bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical and Experimental Bifurcation Analysis of Trailers
Authors: Horvath Hanna Zs. , Takacs Denes
Published: November 2020

A 4-DoF spatial mechanical model of trailers is used to analyze the snaking, rocking and roll-over motions. The derivation of the governing equations is presented. The non-smooth characteristics of the tire forces are taken into account together with other geometrical non-linearities. Beyond the linear stability analysis the nonlinear vibrations are investigated via numerical continuation and simulations. Linear stability charts and bifurcation diagrams are constructed to identify the parameter ranges, where large amplitude vibration can occur. The domains of the snaking and the rocking motion are detected. Numerical simulations verify the existence of periodic solutions predicted by numerical bifurcation analysis. A small scale experimental rig is presented and the nonlinear vibration of the trailer is investigated.
Measuring Dielectric Properties of Ceramic Powders at Microwave Frequencies for Material Processing Applications
Authors: Graber B. D. , Iliopoulos A. P. , Michopoulos J. G. , Steuben J. C. , Birnbaum A. J. , Fischer R. P. , Johnson L. A. , Bernhardt P. A. , Coombs J. M. , Gorzkowski E. P. , Patterson E. A.
Published: November 2020

Ceramic powders are commonly used as precursors for several ceramic part manufacturing processes. Their dielectric characterization is necessary for all the cases where electromagnetic radiation is used to induce heating. In support of such activities at the U.S. Naval Research Laboratory, the present work introduces a technique for measuring the complex dielectric constants of ceramic powders at microwave frequencies. The data produced by this technique is critical for the proper modeling of ceramic powder microwave absorption and will assist in ongoing research into volumetric microwave sintering. This technique involves a transmission line measurement using a network analyzer and waveguide setup. Dielectric parameters are then extracted from these measurements using two established methods. Complex relative permittivity measurements are presented for ceramic powders ofyttria stabilized zirconia (YSZ), barium titanate (BaTiO3), zinc oxide (ZnO), and titanium dioxide (TiO2) as well as a method for containing the sample shape during measurement. Experiments were carried out between 25 and 40GHz; in the Ka microwave band. Experimental results suggest that the dielectric constant (ε′) of these powders are similar to those of bulk. Results are compared to lower frequency reference data showing reasonable agreement.
Knee Prostheses Reverse Engineering: A Preliminary Investigation
Authors: Rossoni Marco , Regazzoni Daniele , Vitali Andrea , Colombo Giorgio , Spandre Luca , De Caro Francesca
Published: November 2020

Total Knee Arthroplasty is one of the most commonly performed orthopedic procedures and it is expected to grow in the next future. In the last past years, computer-assisted procedures represent one of the trends that are transforming the way of practicing medicine. Cornering the Total Knee Arthroplasty, digital models of the joints have been used to carry out simulation of their kinematics and mechanical performance. Whilst for the 3D digital reconstruction of the patient geometry several studies have been conducted, an approximated geometry of the prosthesis has been several times employed, with undeniable consequences on the final results. This paper aims at comparing two non-contact reverse engineering technologies to acquire the shape of femoral components employed for total knee arthroplasty. A high-level device (Konika Minolta Vivid 9i) and a mid-low cost laser (NextEngine) has been compared. For the comparison, a systematic procedure of acquisition and elaboration of the results has been adopted in order to have as unbiased as possible results. The procedure involves the use of the proprietary software of the scanners for the elaboration of the raw data and the meshing procedure has been kept the same for all the models. Since the as-is acquired mesh is of high-resolution, a decimation procedure has been carried out in order to make the 3D models lighter and easier to be handled. Once the decimation procedure has been evaluated comparing the original and the simplified models to one another, the digitalized models have been compared with the measurements taken from a coordinate measuring machines. As a preliminary result, the two lasers seem to be adequate to accomplish the reverse engineering process as required by this application. Of course, the mid-low cost laser would be preferable whether the performance will be confirmed to be (statistically) equal.
A Study of Human Balance and Coordination Using a Head Mounted Display
Authors: Gracia De Luna Daniel , Tijernia Roel , Butler Alley , Tomai Emmett , Timmer Douglas , Caruntu Dumitru
Published: November 2020

This paper reports on an experiment in human subject balance and coordination using a HTC Vive head mounted display to create a virtual environment. For the experiment, 30 male human subjects of college age and 30 female subjects of college age were asked to navigate along a clear path in a virtual world using a controller with their dominant hand and asked to balance a virtual ball on a virtual plate using the other controller in the non-dominant hand. The test subjects moved along a clearly marked path, with three surprise obstacles occurring: a large rock landing near the path, and explosion near the path, and a flock of birds coming across the path. Data included 6 degree of freedom trajectories for the head, and both hands, as well as data gathered by the computer system on ball location and velocity, plate location and velocity and ball status. Likert scale questionnaires were answered by the test subjects relative to video game experience, sense of presence, and ease of managing the ball movement. Statistics showed that the male students dropped the ball less frequently at p = 0.0254 and p = 0.0036. In contrast, female students were aware of their performance with correlation levels of 0.632 and 0.588.
Optimal Product Family Architecture Design and Commonality Decision for Sustainability and Intellectual Property Protection
Authors: Kim Jinju , Saidani Michael , Kim Harrison M.
Published: November 2020

With the rapid development of new technology and the growing global competition in industry, it is essential for companies to protect their sensitive product designs and technologies. To ensure that their systems are not exploited by third-party competitors or remanufacturers, original equipment manufacturers often apply physical attributes and/or reduce commonality within a product family to prevent easy reusing and recovering. Yet, these design strategies are key barriers to the sustainable recovery and recycling of products. To address these trade-offs, this paper proposes a stepwise methodology to identify the sustainable optimal product family architecture design while protecting intellectual property on sensitive parts or modules. The developed approach notably allows the selection of suitable and sustainable candidates to share among products, taking into account the cost-benefit of commonality within the product family. As such, it can be used as a decision support tool to help product designers identify appropriate product family architecture design and find candidates that can be shared within a product family by considering both sustainability and security parameters.
Variational Principles for Non-Material Systems Within an Arbitrary Lagrangian Eulerian Description of Motion
Authors: Pennisi Giuseppe , Bauchau Olivier
Published: November 2020

Dynamics of axially moving continua, such as beams, cables and strings, can be modeled by use of an Arbitrary La-grangian Eulerian (ALE) approach. Within a Finite Element framework, an ALE element is indeed a non-material system, i.e. a mass flow occurs at its boundaries. This article presents the dynamic description of such systems and highlights the peculiarities that arise when applying standard mechanical principles to non-material systems. Starting from D’Alembert’s principle, Hamilton’s principle and Lagrange’s equations for a non-material system are derived and the significance of the additional transport terms discussed. Subsequently, the numerical example of a length-changing beam is illustrated. Energetic considerations show the complex dynamic behavior non-material systems might exhibit.
Parallelized Additive Manufacturing of Variably Partitioned Volumes for Large Scale 3D Printing With Localized Quality
Authors: Dinar Mahmoud
Published: November 2020

Despite the growing application of additive manufacturing (AM) in fabricating complex designs, most machines suffer from small working envelopes and slow processing speeds. One workaround to the problem of small throughput in AM is to partition the volume of a desired object and fabricate sub-volumes in parallel. Prior related work has focused on two problems. One is the geometric division problem, disregarding AM benefits and challenges in determining partitions. Others attempt to install multiple AM processing heads on the same machine, ensuring seamless bonding between deposited material from different heads while avoiding interference among them. A missed opportunity lies in deploying many independent machines simultaneously while considering benefits and limitations of AM. To that end, objects too large to be fabricated on one machine, are divided primarily into cubes that exploit benefits of AM. Specifically, the cubes are hollowed out in the direction of printing to reduce weight while avoiding the need for support structure, and depending on load conditions, packed in different orientations to mitigate material anisotropy.
A Consumer Dissatisfaction Model Linking Dynamic Pricing With Shifted Product-Use in Residential Electricity Markets
Authors: Dunbar Samuel , Ferguson Scott
Published: November 2020

Demand Response (DR) is the implementation of a specific strategy or set of strategies, with the goal of altering consumer energy demand, such that some system level objectives are improved. These strategies typically include dynamic pricing, direct load control, policy implementation, or other financial incentives. DR will become a crucial tool for managing growing global energy demand in conjunction with higher penetration rates of intermittent renewable energy resources. Effective implementation of a DR strategy requires a realistic understanding of how consumers will respond to that strategy and how they will be affected by it. Here, a product-based decision model for residential consumers, that links consumer decisions directly to product-use, is revisited and adapted from a continuous time formulation to discrete time. The relationship between financial incentives, consumer preferences, and demand flexibility at the population level is then quantified. The model is used for exploring the tradeoffs between typical objectives for a dynamic pricing residential DR program and evaluating the characteristics of well-performing pricing solutions.
Neural Network Based Transfer Learning of Manipulator Inverse Displacement Analysis
Authors: Tang Houcheng , Notash Leila
Published: November 2020

In this paper, a neural network based transfer learning approach of inverse displacement analysis of robot manipulators is studied. Neural networks with different structures are applied utilizing data from different configurations of a manipulator for training purposes. Then the transfer learning was conducted between manipulators with different geometric layouts. The training is performed on both the neural networks with pretrained initial parameters and the neural networks with random initialization. To investigate the rate of convergence of data fitting comprehensively, different values of performance targets are defined. The computing epochs and performance measures are compared. It is presented that, depending on the structure of neural network, the proposed transfer learning can accelerate the training process and achieve higher accuracy. For different datasets, the transfer learning approach improves their performance differently.
Reconstruction of Ground Reaction Force Data Using Lyapunov Floquet Theory and Invariant Manifold Theory
Authors: Bhat Sandesh G. , Sugar Thomas G. , Redkar Sangram
Published: November 2020

Ground Reaction Force (GRF) is an essential gait parameter. GRF analysis provides important information regarding various aspects of gait. GRF has been traditionally measured using bulky force plates within lab environments. There exist portable force sensing units, but their accuracy is wanting. Estimation of GRF has applications in remote wearable systems for rehabilitation, to measure performance in athletes, etc. This article explores a novel method for GRF estimation using the Lyapunov-Floquet (LF) and invariant manifold theory. We assume human gait to be a periodic motion without external forcing. Using time delayed embedding, a reduced order system can be reconstructed from the vertical GRF data. LF theory can be applied to perform system identification via Floquet Transition Matrix and the Lyapunov Exponents. A Conformal Map was generated using the Lyapunov Floquet Transformation that maps the original time periodic system on a linear Single Degree of Freedom (SDoF) oscillator. The response of the oscillator system can be calculated numerically and then remapped back to the original domain to get GRF time evolution. As an example, the GRF data from an optical motion capture system for two subjects was used to construct the reduced order model and system identification. A comparison between the original system and its reduced order approximation showed good correspondence.
From Information to Ideas: How Designers Structure Information to Support Idea Generation
Authors: Damen Nicole B. , Toh Christine A.
Published: November 2020

Design can be seen as a series of decisions that are informed by information that the designer has gathered from the environment and transformed into actionable knowledge. The sheer volume and variety of available information compels designers to impose structure upon the desired information, which in turn may affect subsequent design activities. To better understand how information may inform design decisions, this study investigates the relationship between designers’ information organization behaviors and their generated ideas by recruiting eight professionals (four from software design and four from graphic design) for individual 3-hour design sessions. They were asked to generate ideas for a design problem (reducing pedestrian accidents in Nebraska) using the provided information. Results reveal that designers structured the information in three different ways (Clusters, Relations, and Nests), and both designer background and organizational strategy display different roles in the features generated in their ideas.
Six-Bar Linkages With Compliant Mechanisms for an Adaptive Robot
Authors: Pieber Michael , Gerstmayr Johannes
Published: November 2020

Programmable structures are formed by autonomous and adaptive triangular cells. However, they are composed of a large number of parts, specifically bearings, which make them laborious to manufacture and expensive. An essential part of these programmable structures are six-bar linkages, which allow to build cells that can preserve the underlying geometry of a triangular mesh. A major improvement, which is the main part of this paper, is to replace the joints of the six-bar-linkage by a compliant mechanism, which allows to manufacture them as one 3D printable part. A multibody system formulation is setup with the model of the compliant mechanisms, treating every joint either ideal or compliant with the given stiffness parameters. The multi-body formulation furthermore allows to include friction as well as an actuator model in a straight-forward manner. The overall stiffness parameter of the real system is then identified from a comparison with an experimental setup of a real compliant triangular cell. Finally, the model is used to show the deviations of a medium-scaled programmable structure with respect to the idealized behavior. The present paper marks a relevant step towards the realization of larger programmable structures as well as the development of 3D programmable structures.
Deployable Convex Generalized Cylindrical Surfaces Using Torsional Joints
Authors: Nelson Todd G. , Baldelomar Pinto Luis M. , Bruton Jared T. , Deng Zhicheng , Nelson Curtis G. , Howell Larry L.
Published: November 2020

The ability to deploy a planar surface to a desired convex profile can enhance foldable or morphing airfoils, deployable antennae and reflectors, and other applications where a specific profile geometry is desired from a planar sheet. A model using a system of rigid links joined by torsional springs of tailorable stiffness is employed to create an approximate curved surface when two opposing tip loads are applied. The physical implementation of the model uses compliant torsion bars as the torsion springs. A multidimensional optimization algorithm is presented to minimize the error from the rigid-link approximation and account for additional manufacturing and stress considerations in the torsion bars. A proof is presented to show that equal torsion spring spacing along the horizontal axis of deployed parabolic profiles will result in minimizing the area between the model’s rigid-link approximation and smooth curve. The model is demonstrated through the physical construction of a deployable airfoil surface and a metallic deployable parabolic reflector.
Thermo-Mechanical Coupling Characteristics of Dry Clutch Under Different Automotive Starting Modes
Authors: Wu Guangqiang , Li Pingyang
Published: November 2020

Both system dynamics simulation and numerical analysis have been conducted to study the effect of different automotive starting modes on the clutch thermo-mechanical coupling characteristics. Based on the six-degree-of-freedom dynamic model of the automotive driveline, the system dynamic responses were obtained under four different starting modes that are determined by the changes of pressure between the friction plate and pressure plate. According to the results of dynamic responses, the transient thermal analysis and thermo-mechanical coupling analysis of the clutch friction pair were performed using the finite element method assuming that the car is driving on the congested roads. The results show that as the starting time increases, the thermal-mechanical coupling characteristics of the clutch become sever, as the temperature and stress levels of the friction pair show a trend of slow and then rapid rise. Therefore, taking into account the requirements of both well starting riding comfort and clutch working conditions, it is recommended that the driver controls the starting time within a certain range when operating the clutch pedal.
The Presence of Culture in Student Designer Perceptions When Making Design Requirements: A Pilot Study
Authors: Agyemang Malena , Turner Cameron J.
Published: November 2020

Unaddressed cultural elements have prevented the adoption and diffusion of many humanitarian engineering and global development efforts. Design requirements act as the link between the designer and the target users. This pilot study looks at the perceptions of student designers when making design requirements, to understand what aspects of target user culture designers consider when making design requirements. This study also looks at how a formal method that encourages designers to use the culture of the target user to assess their design requirements affects the designers’ considerations when generating design requirements as well as the design requirements they generate. A quasi-experimental case study methodology was used for this study. Using a control group and an experimental group, student perceptions and design requirements were collected and compared to uncover the cultural considerations when making design requirements, their design requirements, and the effects on their cultural considerations and design requirements post-intervention. The study showed that the use of the formal method increased the designer’s consideration for target user culture when generating design requirements. However, the findings do not suggest that the intervention method alone altered the designer’s considerations and design requirements. This study acts as a pilot study to understand experimental design limitations that will be addressed in a larger study.
Evolution of Brain Network Connectivity in the Prefrontal Cortex During Concept Generation Using Brainstorming for a Design Task
Authors: Milovanovic Julie , Hu Mo , Shealy Tripp , Gero John
Published: November 2020

The research results presented in this paper explore the temporal changes in central regions of the prefrontal cortex (PFC) during design brainstorming. Design mobilizes a range of cognitive processes such as problem analysis and framing, concept generation, decision-making, visual reasoning and creative problem solving. Concept generation is supported by an iteration of divergent and convergent thinking. The process of brainstorming focuses primarily on divergent thinking. Measurement techniques from neuroscience were used to quantify neurocognitive activation during concept generation using brainstorming during a design task. Correlations in brain activation were used with graph theory to describe brain network connectivity and present the temporal evolution of network centrality in the PFC during brainstorming. The results reveal shifts of network centrality between the right, medial, and left PFC, suggesting possible shifts in the dominant cognitive functions between divergent and convergent thinking during design brainstorming. The alternations of centrality and connectivity between hemispheres provides a consistent mapping with the theory of dual reasoning process in prior design cognition studies. This empirical study with ten graduate engineering students offers initial results to further explore connections between brain network connectivity and cognitive processes when brainstorming during a design task. It provides new evidence to examine existing theories of design.
Topic Modeling and Sentiment Analysis of Social Media Data to Drive Experiential Redesign
Authors: Song Binyang , Meinzer Emmett , Agrawal Akash , McComb Christopher
Published: November 2020

The elicitation of customer pain points is a crucial early step in the design or redesign of successful products and services. Online, user-generated data contains rich, real-time information about customer experience, requirements, and preferences. However, it is a nontrivial task to retrieve useful information from these sources because of the sheer amount of data, often unstructured. In this work, we build on previous efforts that used natural language processing techniques to extract meaning from online data and facilitate experiential redesign and extend them by integrating a sentiment analysis. As a use case, we explore the airline industry. A considerable portion of potential passengers opt out of traveling by airplane due to aviophobia, a fear of flying. This causes a market loss to the industry and inconvenience for those who experience aviophobia. The potential contributors to aviophobia are complex and diverse, involving physical, psychological and emotional reactions to the air travel experience. A methodology that is capable of accommodating the complexity and diversity of the commercial airline industry user-generated data is necessary to effectively mine customer pain points. To address the demand, we propose a novel methodology in this study. Using passenger commentary data posted on Reddit, the method implements topic modeling to extract common themes from the commentaries and employs sentiment analysis to elicit and interpret the salient information contained in the extracted themes. This paper ends by providing specific recommendations that are germane to the use case as well as suggesting future research directions.
A Dual Quaternion Based Method for Estimating Margins for Planning Target Volumes in Radiotherapy
Authors: Ge Q. J. , Yu Zihan , Langer Mark
Published: November 2020

This objective of this paper is to develop a dual quaternion based method for estimating target volumes in radiation therapy for head and neck cancer. Inaccuracies in radiation targeting are responsible for incidental exposure of healthy adjacent tissues, causing significant morbidity and mortality. This paper focuses on inaccuracies incurred when a tumor is displaced during treatment. To address this problem, the clinical target must be expanded to cover the region through which the tumor might move. The resulting expanded target is known as the Planning Target Volume (PTV). In the current practice, the rotational components of displacements are neglected, producing planning target volumes that either miss the true target motion or are larger than needed to cover the target path. By using the dual quaternion based kinematic formulation, this paper represents and captures both translational and rotational inaccuracies. It then presents a framework for calculating the PTV swept out by the target as it shifts within its range of translations and rotations.
Towards an Understanding of Semantic Memory During Idea Generation
Authors: Mertens Attakias T. , McComb Christopher , Toh Christine A.
Published: November 2020

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. 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 Latent Semantic Analysis in order to assess the similarities between generated ideas, recall, and information pieces. Results from this were assessed for relationships using Spearman correlations and simple regression. This study was able to demonstrate memory usage within the early design process.
Life Cycle GHG Assessment of Mixed Construction and Demolition Waste Treatment for End of Life Recovery Facility Design: A Sydney, Australia Case Study
Authors: Moore Tahli , Zhang Hao
Published: November 2020

Historically in Australia, mixed Construction and Demolition waste, and Commercial and Industrial waste has been traditionally landfilled. As environmental impacts of landfilling is becoming more evident New South Wales policy makers and innovators have begun exploring an incineration strategy to use such waste to generate electricity. The objective of this study is to utilise life cycle assessment to evaluate GHG emissions from this waste treatment strategy and the environmental impact of a case study facility, in Sydney Australia. The system boundary includes the thermal treatment of waste through incineration, the electricity generation from the steam turbine and air pollution control processes involved within. The functional unit is based on 1 tonne of input mixed Construction and Demolition waste and Commercial and Industrial waste. GHG emissions are calculated and the result shows that the facility generates 0.994 MWh/tonne waste and 1.16 tCO2e/MWh electricity. This emission is lower than a brown coal fired powerplant emission factor 1.31 tCO2e/MWh. The results from this study assists understanding and policy making for the future of Energy-from-Waste as part of the generation mix in New South Wales, Australia.
Effects of Correlated Noise on the Performance of Persistence Based Dynamic State Detection Methods
Authors: Tempelman Joshua R. , Myers Audun , Scruggs Jeffrey T. , Khasawneh Firas A.
Published: November 2020

The ability to characterize the state of dynamic systems has been a pertinent task in the time series analysis community. Traditional measures such as Lyapunov exponents are often times difficult to recover from noisy data, especially if the dimensionality of the system is not known. More recent binary and network based testing methods have delivered promising results for unknown deterministic systems, however noise injected into a periodic signal leads to false positives. Recently, we showed the advantage of using persistent homology as a tool for achieving dynamic state detection for systems with no known model and showed its robustness to white Gaussian noise. In this work, we explore the robustness of the persistence based methods to the influence of colored noise and show that colored noise processes of the form 1/ f α lead to false positive diagnostic at lower signal to noise ratios for α < 0.
Dimensions of Similarity Used to Identify Products As Sources of Analogy
Authors: Tsoka Arnold N. , Tribaldos Jicmat Ali , Sen Chiradeep
Published: November 2020

This paper presents a human-subject experiment exploring the dimensions of product similarity that designers use to detect a product as a source of analogy during designing another. In the study, fifty voluntary participants are presented with a target product that is to be designed, and five other source products that are similar to the design task in various dimensions such as function, structure, or working principle. The designers are then asked to identify the products that they consider to be useful sources of analogy for designing the target, and to write in plain English why they considered so. These comments are analyzed using a protocol to reveal the dimensions of similarity between the target and the source product that inspired them to select the source. The data comprises of 2,440 total dimension instances among the participants. The results show that the identification of products as sources of analogy is driven by at least six dimensions: working principle, structure, human interaction, function, energy flows, and material flows. Among these, working principle, structure, and human interaction are more dominant than function, which was previously believed to be the sole driver of analogy.
Creating a Design for Inspectability Framework: Investigating DfAM Heuristics for Inspection Technologies
Authors: Mahan Tobias , Stover Micaela , Arguelles Andrea , Menold Jessica
Published: November 2020

Design heuristics created for additive manufacturing (AM) help designers increase manufacturability, reduce waste, and create novel geometries that are generally impossible to create with traditional manufacturing techniques. However, this new manufacturing method has come with its own challenges, specifically for inspection and quality assurance end use parts. Current methods for quality assurance and control are not capable of assessing quality of complex geometries or may be prohibitively expensive for AM produced components. By considering inspection early in the design process, designers can reduce the cost of quality control and prevent expensive redesign associated with non-inspectable components. The Design for Inspectability (DfI) worksheet proposed in the current work serves as a first step towards integrating quality control and quality assurance considerations into early stage design, specifically in the context of AM. The DfI worksheet can be used to assess if a part can be inspected for quality after production and can inform future iterations of design concepts. To determine if the worksheet assists designers in creating a component that can be assessed for quality, a controlled laboratory study was conducted. Findings suggest the worksheet effects design outcomes.
Development of a Robotic Landing System for UAVs Applied in Various Terrains
Authors: Peng Chengyang , Chowdhury A. M. Masum Bulbul , Cheng Jinsai , George Richard L. , Shen Tao
Published: November 2020

Unmanned Aerial Vehicles (UAVs), often referred as drones, have been widely implemented for civilian, commercial, search and rescue, and military operations with the advantages of easy deployment, low cost, automation, as well as, most importantly, allowing the execution of dangerous or difficult tasks remotely and safely. However, current UAVs are equipped with a skid or wheel landing gear that limits the application of UAVs to an even and flat ground for safe landing and taking off; this constraint impedes the development of UAVs for application in extreme environments, such as war fields and remote wilderness where proximate level ground is inaccessible. The ability of UAVs to land on un-level ground would help broaden the application of UAVs; in particular, the ability to go beyond thermal imaging to locate a lost hiker with the ability to land and deliver life-sustaining resources in a more timely manner offers a benefit to human rescue missions. This paper presents an innovative robotic landing system consisting of three slanted legs, each individually controlled by a motor. The footpad of each leg has an integrated force sensor for detecting ground touch. An inclinometer is installed on the platform of the landing system to sense the UAVs orientation during landing. Thus, the landing system can keep the platform horizontal when it lands on the ground by extending or retracting the legs. The feasibility and effectiveness of the robotic method have been demonstrated by several indoor and outdoor experiments.
Bayesian Optimization of Target Buckling Shapes in Constrained Elastomeric Beams With Geometric Uncertainty
Authors: Hertlein Nathan , Yoo David , Buskohl Philip R. , Vemaganti Kumar , Anand Sam
Published: November 2020

Additive manufacturing has enabled the fabrication of complex, architected materials, which have shown great promise in fields such as acoustics, mechanical logic gates, and energy trapping, due to their unique properties derived from repeating unit cells. The force-displacement performance of one such unit cell, the bistable elastomeric beam, has been characterized experimentally and subsequently tuned by the introduction of a Fourier series-based design parameterization that enables a wider range of available energy performance characteristics and secondary stable configurations. Here, another characteristic of this beam that has not yet been explored, namely the shape during post-buckling deformation between the two stable states, is optimized under the same Fourier series-based parameterization. Nonlinear finite element analysis reveals that the performance is highly sensitive to even modest profile error incurred on the beam’s upper and lower sides during manufacturing. Various methods of quantifying performance are compared, and Bayesian optimization is employed in two case studies to achieve desired post-buckled shapes. A novel acquisition function, which considers a candidate design’s robustness to profile error, is used to find the design that achieves the desired performance consistently, even in the face of the variability associated with additive manufacturing. Finally, Monte Carlo simulations are used to quantify the performance of optimal beams found with and without the new acquisition function, and reveal the importance of considering geometric uncertainty during the optimization process.
Off-Road Vehicle Path Planning Using Geodesics on a Multifactor Terrain Model
Authors: Barthlow Dakota , Pandey Vijitashwa , Gorsich David , Jayakumar Paramsothy
Published: November 2020

Optimal navigation of wheeled or tracked vehicles through a particular off-road terrain is primarily governed by terrain properties, and the capabilities of the vehicle itself. Reconciling vehicle operation with a terrain’s trafficability, termed mobility mapping, is a complex and multi-faceted problem that involves geophysics, vehicle dynamics, optimization, meta-modeling, and statistical modeling. A mobility map in turn informs path planning, which is the process of creating optimal routes through the trafficable areas to successfully arrive at a destination. This optimality can be in the sense of the length of the path taken, energy consumption, or any other metric that the operator considers important. This paper presents a procedure that first models the terrain by including factors affecting trafficability, uses a kriging interpolator for terrain modeling, then utilizes an existing path planning algorithm to create a rough path between start and goal points. Subsequently, a differential geometry based algorithm is presented to optimize the path. In the proposed method, the height of the terrain is augmented with multiple factors beneficial or detrimental to mobility to define a composite surface, thereby simultaneously considering them in path planning. A geodesic connecting the start and goal points is then found on this composite surface. We present examples on terrains acquired from geospatial data gateway of the United States Geological Survey, showing the efficacy of the method. Comparisons with an existing approach are made and avenues for future work are also identified.
Validation of an Analytical Model to Lower the Cost of Solar-Powered Drip Irrigation Systems for Smallholder Farmers in the Mena Region
Authors: Grant Fiona , Sheline Carolyn , Amrose Susan , Brownell Elizabeth , Nangia Vinay , Talozi Samer , Winter Amos
Published: November 2020

Drip irrigation is a micro-irrigation technology that has been shown to conserve water and significantly increase crop yield. This technology could be particularly beneficial to the world’s estimated 500 million smallholder farmers, but drip systems tend to be financially inaccessible to this population. Drip systems require costly components including a pipe network, emitters, a pump and power system. Due to limited access to electricity, many smallholder farmers would require off-grid solutions. Designing reliable, low cost, off-grid drip irrigation systems for smallholder farms could significantly reduce the barrier to adoption.

This paper builds on an integrated solar-powered drip irrigation model that was shown to improve upon an existing software. Field trials of the small-scale drip system were conducted on research farms in Jordan and Morocco for a full growing season. Data collected from these field trials are used to validate the hydraulics portion of the systems-level model. In addition, the insights gained from the field trials were formed into design requirements for future iterations of the model. These include optimizing for the system life cycle cost, as opposed to capital cost, the ability to simulate the system operation over a season, the capability to input a user’s irrigation schedule, incorporating locally-available components, and incorporating a system reliability constraint based on more detailed agronomic calculations.
Pilot Study: Investigating EEG Based Neuro-Responses of Engineers via a Modified Alternative Uses Task to Understand Creativity
Authors: Hartog Tess , Marshall Megan , Ahad Md Tanvir , Alhashim Amin G. , Okudan Kremer Gul , van Hell Janet , Siddique Zahed
Published: November 2020

Assessing creativity is not an easy task, but that has not stopped researchers from exploring it. Because creativity is essential to engineering disciplines, knowing how to enhance creative abilities through engineering education has been a topic of interest. In this paper, the event related potential (ERP) technique is used to study the neural responses of engineers via a modified alternative uses task (AUT). Though only a pilot study testing two participants, the preliminary results of this study indicate general neuro-responsiveness to novel or unusual stimuli. These findings also suggest that a scaled-up study along these lines would enable better understanding and modeling of neuroresponses of engineers and creative thinking, as well as contribute to the growing field of ERP research in the field of engineering.
Hybrid Modeling Approach for Melt Pool Prediction in Laser Powder Bed Fusion Additive Manufacturing
Authors: Moges Tesfaye , Yang Zhuo , Jones Kevontrez , Feng Shaw , Witherell Paul , Lu Yan
Published: November 2020

Multi-scale, multi-physics, computational models are a promising tool to provide detailed insights to understand the process-structure-property-performance relationships in additive manufacturing (AM) processes. To take advantage of the strengths of both physics-based and data-driven models, we propose a novel, hybrid modeling framework for laser powder bed fusion (L-PBF) processes. Our unbiased, model integration method combines physics-based data and measurement data for approaching more accurate prediction of melt-pool width. Both a high-fidelity computational fluid dynamics (CFD) model and experiments utilizing optical images are used to generate a combined dataset of melt-pool widths. From this aggregated dataset, a hybrid model is developed using data-driven modeling techniques, including polynomial regression and Kriging methods. The performance of the hybrid model is evaluated by computing the average relative error and comparing it with the results of the simulations and surrogate models constructed from the original CFD model and experimental measurements. It is found that the proposed hybrid model performs better in terms of prediction accuracy and computational time. Future work includes a conceptual introduction on the use of an AM ontology to support improved model and data selection when constructing hybrid models. This study can be viewed as a significant step towards the use of hybrid models as predictive models with improved accuracy and without the sacrifice of speed.
Comparing Segmentation Approaches for Learning-Aware Wireframe Generation on Human Model
Authors: Huang Jida , Kwok Tsz-Ho
Published: November 2020

Wireframe has been proved very useful for learning human body from semantic parameters. However, the definition of the wireframe is highly dependent on the anthropological experiences of experts in previous works. Hence it is usually not easy to obtain a well-defined wireframe for a new set of human models in the available database. To overcome such difficulty, an automated wireframe generation method would be very helpful in relieving the need for manual anthropometric definition. In order to find such an automated wireframe designing method, a natural way is using automatic segmentation methods to divide the human body model into small mesh patches. Nevertheless, different segmentation approaches could have various segmented patches, thus resulting in various wireframes. How these wireframes affect human body learning performance? In this paper, we attempt to answer this research question by comparing different segmentation methods. Different wireframes are generated with the mesh segmentation methods, and then we use these wireframes as an intermediate agent to learn the relationship between the human body mesh models and the semantic parameters. We compared the reconstruction accuracy with different generated wireframe sets and summarized several meaningful design guidelines for developing an automatic wireframe-aware segmentation method for human body learning.
Does It Translate? A Case Study of Conceptual Design Outcomes With U.S. and Moroccan Students
Authors: Peng Aoran , Menold Jessica , Miller Scarlett R.
Published: November 2020

High globalization in the world today results in the involvement of multi-discipline, multi-cultural teams, as well as the entrance of more economic powers in the market. Effective innovation strategies are critical if emerging markets plan to become economic players in this increasingly connected global market. The current work compares the design processes of designers from emerging and established markets to understand how design methods are applied across culture. Specifically, the design decisions of designers from Morocco, one of the four leading economic power in Africa, and the U.S. are investigated. Concept generation and selection are the focus of the current study as they are critical steps in the design process that can determine project outcomes. Previous studies have identified three factors, ownership bias, gender, and idea goodness as influential during concept selection. The effect of these three factors on designers in the United States is well established. The current study expands upon previous findings to examine the influence of these factors across two cultures — U.S. and Morocco. The results of this study, although preliminary, found that U.S. students had a higher idea fluency than Morocco students. It also found a significant difference in idea fluency between genders in the U.S. but not in Morocco. In addition, it was found that overall, participants exhibited ownership bias toward ideas with high goodness.
Scalable Thermal Simulation of Powder Bed Fusion
Authors: Zhang Yaqi , Shapiro Vadim , Witherell Paul
Published: November 2020

Powder bed fusion (PBF) has become a widely used additive manufacturing (AM) technology to produce metallic parts. Since the PBF process is driven by a moving heat source, consistency in part production, particularly when varying geometries, has proven difficult. Thermal field evolution during the manufacturing process determines both geometric and mechanical properties of the fabricated components. Simulations of the thermal field evolution can provide insight into desired process parameter selection for a given material and geometry. Thermal simulation of the PBF process is computationally challenging due to the geometric complexity of the manufacturing process and the inherent computational complexity that requires a numerical solution at every time increment of the process.

We propose a new thermal simulation of the PBF process based on the laser scan path. Our approach is unique in that it does not restrict itself to simulations on the part design geometry, but instead simulates the formation of the geometry based on the process plan of a part. The implication of this distinction is that the simulations are in tune with the as-manufactured geometry, meaning that calculations are more aligned with the process than the design, and thus could be argued is a more realistic abstraction of real-world behavior. The discretization is based on the laser scan path, and the thermal model is formulated directly in terms of the manufacturing primitives. An element growth mechanism is introduced to simulate the evolution of a melt pool during the manufacturing process. A spatial data structure, called contact graph, is used to represent the discretized domain and capture all thermal interactions during the simulation. The simulation is localized through exploiting spatial and temporal locality, which is based on known empirical data. This limits the need to update to at most a constant number of elements at each time step. This implies that the proposed simulation not only scales to handle three-dimensional (3D) printed components of arbitrary complexity but also can achieve real-time performance. The simulation is fully implemented and validated against experimental data and other simulation results.