bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surface Acoustic Wave (SAW) Force Myography Sensor for Muscle Force Output Identification
Authors: Kohler Michael C. , Voiculescu Ioana , Li Fang 
Published: January 2025

Abstract
Precise measurement of muscle force output is fundamental for evaluating physical performance and overall health. It serves as a direct and reliable indicator of muscle strength and functionality, which are indispensable for everyday activities, athletic performance, and rehabilitation. Data on muscle force output also play a pivotal role in controlling prostheses and exoskeletons. This paper presents an innovative approach to capturing muscle force output using Surface Acoustic Wave (SAW) sensors. While not frequently highlighted in this field, SAW sensors are increasingly valued for their versatility and potential to enable self-powered, wireless devices. This research focuses on a 128° YX-cut LiNbO3-based SAW sensor, used here as a force myography sensor to measure muscle contractions. The findings reveal that SAW sensors offer excellent sensitivity and accuracy in tracking muscle activities, potentially surpassing traditional methods like strain gauge measurements and conventional electromyography (EMG).
Electric Propulsion Powerplant Modeling and Simulation for Investigation of Cyclic Rapid Large-Amplitude Transients
Authors: Trejos Miguel , Xiros Nikolaos I. , Aktosun Erdem , Georgiou Ioannis 
Published: January 2025

Abstract
With the expansion of the Arctic and Northwest Passage, the use of icebreaking and ice class vessels outfitted with electric propulsion becomes more and more common. The transportation of cargo following this route offers economic and logistical opportunities. The Northern Sea Route (NSR) is a much shorter marine passage between the Atlantic and Pacific Oceans. Historically being used by several countries for the purposes of resource extraction, the NSR reduces the travel distances by 35–60%. The flexibility of electric propulsion systems makes them ideal for navigation through ice infested waters where rapid, large amplitude transients may arise. In view of the fact that there is often a lack of extensive experimental data in the literature for how these systems operate in changing conditions such as in Artic and Polar regions, simulations are an important resource for analyzing the effects on propulsion operation. The major purpose of this work is to construct a simulation for the investigation of the dynamics of the diesel-electric propulsion system when receiving a large transient input. To this end, the transients are modeled as large, periodic rectangular pulses with noise superimposed over to simulate random fluctuations. The propulsion outfit considered includes at least two screws powered by synchronous three-phase motors which are driven by Variable-Frequency Drives. The integrated power system of the vessel consists of several generators operating in drooped or isochronous mode and driven by a diesel engine prime mover. Single-phase equivalent circuits are employed for the synchronous machines based on a quasi-steady-state approximation. This as well as other approaches are examined through mathematical modeling and dynamic simulation runs.
Simulation Model Development and Calibration of Surface Watercraft Dynamics Using Neural Networks and Machine Learning
Authors: Freels Jonathan Parker , Xiros Nikolaos , Trejos Miguel A. 
Published: January 2025

Abstract
The scale model of a surface watercraft with electric propulsion by a dc motor, propeller and rudder for steering was built. A simulation model that can reproduce motion patterns of the boat with sufficient fidelity in various sets of conditions was developed by compounding data sets acquired through various trials and controlled experiments with established governing principles of ship theory. The aim was to reduce the number and cost of instrumentation required to calibrate the model, without unacceptably compromising precision or fidelity. In effect, by using knowledge of boat dynamics, a custom grey-box model was built and calibrated. A pair of nonlinear state equations, capturing the dynamic response of the watercraft of interest were formulated derived. The dynamical model can form the foundation on which AI-inspired control approaches for navigation of a single or swarm of boats can be built. In the AI-inspired control synthesis approach, the control problem is tackled by concept of virtual physics applying on the boat and resulting in motion schemes that are beneficial in particular applications, e.g. homing or visiting waypoints. The design of such controllers involves cancellation of actual dynamics governing the boat’s motion complies and then implementation of laws of virtual (i.e. artificial) physics. In the present work, as an initial step in this direction, a series of open-loop tests enable us to identify and formulate the dynamics governing the watercraft’s motion.
A Symbolic-Numerical Approach to Suspension Kinematics and Compliance Analysis
Authors: Larcher Matteo , Stocco Davide , Tomasi Matteo , Biral Francesco 
Published: January 2025

Abstract
This paper presents an innovative method for the analysis and simulation of suspension systems through either symbolic or mixed symbolic-numeric computation, which leads to the development of a comprehensive analytical model for the Kinematics and Compliance (K&C) characteristics. State-of-the-art approaches involve either resource-intensive flexible multi-body dynamics or static K&C maps, however, they come with intrinsic limitations. Flexible multi-body systems require substantial computational resources and are unsuitable for real-time applications, whereas K&C maps need frequent regeneration when suspension set-up changes. The proposed approach, rooted in the finite element method and, more specifically in the direct stiffness method, aims at overcoming these challenges. It seeks to create generic analytical K&C models to be employed with suspensions presenting the same topology. Furthermore, this approach achieves a high level of generalization by also taking into account the compliance of bushings, along with the deformation of relative hard points, chassis, and suspension links.
Two-Scale Co-Simulation Approach for Drop-Test Simulation of Kovan PCB Board
Authors: Shejwal Amogh , Medikonda Sandeep , Lyu Dandan , Sengupta Arkaprabha , Mao Henan , Kumar M. Satish 
Published: January 2025

Abstract
Solder joints in PCBs are typically observed to be the weakest links in the drop impact of most consumer electronics products. A drop-shock analysis and particularly the failure of solder joints involves the modeling of meso-scale solder joints and macro-scale chip packages, which is a typical multi-scale problem. Conventional finite element analysis (FEA) approaches using beam elements for the representation of the solders and the one-way sub-modeling technique cannot offer a high-fidelity solution in a reasonable amount of time. The two-scale co-simulation approach discussed in this study provides an efficient analysis tool to enrich Integrated Circuit (IC) packaging models with detailed solder joints so that complex failure modes of solder joints and corresponding structural responses can be accurately captured.
In this context, a detailed solder joint model of a consumer electronics board has been studied using a multi-scale approach in a drop-test scenario. The local solder joint models are coupled to the large-scale global packaging model without the need for a conformal mesh at the coupling interface, this largely simplifies the workflow in both meshing and analysis and provides the flexibility to vary the characteristics of local solder models without the added cost of changing the global model. Under this proposed co-simulation framework, data exchange between the two explicit jobs (at different scales) occurs at the coupling interface synchronously using the Message Passing Interface (MPI). Additionally, this approach eliminates the constraint on time step variation imposed by a mesh-sensitive explicit analysis. The concurrent solder joint models with much smaller time-step sizes run separately from the global model, and communication happens at every global time step resulting in low overhead cost.
The multi-scale analysis has been carried out using the trace-mapped shell PCB. It has been compared against a trace-mapped solid PCB model and a lumped solid PCB model.
The multiscale results show a good correlation with the solid trace-mapped PCB model thus validating this approach. A detailed HPC scalability study and the dependency on the number of processors on the master and slave processes of a multi-scale analysis have also been discussed in detail.
Deep Learning Enabled Approach for Nonlinear Response Modeling of Piezoelectric Energy Harvesters
Authors: Li Dubai , Liao Yabin , Zhang Ruiyang , Lan Chunbo 
Published: January 2025

Abstract
Piezoelectric energy harvesting has been extensively investigated to provide a sustainable power supply for small-scale devices. Though significant progress has been made in the past two decades, accurate modeling of piezoelectric energy harvesters (PEHs) still remains difficult or usually involves parametric identification from experimental results. This paper explores and leverages deep learning techniques for modeling behaviors of nonlinear PEHs. To this end, we present a deep learning-based surrogate model for nonlinear response analysis of PEHs with high complexity and strong nonlinearity. The key concept is to establish a long short-term memory (LSTM) neural network to capture the dynamic properties of the piezoelectric energy harvesters from limited training data and infer the voltage and power given unseen excitations in a data-driven fashion without the need of conventional time-consuming numerical simulation or parametric identification. In addition, the input and output sequences are preprocessed into stacked structures to reduce the complexity and enhance the feature learning. The performance of the proposed approach was successfully demonstrated through numerical data of a monostable PEH of Duffing stiffness nonlinearity and piezoelectric material nonlinearity. The results indicate that the proposed framework is a promising, reliable and computationally efficient approach for nonlinear response modeling of complex piezoelectric energy harvesters.
Laser-Induced Graphene Heater for DNA Amplification and CRISPR-Cas9 Biosensing
Authors: Zhou Peng , McElroy Amber , Xu Yingming , Simon Terrence , Osborn Mark , Cui Tianhong 
Published: January 2025

Abstract
This paper presents an innovative approach by integrating laser-induced graphene (LIG) as a low-power heater and a CRISPR-Cas9 sensor for efficient DNA amplification and detection. LIG, engineered using a laser-induced carbonization technique on polyimide tape, serves as a rapid heater for isothermal DNA amplification, achieving results within 30 minutes with minimal power consumption. Simultaneously, a CRISPR-Cas9 sensor detects DNA concentrations as low as 16 pM, offering cost-effective and sensitive detection. The combination of LIG heaters and CRISPR-Cas9 sensors streamlines DNA amplification and detection processes, offering substantial advantages over traditional methods in terms of power efficiency, cost effectiveness, and application simplicity. We validated our approach using lateral flow assay technology. Further, a pyrolytic glassy carbon electrode-based electrochemical sensor demonstrates specificity in DNA detection, with a detection limit of 16 pM. This integrated approach holds promise for multiple applications, particularly in nucleic acid diagnostics, showcasing a resource-efficient strategy for DNA amplification and detection in molecular biology research.
An Experimental Study of the Thermal Transport Mechanisms in Porous Media for Thermal Protection Systems
Authors: Hassan Mahedi , Amin M. Ruhul , Li Yaofa 
Published: January 2025

Abstract
Thermal protection systems (TPS) are crucial to atmospheric reentry vehicles to shield the intense heat generated by propulsion systems as they enter the atmosphere of planets. Porous materials, among others, have been extensively used to build TPS due to their advantageous characteristics such as low thermal conductivity, lightweight design, high reliability, and cost-effectiveness. Heat transfer through a porous medium includes combined contributions from conduction along solid matrix, radiation across voids (pores), and conduction through gases filling the voids. Although this qualitative picture of the heat transfer mechanisms is well accepted, a quantitative understanding of the contribution of each individual mechanism is still lacking, primarily due to the complex morphology of the porous materials and the intrinsically coupling nature of different mechanisms across scales. To that end, this study aims to experimentally quantify thermal transport mechanisms in porous materials by creatively isolating individual mechanisms. Model porous media were fabricated from silicon and glass wafers employing microfabrication techniques, which were then tested with a customized thermal test apparatus. The results highlight the dominant contribution of gas conduction to the overall heat transfer in the entire test temperature range. However, as the temperature increases, the contribution from radiation has been observed to increase.
Dynamic Response of a Wind and Base Vibration Driven Linear Galloping Energy Harvester
Authors: Yu Bo 
Published: January 2025

Abstract
This paper presents the responses of a linear galloping energy harvester subjected to combined wind and base excitation. The nondimensionalized equations of the linear galloping energy harvester are presented. Compared with other existing studies on concurrent energy harvester, this study utilizes an implicit mapping method to investigate the system’s response characteristics across various excitation frequencies for a given set of system parameters. The stabilities of the periodic responses are also studied through eigenvalue analysis. Our study reveals the conditions under which stable periodic responses occur, and identifies the critical frequencies that lead to transitions between stable and unstable oscillations. Through time domain comparisons, our predictions are validated with numerical simulations. The displacement and voltage responses are illustrated. The findings provide novel insights into the optimal design of piezoelectric energy harvesters.
Developing a Course on Electric Vehicles Modeling for Mechanical Engineers: Challenges and Experiences
Authors: Das Shuvra 
Published: January 2025

Abstract
There is a world-wide push to transform automobile technologies from traditional fossil-fuel based to one that is based on electric drives. Many automotive companies have launched Electric (EV) and Hybrid Electric vehicles (HEV). These vehicles are more fuel-efficient and environmentally friendly compared to conventional vehicles. Optimizing the power intake in EVs allows the vehicle’s operation to be kept within the range designed for best fuel economy and lowest emission, while the motor/generator system provides additional power input as well as generates electricity using the excessive power from the engine. In the case of hybrid electric vehicles (HEVs) the motor/generator system also recovers the kinetic energy during braking or coasting. All these advantages have attracted worldwide development interests for such vehicles. It has also created a need for engineers working in the automotive industry to develop expertise in these systems as they contribute to the design and manufacturing of EVs and HEVs. The mechanical engineering curriculum needs to adjust to this new reality, and it is imperative that graduates of mechanical engineering programs graduate with a decent understanding and knowledge of EVs and HEVs if they are to be employed by the automotive industry. This course was designed with that need in mind and careful attention was paid to designing the content and focus of this course. It needed to be introductory in nature, yet students needed more than just awareness and gain some skill and confidence in the topic. That is why this course covers all aspects of the EV and HEV technology and every topic discussion is followed by modeling exercises. Simscape, a physical modeling toolbox in Matlab, is used for all the modeling work. The simulation exercises are designed with ample scaffolding so that the students can gain proficiency in using the tool while simultaneously accomplish the modeling task assigned. This paper discusses the course content, the simulation exercises, the challenges, and the lessons learned.
Privacy-Preserving In-Situ Monitoring in Additive Manufacturing Through Hyperdimensional Computing
Authors: Piran Fardin Jalil , Poduval Prathyush P. , Errahmouni Barkam Hamza , Imani Mohsen , Imani Farhad 
Published: January 2025

Abstract
Machine learning (ML) models are used for in-situ monitoring in additive manufacturing (AM) for defect detection. However, sensitive information stored in ML models, such as part designs, is at risk of data leakage due to unauthorized access. To address this, differential privacy (DP) introduces noise into ML, outperforming cryptography, which is slow, and data anonymization, which does not guarantee privacy. While DP enhances privacy, it reduces the precision of defect detection. This paper proposes combining DP with Hyperdimensional Computing (HDC), a brain-inspired model that memorizes training sample information in a large hyperspace, to optimize real-time monitoring in AM while protecting privacy. Adding DP noise to the HDC model protects sensitive information without compromising defect detection accuracy. Our studies demonstrate the effectiveness of this approach in monitoring anomalies, such as overhangs, using high-speed melt pool data analysis. With a privacy budget set at 1, our model achieved an F-score of 94.30%, surpassing traditional models like ResNet50, DenseNet201, EfficientNet B2, and AlexNet, which have performance up to 66%. Thus, the intersection of DP and HDC promises accurate defect detection and protection of sensitive information in AM. The proposed method can also be extended to other AM processes, such as fused filament fabrication.
ADArC: Automated Design Tool for Arduino Circuits
Authors: Wohlers Casey , Jin Yangyang , Negron Andres , Tu Le Cam , Buziba Gabriel , Radhakrishnan Pradeep , Brown David C. 
Published: January 2025

Abstract
Experimentation using microcontrollers such as Arduino is becoming common in several university courses and capstone projects due to their low cost. But students often face challenges with microcontrollers, sensors, and actuators. Novice learners in Mechanical, Electrical, and Robotics Engineering struggle with wiring components, coding, and interpreting circuit results. This hinders their progress and leads to time-consuming troubleshooting. Our tool, called ADArC, Automated Design tool for Arduino Circuits, seeks to alleviate this struggle by offering an intuitive software simulator that supports circuit design and Arduino code generation. Users can use the graphical interface to choose components, have them automatically connected on screen to the Arduino, generate and edit code, as well as run and modify circuit simulations in real time. In a class setting, students showed enthusiasm for this app’s design and accessibility, also praising its efficacy in enhancing their learning experiences. The paper will describe the details of the software.
Multi-Directional Mechanical Property Characterization of Additively Manufactured Metal Utilizing Wavefield Analysis
Authors: Cai Bowen , Sun Chuangchuang , Sullivan Rani , Tian Zhenhua 
Published: January 2025

Abstract
The advancement of additive manufacturing has significantly transformed the production process of metal components. However, the unique challenges associated with layer-by-layer manufacturing result in anisotropy in the microstructure and uneven mechanical properties of additive-manufactured metal products. Traditional testing methods often fall short of providing the precise mechanical performance evaluations required to meet industry standards. This paper introduces an innovative approach that combines a nondestructive Lamb wave sensing system with a wavenumber analysis method to characterize the mechanical properties of 3D-printed metal panels in multiple directions. Our method employs piezoelectric actuators (PZT) to generate Lamb waves and utilizes a laser Doppler vibrometer (LDV) for non-contact, two-dimensional grid acquisition of the wavefield. The anisotropic properties of the metal 3D-printed structure will be captured in the wavefield, offering an informative dataset for wavenumber analysis. The proposed analytical method includes multi-directional frequency wavenumber analysis and a least-squares-based dispersion curves regression. The integration of the above advanced analytical tools allows for the accurate characterization of the shear wave velocity and Poisson’s ratio of the plate structure. This precise characterization is crucial for ensuring the structural integrity and consistent mechanical properties of 3D-printed metal components. We validated our method using a 3D-printed stainless-steel plate, demonstrating its capability to effectively characterize the multi-directional mechanical properties of additively manufactured metal plates. We expect that our method can provide a nondestructive, time-efficient, and comprehensive quality control solution for additive manufacturing across various industries.
Activation and modulation of the host response to DNA damage by an integrative and conjugative element
Authors: McKeithen-Mead Saria , Anderson Mary E. , García-Heredia Alam , Grossman Alan D. 
Published: January 2025

ABSTRACT

Mobile genetic elements help drive horizontal gene transfer and bacterial evolution. Conjugative elements and temperate bacteriophages can be stably maintained in host cells. They can alter host physiology and regulatory responses and typically carry genes that are beneficial to their hosts. We found that ICE
Bs1
, an integrative and conjugative element (ICE) of
Bacillus subtilis
, inhibits the host response to DNA damage (the SOS response). Activation of ICE
Bs1
before DNA damage reduced host cell lysis that was caused by SOS-mediated activation of two resident prophages. Further, activation of ICE
Bs1
itself activated the SOS response in a subpopulation of cells, and this activation was attenuated by the functions of the ICE
Bs1
genes
ydcT
and
yddA
(now
ramT
and
ramA
;
ram
for RecA modulator). Double-mutant analyses indicated that RamA functions to inhibit and RamT functions to both inhibit and activate the SOS response. Both RamT and RamA caused a reduction in RecA filaments, one of the early steps in activation of the SOS response. We suspect that there are several different mechanisms by which mobile genetic elements that generate single-stranded DNA (ssDNA) during their life cycle inhibit the host SOS response and RecA function, as RamT and RamA differ from the known SOS inhibitors encoded by conjugative elements.

IMPORTANCE

Bacterial genomes typically contain mobile genetic elements, including bacteriophages (viruses) and integrative and conjugative elements, that affect host physiology. ICEs can excise from the chromosome and undergo rolling-circle replication, producing ssDNA, a signal that indicates DNA damage and activates the host SOS response. We found that following excision and replication, ICE
Bs1
of
B. subtilis
stimulates the host SOS response and that ICE
Bs1
encodes two proteins that limit the extent of this response. These proteins also reduce the amount of cell killing caused by resident prophages following their activation by DNA damage. These proteins are different from those previously characterized that inhibit the host SOS response and represent a new way in which ICEs can affect their host cells.