cross-linking agent glutaraldehyde was used to improve the viscosity of the biocomposite. Our results showed the composite is a paste-like material and adaptable for 3D printing. Scanning electron microscopy (SEM) and mechanical testing were used to evaluate the surface morphology and mechanical resistance of biocomposite, respectively. A prototype for food spoilage monitoring based on the BSG-NFC biocomposite was demonstrated. It is expected that this fully bio-based composite will be a low-cost, recyclable, and sustainable 3D bio-printing material for biological applications.
Long-Term Thermal Performance Evaluation of a Novel Energy Pile for Space Heating and Cooling in a Cold Climate
Authors: Beragama Jathunge Charaka , Darbandi Amirhossein , Kim Nayoung , Taslimi Taleghani Sahar , Dworkin Seth B. , Mwesigye Aggrey
Published: February 2024

In cold climates, space heating and domestic hot water production account for a large portion of the building’s energy demand and the related CO2 emissions. To sustainably climatize buildings, renewable energy technologies need to be integrated into building energy systems. The ground source heat pump (GSHP) technology is one such clean energy technologies. The energy pile technology is an excellent alternative to conventional borehole heat exchangers which reduces the cost of GSHP systems substantially. This study numerically investigates the long-term performance of a novel energy pile coupled with a GSHP using realistic building loads for a cold climate. A finite volume-based computational model was developed and thoroughly validated using experimental data from a system in Waterloo, Ontario, Canada. First, three normalized building load profiles were derived using a building energy model for a typical residential house in Calgary, Alberta, Canada. Then a 4-year performance investigation on the performance of the energy pile for the three normalized load profiles was undertaken. In addition, two configurations were considered — one with the pile beneath the basement of the building and another one with the pile at the ground surface level. For the first configuration, results show that the higher heating loads (> 0.4 tons) render the system inoperable for a significant amount of time. Also, the yearly average heating coefficient of performance (COP) decreased over the years while the yearly average cooling COP increased. The average ground temperature decreases for all the load cases, indicating ground thermal imbalance. The decrease in ground temperature was 0.08°C/year, 0.1°C/year, and 0.13°C/year for 0.3, 0.4 and 0.6 tons, respectively. The first configuration yields favorable results compared to the second in terms of system operability and thermal performance due to the reduced influence by low ambient temperatures.