bluuebunny/crossref_metadata_2025 huggingface dataset:
An Underwater Magnetically Coupled Bistable Vibration Energy Harvester Using Wings
Authors: Zou Hong-Xiang , Wei Ke-Xiang , Zhao Lin-Chuan , Zhang Wen-Ming , Zuo Lei , Qian Feng
Published: November 2019

Piezoelectric flow energy harvesting can be a potential way to yield endless electrical energy for small mechanical systems and wireless sensors. We propose a novel magnetically coupled bistable vibration energy harvester using wings for the applications in the water environment. The water flow energy can be harvested through the induced vibration of wings. The flextensional transducer can be packaged conveniently by using non-contact magnetic coupling mechanism. The magnetic force is amplified by the flextensional structure and transferred to the piezoelectric layer, thereby achieving higher power density and better reliability. A prototype was fabricated and tested in a water flume, which attended a maximum power of about 400 μW and the average power of 55 μW at the water flow velocity of 4 m/s. No significant variation occurred to the performance of the harvester after five days of continuous operation in the water, which indicates that the magnetically coupled vibration energy harvesting method has high reliability in the underwater environment.
Chattering-Free Finite-Time Stability of a Class of Fractional-Order Nonlinear Systems
Authors: Wang Bin , Chen Yangquan , Yang Ying
Published: November 2019

This paper studies the chattering-free finite-time control for a class of fractional-order nonlinear systems. First, a class of fractional-order nonlinear systems with external disturbances is presented. Second, a new finite-time terminal sliding mode control method is proposed for the stability control of a class of fractional-order nonlinear systems by combining the finite-time stability theory and sliding mode control scheme. Third, by designing a controller with a differential form and introducing the arc tangent function, the chattering phenomenon is well suppressed. Additionally, a controller is developed to resist external disturbances. Finally, numerical simulations are implemented to demonstrate the feasibility and validity of the proposed method.
Testing Design Optimization for Uncertainty Reduction in Generating Off-Road Mobility Map
Authors: Hu Zhen , Mourelatos Zissimos P. , Gorsich David , Jayakumar Paramsothy , Majcher Monica
Published: November 2019

The Next Generation NATO Reference Mobility Model (NG-NRMM) plays a vital role in vehicle mobility prediction and mission planning. The complicated vehicle-terrain interactions and the presence of heterogeneous uncertainty sources in the modeling and simulation (M&S) result in epistemic uncertainty/errors in the vehicle mobility prediction for given terrain and soil conditions. In this paper, the uncertainty sources that cause the uncertainty in mobility prediction are first partitioned into two levels, namely uncertainty in the M&S and uncertainty in terrain and soil maps. With a focus on the epistemic uncertainty in the M&S, this paper presents a testing design optimization framework to effectively reduce the uncertainty in the M&S and thus increase the confidence in generating off-road mobility maps. A Bayesian updating approach is developed to reduce the epistemic uncertainty/errors in the M&S using mobility testing data collected under controllable terrain and soil conditions. The updated models are then employed to generate off-road mobility maps for any given terrain and soil maps. Two types of design strategies, namely testing design for model selection and testing design for uncertainty reduction, are investigated in the testing design framework to maximize the information gain subject to limited resources. Results of a numerical example demonstrate the effectiveness of the proposed mobility testing design optimization framework.
Bi-Material Re-Entrant Triangle Structures Incorporating Tailorable Thermal Expansion and Tunable Poisson’s Ratio
Authors: Xiaobing He , Yan Xie , Jingjun Yu
Published: November 2019

Based on the bi-material triangle lattice material, a new cellular structure: bi-material re-entrant triangle (BRT) is devised to incorporate tailorable coefficient of thermal expansion (CTE) and tunable Poisson’s ratio (PR) properties by replacing the straight base of a triangle with two hypotenuse members. An equation to systematically build the relationship among the external force, the temperature increment and the deformation for the planar lattice material with bounded joints is derived and then embedded into a theoretical model for devised BRT structure. Using master stiffness equation, effective PR, effective Young’s modulus as well as effective CTE are computed. In order to guide designers to construct an initial concept quickly, the design domain for coupling negative CTE and negative PR properties is proposed. Nine available paired characteristics for coupling effect are extracted and demonstrated with ABAQUS simulation.
It Rings a Bell! Memory’s Impact on Information Utilization by Novice Designers in the Early Design Process
Authors: Mertens Attakias T. , Toh Christine A.
Published: November 2019

Research in new product design still lacks an understanding of how the types of information used by designers can lead to more successful designs and what cognitive components are involved in the process of generating new ideas. Some theories have arisen that focus on memory usage that could have an impact in idea generation early on in the design process. As a first step to address this gap, an Information Archetypes Framework was developed in previous work to outline the different dimensions and levels of information commonly used by designers. This framework forms the basis of the current study, focused on identifying the underlying cognitive processes that are active during the design process. To accomplish this, undergraduate students were recruited from the University of Nebraska-Omaha. During the study, participants were presented a design problem, given information pieces that corresponded to the Information Archetypes Framework, and asked to generate ideas for a solution. Students were then asked to recall the information pieces from memory. Participants’ data were analyzed using Linguistic Inquiry Word Count (LIWC) for relevant cognitive mechanisms. Scores from LIWC captured the linguistic properties of information pieces and generated ideas, and this study was able to demonstrate that memory usage has both semantic and linguistic components that emerge during the conceptual design process.
Design of a Totally Robotic Solution for Sampling in Pharmaceutical Industry
Authors: D’Imperio Mariapaola , Cannella Ferdinando
Published: November 2019

Quality control in the pharmaceutical industries is a critical issue. It consists of a sampling phase and an analysis phase. There are different ways of taking a sample to be submitted for a quality control: from static to dynamic methods, from simple to more complex solutions. All these traditional procedures and their results are strictly dependent on the operator, due to the fact that this type of environment is unstructured and not very often robotised. For this reason, the aim of the paper is to push forward the state of art in the sampling methods for quality controls, by presenting a totally robotic solution in the framework of dust samples collection from closed containers.
Study on the Dynamic Response of an Unbalanced Rotor System Supported by Ball Bearings
Authors: Fang Bin , Zhang Jinhua , Yan Ke , Hong Jun
Published: November 2019

This paper proposed a new four-degree-of-freedom dynamic model of the bearing-rotor system based on ball bearing without Raceway Control Hypothesis, and both the inertia forces of balls and the tilting motions of rotor are fully considering in the calculation of restoring forces and moments of ball bearings. Then the dynamic model are solved by the fourth-step Runge-Kutta method, and the dynamic responses of rotor system including the displacement, velocity and center orbits are obtained, and the influences of rotating speeds, eccentricity and symmetry of rotor are studied and analyzed. The results show that both the varying compliance of ball bearing and rotor eccentric force have a great influence on the dynamic responses and motion patterns of bearing-rotor system, and the titling motion of bearing-rotor should be considered in the analysis of asymmetric rotor or the symmetric rotor under some specific conditions.
Phase-Locking and Chaotic Phenomena of Circular Mesh Antenna With 1:3 Internal Resonance
Authors: Liu Tao , Zhang Wei , Zheng Yan , Guo Xiangying
Published: November 2019

We study chaotic dynamics and the phase-locking phenomenon of the circular mesh antenna with 1:3 internal resonance subjected to the temperature excitation in this paper. Firstly, the frequencies and modes of the circular mesh antenna are analyzed by the finite element method, it is found that there is an approximate threefold relationship between the first-order and the fourth-order vibrations of the circular mesh antenna. Considering a composite laminated circular cylindrical shell clamped along a generatrix and with the radial pre-stretched membranes at both ends subjected to the temperature excitation, we study the nonlinear dynamic behaviors of the equivalent circular mesh antenna model based on the fourth-order Runge-Kutta algorithm, which are described by the bifurcation diagrams, waveforms, phase plots and Poincaré maps in the state-parameter space. It is found that there appear the Pomeau-Manneville type intermittent chaos. According to the topology evolution of phase trajectories, the phase-locking phenomena are found.
An Automatic Transformation Method for the Walking Assistive Device to Walk Between Flat Ground and Stairs Safely
Authors: Yang Bo-Rong , Zhang Yu-Cheng , Lee Hee-Hyol , Tanaka Eiichiro
Published: November 2019

The main target of this research is to assist the elderly people to walk on different road conditions independently. A method that can transform the walking motion of a walking assistive device between level walking and stair climbing automatically was proposed. To teach the target user how to walk correctly, we defined a trajectory that belongs to healthy people to help the user exercise. Stairs are common in various indoor situations and become a huge challenge for people with gait disorders. To extend the range of physical activity, walking trajectories in different surroundings were imported on the assistive device. Ultrasonic sensors were utilized to detect the distance between stairs and the swing foot. Based on the measured distance, the gait was modified according to a predefined safety distance that was determined experimentally. We also designed trajectory combination methods for changing the device motion patterns between ascending and descending stairs as the walking conditions change. The effectiveness of the system was tested through simulation. The results showed that the device smoothly shifted gait with the proposed methods in this paper. This method has the potential to solve the adaptability of various walking devices to different surroundings.
Investigation of the Effect of Long-Term Contact on Adhesion Force in Polycrystalline MEMS Devices
Authors: Othayq Mazen M. , Giganti Nino , Shavezipur Mohammad
Published: November 2019

The effect of long-term contact on adhesion force between MEMS silicon surfaces is investigated. A test structure is developed that can initiate the contact between the two surfaces without actuation. Therefore, the surfaces may remain in contact for a long period of time. The contacting surfaces are separated using a thermal actuator and the adhesion force is determined utilizing FEM simulations. Freshly released and long-time stored devices were tested, and their adhesion force is determined. The test results show that the adhesion force for devices in contact for a long time is drastically larger than those with short-term contact. Adhesion force values as large as 2.9 μN for long-term contact and as small as 0.4 μN for fresh contact were measured. The large adhesion force associated with long-term contact is believed to be attributed to the formation of native oxide at contacting nano-asperities and formation of covalent bonds between the surfaces, requiring larger force to break the bonds.
Hybrid Fabrication of a Soft Bending Actuator With Casting and Additive Manufacturing
Authors: Oliveira Marcos B. , Lurie Alexander , Ewen David , Long Philip , Padir Taskin , Felton Samuel M.
Published: November 2019

In this paper, we present the design, modeling and, fabrication of a soft bending actuator that combines casting techniques and additive manufacturing. We performed tests to evaluate the bending actuator’s angular deflection and tip force. We demonstrated flexibility in the process by varying the bladder material. We also showed the actuator’s resilience to damage by cutting and puncturing the exoskeleton prior to operation. Finally, we integrated the bending actuator into a three-finger gripper configuration and performed a gripping test for four different objects with various weights and shapes. Results show that the curvature and force obtained in these actuators are comparable to other proposed bending actuators with a faster and more adaptable fabrication process. With these results we demonstrate that fast, effective, and versatile fabrication of soft robotic components can be attained by combining casting and additive manufacturing techniques.
Lattice Structure Design for Additive Manufacturing: Unit Cell Topology Optimization
Authors: Hanks Bradley , Frecker Mary
Published: November 2019

Additive manufacturing is a developing technology that enhances design freedom at multiple length scales, from the macroscale, or bulk geometry, to the mesoscale, such as lattice structures, and even down to tailored microstructure. At the mesoscale, lattice structures are often used to replace solid sections of material and are typically patterned after generic topologies. The mechanical properties and performance of generic unit cell topologies are being explored by many researchers but there is a lack of development of custom lattice structures, optimized for their application, with considerations for design for additive manufacturing. This work proposes a ground structure topology optimization method for systematic unit cell optimization. Two case studies are presented to demonstrate the approach. Case Study 1 results in a range of unit cell designs that transition from maximum thermal conductivity to minimization of compliance. Case Study 2 shows the opportunity for constitutive matching of the bulk lattice properties to a target constitutive matrix. Future work will include validation of unit cell modeling, testing of optimized solutions, and further development of the approach through expansion to 3D and refinement of objective, penalty, and constraint functions.
Autonomous Vehicle Driving via Deep Deterministic Policy Gradient
Authors: Huang Wenhui , Braghin Francesco , Arrigoni Stefano
Published: November 2019

Autonomous driving has became one of the most hot trends in artificial intelligence area in recent years thanks to the machine learning algorithms. However, most of the autonomous driving studies are still limited to discrete action space. In this study, we propose to implement Deep Deterministic Policy Gradient algorithm for learning driving behavior over the continuous actions. For this purpose, a driving simulator is employed which interfaces with IPG CarMker software where the virtual environment and dynamical vehicle model can be built. “Human-in-the-loop” is performed in order to gather the data and a neural network which is implemented in Behavior Layer is trained to recognize two different scenarios-forward driving and stop. Based on the scenario the agent is dealing with, the actions are learnt and suggested from the DDPG algorithm. The experimental results show that DDPG algorithm is able to learn the optimal policy with continuous actions reliably for both scenarios.
Life Cycle Assessment of Pyrolysis-Derived Biochar From Organic Wastes and Advanced Feedstocks
Authors: Hersh Benjamin , Mirkouei Amin
Published: November 2019

Recent interest in reducing stress on the food-energy-water (FEW) nexus requires the use of renewable, organic products that can subsequently address environmental sustainability concerns, such as mitigating greenhouse gas emissions. Pyrolysis-derived biochar from organic wastes (e.g., nutrient-rich agricultural wastes and leftovers, forest harvest residues, and cattle manure) and advanced feedstocks (e.g., algae) is capable of addressing ever-increasing global FEW concerns. Biochar water-nutrient holding capacity and carbon sequestration are key attributes for improving organic farming and irrigation management. The major challenge to commercialize biochar production from organic wastes is the conversion process. Pyrolysis process is a cost-effective and successful approach in comparison to other conversion technologies (e.g., gasification) due to low energy requirement and capital cost, as well as high process efficiency and biochar quality. To determine the environmental impacts of the biochar production process, an analysis of the material, energy, and emission flows of a small-scale pyrolysis process is conducted for a real case study, using life cycle assessment method with the assistance of available life cycle inventory databases within OpenLCA software. The results demonstrate that this study is able to enhance sustainability aspects across FEW systems by (a) employing a portable refinery to address upstream challenges (i.e., collection, transportation, and preprocessing) of waste-to-biochar life cycle, (b) recycling domestic forest and agricultural residues (e.g., pine wood), (c) producing organic biochar-derived soil conditioners that can improve organic cropping and FEW systems. Ultimately, we conclude by discussing techno-economic and socio-environmental implications of biochar production from organic wastes and advanced feedstocks.
Virtual Sensing in High-Performance Vehicles With Artificial Intelligence
Authors: Bonfitto Angelo , Feraco Stefano , Amati Nicola , Tonoli Andrea
Published: November 2019

This paper presents a technique for the estimation of the sideslip angle and longitudinal speed of a high-performance four-wheel drive vehicle by means of Artificial Neural Networks. The proposed architecture relies on the combination of a pattern recognition neural classifier with two stages of cascaded regression neural networks. The classifier allows identifying the road condition and the regression stages perform the two estimation tasks. The networks are trained by means of datasets recorded on an instrumented vehicle. The strategy is tested in different road adherence conditions, namely dry, wet and icy, and in a variety of driving maneuvers. The effectiveness of the technique is demonstrated experimentally by deploying the algorithm on the vehicle and comparing the sideslip angle estimation with the measurement computed by an optical sensor and the longitudinal speed estimation with both the estimation already present on the vehicle and obtained as the mean value of the wheels’ velocity and with the optical sensor measurement.
Mechanical Design and Prototype of a Reconfigurable Actuated Universal Joint
Authors: Palpacelli M. C. , Carbonari L. , Palmieri G. , Callegari M.
Published: November 2019

This paper presents the mechanical design and prototyping of a reconfigurable universal joint. An electronically actuated mechanical switch allows to change joint’s configuration so that two different universal pairs can be obtained. One of the two revolute axes rotates freely whereas the other is driven by a servomotor: its direction can be chosen by the user, providing two different mechanical arrangements. It can be demonstrated that the use of this reconfigurable joint in a specific parallel kinematic manipulator equipped with three identical legs allows to change the mobility of its moving platform. The design proposed in the current work has been driven by analytical analyses and multibody simulations. A finite element analysis demonstrates the effectiveness of the mechanical design.
Modeling, Validation and Prototype Development of Electric Sail Tether Deployment Systems for CubeSats
Authors: Hargis Benjamin E. , Brandt Benjamin F. , Canfield Stephen L. , Tinker Michael
Published: November 2019

The Electric sail concept is based on a distributed tether satellite system with tether lengths on the order of thousands-of meters. The system must deploy from stowed arrangement into a selected flight configuration in which thrust forces are transmitted through the tether to the satellite body. The system must be stable through deployment procedure and maintain stable, desired configuration during flight operations. Understanding the dynamic behavior of the satellite bodies and distributed, conductive tether are critical to long-range design and development of the Electric Sail concept. This paper’s contribution is the presentation, development and validation of a mathematical model for simulating E-Sail deployment of a prototype system for testing on the MSFC Robotic Flat Floor Facility. A massed tether model is developed using the bead and string concept with equations of motion derived from Lagrange’s Method. The model is validated using infrared motion capture data produced by controlled experiments of a representative tether portion outfitted with IR targets. Further, a prototype is presented which will be used to investigate an E-Sail deployment approach and associated control. The design of this system will allow for deployment on specially designed flat floor facilities at MSFC. The prototype will be used to: 1) gather data for validation of system dynamic model, 2) evaluate alternative deployment strategies, 3) evaluate tether reel-out and damping control strategies.
Mahalanobis-Taguchi-Fukuda Approach to Human Motion Control
Authors: Fukuda Shuichi
Published: November 2019

Learning from failures approach how to control human motion is developed by extending Mahalanobis Taguchi System. It enables quantitative measurement of how the learner is improving in his or her learning, It helps to acquire tacit knowledge such as swimming, for which we do not have valid approach. Since Mahalanobis Distance is a unitless measure for multi-dimensional variables, this approach can be extended to many adaptive network formation and management, because this approach let the learner recognize how he or she can coordinate their body pars to adapt to the changing situations. Thus, the approach ca be applied to development and operation of soft robots and adaptive network or team formation and management in the IoT connected society.
Multi-Fidelity Physics-Constrained Neural Network and its Application in Materials Modeling
Authors: Liu Dehao , Wang Yan
Published: November 2019

Training machine learning tools such as neural networks requires the availability of sizable data, which can be difficult for engineering and scientific applications where experiments or simulations are expensive. In this work, a novel multi-fidelity physics-constrained neural network is proposed to reduce the required amount of training data, where physical knowledge is applied to constrain neural networks, and multi-fidelity networks are constructed to improve training efficiency. A low-cost low-fidelity physics-constrained neural network is used as the baseline model, whereas a limited amount of data from a high-fidelity simulation is used to train a second neural network to predict the difference between the two models. The proposed framework is demonstrated with two-dimensional heat transfer and phase transition problems, which are fundamental in materials modeling. Physics is described by partial differential equations. With the same set of training data, the prediction error of physics-constrained neural network can be one order of magnitude lower than that of a classical artificial neural network without physical constraints. The accuracy of the prediction is comparable to those from direct numerical solutions of equations.
The Importance of Energy Criteria for Selecting Modes in Reduced Order Modeling
Authors: Bhattacharyya Suparno , Cusumano Joseph P.
Published: November 2019

We study the performance of the proper orthogonal decomposition when used for model reduction of an Euler-Bernoulli beam subjected to periodic impulses. We assess the accuracy of reduced order models (ROMs) obtained using steady-state displacement time series. The spatiotemporal localization of the applied impulses is tuned to control the number of excited modes in, and hence the effective dimensionality of, the system’s response. We find that when the impacts are significantly localized (i.e., are more impulsive), the conventional variance-based mode selection criterion can lead to inaccurate ROMs. We show that this arises when the reduced subspace capturing a fixed amount (say, 99.9%) of the total data variance underestimates the energy input and/or dissipated in the ROM, leading to energy imbalance. We thus propose a new energy closure criterion that provides an improved method for generating ROMs. The energetics of the resulting ROMs properly reflect those of the full system, and yield simulations that accurately represent the system’s true behavior.
System Reliability Analysis Using Hybrid Gaussian Process Model
Authors: Li Meng , Sadoughi Mohammad Kazem , Hu Zhen , Hu Chao
Published: November 2019

This paper proposes a system reliability analysis method based on the hybrid of multivariate Gaussian process (MGP) and univariate Gaussian process (UGP) models, named as hybrid Gaussian process-based system reliability analysis (HGP-SRA). MGP and UGP models are selectively constructed for the components of a complex engineered system: MGP models are constructed over the groups of highly interdependent components and the individual UGP models are built over the components which are relatively independent of one another. A nonlinear-dependence measure, namely the randomized dependence coefficient, is adopted to adaptively learn and quantify the pairwise dependencies of the components with both linear and nonlinear dependency patterns. In the proposed HGP-SRA method, initial hybrid Gaussian process (HGP) models are first constructed with a set of near-random samples and these surrogate models are then updated with new samples that are sequentially identified based on the acquisition function named as multivariate probability of improvement (MPI). The results of two mathematical and a real-world engineering case studies suggest that the proposed method can achieve better accuracy and efficiency in system reliability estimation than the benchmark surrogate-based methods.
Topological Semantics for Lumped Parameter Systems Modeling
Authors: Wang Randi , Shapiro Vadim
Published: November 2019

Behaviors of many engineering systems are described by lumped parameter models that encapsulate the spatially distributed nature of the system into networks of lumped elements; the dynamics of such a network is governed by a system of ordinary differential and algebraic equations. Languages and simulation tools for modeling such systems differ in syntax, informal semantics, and in the methods by which such systems of equations are generated and simulated, leading to numerous interoperability challenges.

We propose to unify semantics of all such systems using standard notions from algebraic topology. In particular, Tonti diagrams classify all physical theories in terms of physical laws (topological and constitutive) defined over a pair of dual cochain complexes and may be used to describe different types of lumped parameter systems. We show that all possible methods for generating the corresponding state equations within each physical domain correspond to paths over Tonti diagrams. We further propose a generalization of Tonti diagram that captures the behavior and supports canonical generation of state equations for multi-domain lumped parameter systems. The unified semantics provides a basis for greater interoperability in systems modeling, supporting automated translation, integration, reuse, and numerical simulation of models created in different authoring systems and applications. Notably, the proposed algebraic topological semantics is also compatible with spatially and temporally distributed models that are at the core of modern CAD and CAE systems.
Optimal Reconfiguration Path Decision Method for One RMT System
Authors: Huang Sihan , Zeng Cong , Wang Guoxin , Yan Yan
Published: November 2019

Reconfigurable manufacturing system (RMS) is designed around a specific part family. Reconfigurable machine tools (RMT) is the core facility of RMS. One RMT system is an RMS consisting of only one RMT. So, the RMT of one RMT system is designed for a specific part family, which integrates the characteristics of RMS and RMT. The reconfiguration path problem of one RMT system is an urgent problem to be solved. Therefore, an optimal reconfiguration path decision method for one RMT system is proposed in this paper. The objective is to produce the entire part family at the minimum reconfiguration effort. Reconfiguration time is adopted as the characteristic value of reconfiguration effort in this paper. The Tabu Search algorithm (TS) is used to solve this problem due to its excellent search ability. Process rule is considered during computation to obtained reasonable solution. A case study is given to implement the proposed method. The result shows that the proposed method can produce an optimal reconfiguration path for one RMT system satisfying the process rule.
Leveraging Animations to Enhance Learning Through Virtual Product Dissection
Authors: Kearney Kevin G. , Starkey Elizabeth M. , Miller Scarlett R.
Published: November 2019

Product dissection, in either physical or virtual form, has been found to be an effective learning tool. With the rapid growth of technology, effective virtual education tools have the potential to continue increasing in value. Although physical product dissection is often implemented in the classroom, there are some limitations to employing these tools. One such limitation is the inability to see into a product and view the internals of a product while it is functioning. Recent research has found that students who dissect physical or virtual products have similar conceptual understanding of products after dissection. Although there are promising findings for virtual dissection, there is still room for improvement in these virtual environments to enable better understanding of products. One way this may be possible is through the addition of animations, which show the functions of the internal components in a product, a capability that is currently not offered in virtual product dissection tools. These animations have the ability to show how a product works in ways unobtainable through physical product dissection and currently unavailable in virtual product dissection. Therefore, this research aims to explore the impact that animation in virtual product dissection has on learning and cognitive load for engineering students.
Electron Backscatter Diffraction-Enabled Anisotropic Thermo-Elastic Analysis of Additively Manufactured Single Tracks
Authors: Birnbaum Andrew J. , Michopoulos John G. , Steuben John C. , Iliopoulos Athanasios P.
Published: November 2019

Despite extensive efforts directed toward elucidating the connections between process, microstructure and performance of additively manufactured structures and components, a significant number of meaningful questions remain unanswered. Specifically, a large body of work has demonstrated that microstructural/sub-structural features in selectively laser melted (SLM) components give rise to a significant enhancement in strength. Furthermore, the change in associated ductility is comparable to that seen in post-processed, wrought annealed material. However, the origin and mechanism by which these features arise have remained elusive. This work is an initial step in leveraging computational capabilities for validating experiment-based theories that explain the basis for the above-mentioned phenomena. The present work describes a computational approach for utilizing spatially resolved crystal-lographic descriptions obtained via electron backscatter diffraction (EBSD) to define the domain geometry and material properties of an anisotropic thermo-elastic simulation. The resulting solution is used to ascertain the elastic strain energy state, and slip-system resolved shear stresses on a per-grain basis. This analysis is performed, in part, as a means for validating a hypothesis linking these characteristics with the development of sub-structural features, which are in turn, correlated with improvements in material performance. The results suggest that both strain energy density and grain boundary character play an important role in the formation of substructure in additively manufactured 316L stainless steels.
Conceptual Design and Prototype Development of a Solar-Powered Ground Robot for Energy-Autonomous Operation
Authors: Behjat Amir , Collins Leighton , Hoffman Andrew , Chidambaran Sharat , Dhameliya Maulikkumar , Chowdhury Souma
Published: November 2019

This paper presents the conceptual design and fabrication/assembly of an autonomous solar powered small unmanned ground vehicle (UGV) platform for operation in outdoor environments. The contribution lies in the ability of the proposed design to offer uninterrupted operation in terms of endurance, to facilitate educational and research applications that are otherwise challenging to perform with a typical UGV (that needs significant downtime for recharging). A high incident area for solar PV panels is required to be able to support the complete energy needs of a ∼ 46 lb UGV (i.e., fully recharge the suitably sized battery powering the UGV). This makes it challenging to develop a stable platform that can carry solar panels much larger than the surface area of the platform itself (an aspect receiving minimal attention in other similar purpose platforms). To address this challenge, a novel umbrella-like folding mechanism is conceived, designed and successfully incorporated in the baseline prototype. This mechanism allows incorporating a remarkable ∼1 sq.m of incident solar PV with a net rated capacity of 200 W, one that remains folded to facilitate mobility, and can open/unfold to different extents for energy capture when needed. At the same time, the proposed design facilitates static and dynamic stability in spite of the significant solar PV incorporation. With the reference of the baseline prototype, an optimization approach is taken to develop a conceptual design of the next generation of this solar UGV. Specifically, the incident angle of the solar panels (enabled by the umbrella mechanism) at complete-open stage and the dimensions of the mechanism links and associated supports are separately optimized to respectively maximize the energy capture and the range of the UGV (assuming operation in Buffalo, NY), subject to stability and nominal velocity (of 2km/hr) constraints. The optimum design is found to provide an estimated range of 19.8 km/day.
Risk Perception and Product Safety in User-Centered Design
Authors: Cai Mingzhi , Seligsohn Erin N. , Zhang Zhinan , Wang Yan
Published: November 2019

When customers decide which product to buy, the perceived risks associated with the purchase are typically part of consideration. The customer’s purchase decision is directly related to the perceived risk about finance, safety, reputation, or others. It is important to incorporate the customer’s perception of risks in user-centered product design. Existing research of risk perception in product development focuses on the warning label design to ensure that consumers are aware of product safety and potential hazards. There is limited work on how to design the product itself with the consideration of risk factors. In this research, the effects of risk perception from consumers on design are studied. The results show that the perceived product safety by customers can be independent from objective measurements of risks. The perceptions are influenced by individual experiences, information obtained from government regulations and standards, as well as personal characteristics. Design variables related to the levels of comfort, aesthetics, and performance for automobile could affect the customers’ perception about vehicle safety.
Modeling, Control and Planning for Multiple Mobile Microrobots
Authors: Johnson Benjamin V. , Cappelleri David J.
Published: November 2019

We present the modeling, control and planning for multiple magnetic mobile microrobots actuated on a planar array of coils that generates local magnetic fields. The system is capable of actuating multiple microrobots independently. Such systems have a future in micromanufacturing and biomedical applications. The coils are modeled extensively to understand the forces generated by various coil combinations of the array, and solutions for different actuation force directions are discovered. The path planning problem is formulated as a Markov decision process that solves a policy to reach a goal from any location in the workspace. The presence of multiple robots in the workspace can interfere with their motion. Hence, the coil models are used concurrently with models of interaction force between multiple magnetic robots to plan efficient paths to reach a goal in the workspace in the presence of other robots.
Manipulating Trust of Autonomous Products With Affective Priming
Authors: Liao Ting , MacDonald Erin
Published: November 2019

User-to-product trust has two notable aspects: (1) the user’s propensity to trust, and (2) the product’s trustworthiness as assessed by the user. Autonomous products, which perform many functions on their own with limited user input, require the user to exhibit trust at an appropriate level before use. Research in product trust thus far has focused on the product trustworthiness: manipulating the product’s design, for example, anthropomorphizing an autonomous vehicle and measuring changes in trust. This study flips the usual approach, manipulating a person’s propensity to trust and measuring response to an existing autonomous product, the Amazon Echo. We build on our past successes with priming exercises to reveal insights into the user-related factors of product trust. In this study, we used visual stimuli that evoked either positive, neutral or negative emotions as affective primes to influence users’ trust propensity before the interaction. The participants interacted with a mock-up of the Amazon Echo via ten pre-determined question-and-answer (Q&A) sets. During the interaction, the participants evaluated the Echo’s competence and if it met participants’ expectations. They also reported trust towards the Echo after the Q&A sets. Holistically, the affective primes show no significant effect on the trust propensity. For the subgroup of participants whose expectations of the product’s performance were met, both the perceived product competence and the affective primes have significant effects on trust propensity. These results demonstrate the complex nature of trust as a multidimensional construct and the critical role of product performance in trust formation. They also suggest that it will be difficult for a product to build trust with users who expect the product to perform in a different way than its intent — if one wants to design a product that builds trust, they should understand user expectations and design to meet them. This learning can facilitate the intentional design of the affective process in trust formation that helps build a healthy level of trust with autonomous products.
An Adaptive and Efficient Boundary Approach for Density-Based Topology Optimization
Authors: Behrou Reza , Lotfi Reza , Carstensen Josephine V. , Guest James K.
Published: November 2019

This paper presents an adaptive nodal boundary condition scheme to systematically enhance the computational efficiency and circumvent numerical instabilities of the finite element analysis in density-based topology optimization problems. The approach revisits the idea originally proposed by Bruns and Tortorelli to eliminate the contribution of void elements from the finite element model and extends this idea to modern projection methods to stabilize the implementation, facilitate reintroduction of material, and consider additional physics. The computational domain is discretized on a fixed finite element mesh and a threshold density is used to determine if an element is sufficiently low relative density to be “removed” from the finite element analysis. By eliminating low-density elements from the design domain, the number of free Degrees-Of-Freedom (DOFs) is reduced, thereby reducing the solution cost of the finite element equations. Perhaps more importantly, it circumvents numerical instabilities such as element distortion when considering large deformations. Unlike traditional solids-only modeling approaches, a key feature of the projection-based scheme is that the design and finite element spaces are separate, allowing the design variable sensitivities in a region to remain active (and potentially non-zero) even if the corresponding analysis elements are removed from the finite element model. This ultimately means material reintroduction is systematic and driven by the design sensitivities. The Solid Isotropic Material with Penalization (SIMP) approach is used to interpolate material properties and the Heaviside Projection Method (HPM) is used to regularize the optimization problem and facilitate material reintroduction through the gradient-based optimizer. Several benchmark examples in areas of linear and nonlinear structural mechanics are presented to demonstrate the performance of the proposed approach. The resulting optimized designs are consistent with literature and results reveal the performance and efficiency of the developed method in reducing computational costs without numerical instabilities known to be due to modeling near-void elements.
Load-Flow Based Design of Compliant Mechanisms With Embedded Soft Actuators
Authors: Patiballa Sree Kalyan , Satheeshbabu Sreeshankar , Krishnan Girish
Published: November 2019

Transmission members such as gears and linkages are ubiquitously used in mechatronic systems to tailor the performance of actuators. However, in most bio-inspired soft systems the actuation and transmission members are closely integrated, and sometimes indistinguishable. Embedded actuation is greatly advantageous for attaining high stroke and transferring large output forces. This paper attempts at a systematic synthesis of compliant systems with embedded contractile actuators and passive members to achieve a particular kinematic objective. The paper builds on recent understanding of a compliant mechanism topology where the constituent members can be functionally classified as load transferring transmitters and strain energy storing constraints. The functional equivalence between the transmitter members and actuators are used to replace transmitters in tension with contractile actuators, thus realizing a compliant embedded system. Once a single-input single-output compliant mechanism is designed, and its load flow behavior mapped, systematic guidelines and best practices are established for embedding actuators within the topology to increase performance without altering the kinematic behavior. Several examples, including a prototype that used soft pneumatic artificial muscles is presented to validate the synthesis framework. The initial results will form the basis for designing fully autonomous compliant systems with embedded actuators and sensors without the use of computationally expensive techniques.
A New Human Intruder Detection Scheme for Video Surveillance
Authors: Xiong Shaomin , Wu Haoyu , Hirano Toshiki
Published: November 2019

The demand for video surveillance has increased rapidly in recent years. Artificial intelligence (AI) algorithms are key enablers for the smart functionalities of a surveillance camera. Typical smart functionalities include human or object detection, tracking and recognition. However, many of the neural network (NN) algorithms for AI require intensive computation. At the endpoint or edge such as a home surveillance camera, the computation power is limited. The intensive computation also causes higher power consumption, which is also problematic for battery powered cameras. In this paper, we introduce a new human detection scheme that requires much less computation while the accuracy is equivalent to other existing algorithms. It obtains datasets and knowledge from a complex NN algorithm at the learning and calibration phase. These datasets are later used to train two cascading lightweight machine leaning algorithms, which will be used for further human detections. It is demonstrated that the proposed scheme can be run by the camera alone and the speed of detection is much faster than other benchmark NN algorithms.
Development of Novel Rotary Magnetic Encoder
Authors: Peng Kai-Yang , Chang Jen-Yuan (James)
Published: November 2019

This paper discussed the development and validation of a new rotary magnetic encoder for measurement of spindle’s axial displacements. The novelty of this work is on the design of permanent magnets as the magnetizing source to produce alternative magnetic polarities on ferromagnetic material electroplated on disk/ring-like flange that is attached to the targeted spindle shaft. Through mechatronics integration and numerical finite element parameter studies, the optimal combination of the magnetizer design parameters with consideration of the arrangement of magnetoresistive (MR) elements is reached to produce the novel encoding magnetic patterns for the axial displacement measurements. The effectiveness of the proposed method is further validated through calibrated experiments leading to the conclusion of reaching 10um accuracy performance in the measurement of the spindle’s axial elongation.
A Wearable Neck Measurement Device and Monitoring System to Improve Ergonomic Performance of Surgeons
Authors: Morris Karcher , Zhao Minghui , Lam Jenny , Jacobsen Garth , Horgan Santiago , Talke Frank E.
Published: November 2019

The long-term health of a surgeon is significantly affected by repetitive tasks and positions assumed during surgery. In order to evaluate neck positions throughout surgery, a novel wireless neck measurement system has been designed and developed. Extension, protraction, and rotation data of the neck are captured with accelerometers and flex sensors. Data is transmitted wirelessly and processed utilizing MATLAB. Sensor results are evaluated and compared with the goal to improve the ergonomic behavior of surgeons.
Investigation of Zinc-Silver Oxide-Thermoplastic Composite for Application in a Biofilm Retardant Urinary Catheter
Authors: Gotlib Oren , Morris Karcher , Spada Frederick E. , Alagiri Madhu , Patras Katy , Talke Frank E.
Published: November 2019

Catheter acquired urinary tract infection (CAUTI) is a significant problem in the medical community. Interdisciplinary teams have coordinated to address this problem, yet there is still a need for an adequate solution. In this study, we investigate an electricidal solution by adopting electrochemically active materials that can be incorporated into a urinary catheter. Zinc and silver oxide powders deposited in the form of patterned electrodes on a thermoplastic substrate are shown to illustrate electricidal properties in urine, including the ability to produce electric fields, pH increases, as well as, formation of hydrogen peroxide. The newly developed samples show promising results for killing planktonic E. coli in a controlled setting.