bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimization Model for Owner-Based Microgrids Using LSTM Predicted Demand for Rural Development
Authors: Amaria Anosh P. , Nguyen Ryan , Davison Joshua A. , Chowdhury Souma , Hall John F.
Published: November 2019

Over the past several years, microgrids have been setup in remote villages in developing countries such as India, Kenya and China to boost the standards of living of the less privileged citizens, mostly by private companies. However, these systems succumb to increase in demand and maintenance issues over time. A method for scaling the capacity of solar powered microgrids is presented in this paper. The scaling is based on both the needs of the owner and those of the consumers. Data acquired from rural villages characterizes the electrical use with respect to time. Further, it employees a Long-Short Term Memory (LSTM) deep learning model that can help the owner predict future demand trends. This is followed by a model to determine the optimum increase in capacity required to meet the predicted demand. The model is based on empowering the owner to make informed decisions and the equity of energy distribution is the key motivation for this paper. The models are applied to a village in Eastern India to test its applicability. Acknowledging the highly varying nature of demand for electricity and its applications, we propose a rule-based adaptive power management strategy which can be tailored specifically in accordance to the preference of the communities. This will ensure a fair distribution of power for everyone using the system, thereby making it applicable anywhere in the world. We propose to incorporate social and demographic conditions of the user in the optimization to ensure that the profit of the owner does not outweigh the needs of the users.
Towards Thermal Simulation of Powder Bed Fusion on Path Level
Authors: Zhang Yaqi , Shapiro Vadim , Witherell Paul
Published: November 2019

Powder bed fusion (PBF) is a widely used additive manufacturing (AM) technology to produce metallic parts. Understanding the relationships between process parameter settings and the quality of finished parts remains a critical research question. Developing this understating involves an intermediate step: Process parameters, such as laser power and scan speed, influence the ongoing process characteristics, which then affect the final quality of the finished parts. Conventional approaches to addressing those challenges such as powder-based simulations (e.g., discrete element method (DEM)) and voxel-based simulations (e.g., finite element method (FEM)) can provide valuable insight into process physics. Those types of simulations, however, are not well-suited to handle realistic manufacturing plans due to their high computational complexity.

Thermal simulations of the PBF process have the potential to implement that intermediate step. Developing accurate thermal simulations, however, is difficult due to the physical and geometric complexities of the manufacturing process. We propose a new, meso-scale, thermal-simulation, which is built on the path-level interactions described by a typical process plan. Since our model is rooted in manufactured geometry, it has the ability to produce scalable, thermal simulations for evaluating realistic process plans. The proof-of-concept simulation result is validated against experimental results in the literature and experimental results from National Institute of Standards and Technology (NIST).

In our model, the laser-scan path is discretized into elements, and each element represents the newly melted material. An element-growth mechanism is introduced to simulate the evolution of the melt pool and its thermal characteristics during the manufacturing process. The proposed simulation reduces computational demands by attempting to capture the most important thermal effects developed during the manufacturing process. Those effects include laser-energy absorption, thermal interaction between adjacent elements and elements within the underneath substrate, thermal convection and radiation, and powder melting.
Classification of a Class of 3-RER Parallel Manipulators Using Gröbner Cover and Primary Decomposition of Ideals
Authors: Kong Xianwen
Published: November 2019

Recent studies have revealed that the type/number of operation modes of a parallel manipulator (PM) may vary with the link parameters of the PM. However, current research on the impact of link parameters on the type/number of operation modes of a PM is usually based on intuition. This paper deals with the systematic classification of a 3-RER PM. The 3-RER PM is composed of a base and a moving platform connected by three RER legs, each of which is a serial kinematic chain composed of a revolute (R) joint, a planar (E) joint and an R joint in sequence. The axes of the R joints on the base (or moving platform) are all parallel. At first, a set of constraint equations of the 3-RER PM is first derived. Then using a method called Gröbner cover to calculate the comprehensive Gröbner system of parametric polynomial systems, the 3-RER PM is classified into 21 types. The operation modes of all the types of 3-RER PMs are determined using primary decomposition of ideals. Besides the two 4-DOF (degree-of-freedom) 3T1R operation modes, different types of 3-RER PMs may have up to two more 3-DOF or other types of 4-DOF operation modes. This work is the first systematic study on the impact of link parameters on the operation modes of the 3-RER PM and will contribute to the design and control of 3-RER PMs and research on multi-mode (or reconfigurable) PMs.
Design of an Underactuated Legged Robot With Prismatic Legs for Passive Adaptability to Terrain
Authors: Noh Seonghoon , Dollar Aaron
Published: November 2019

Legged robots have the advantage of being able to maneuver unstructured terrains unlike their wheeled counterparts. However, many legged robots require multiple sensors and online computations to specify the gait, trajectory or contact forces in real-time for a given terrain, and these methods can break down when sensory information is unreliable or not available. Over the years, underactuated mechanisms have demonstrated great success in object grasping and manipulation tasks due to their ability to passively adapt to the geometry of the objects without sensors. In this paper, we present an application of underactuation in the design of a legged robot with prismatic legs that maneuvers unstructured terrains under open-loop control without any sensing. Through experimental results, we show that prismatic legs can support a statically stable stance and can facilitate locomotion over unstructured terrain while maintaining its body posture.
Singularities in Axisymmetric Vectoring Exhaust Nozzle and a Feasible Singularity-Free Approach
Authors: Yu-Tong Li , Yu-Xin Wang
Published: November 2019

The singularities are the inherent disadvantage of parallel manipulators, which negatively influence the static properties and motion concreteness of parallel manipulators. An axisymmetric vectoring exhaust nozzle (AVEN), which turn and/or vector the exhaust flow and thrust of the gas turbine engine powering the aircraft, is driven by a symmetrical parallel manipulator to vector the exhaust nozzle universally. The serious negative influences of the singularities existing in the AVEN on the safety and maneuverability of the aircrafts have not been paid enough attention or aware of by the experts in the field. In this paper, two kinds of singularities existing in the AVEN for the nozzle vectoring drive mechanism of the parallel manipulator and the suspending mechanism of the divergent flaps are analyzed at first. To solve these singularities problem and ensure the safety of the aircrafts equipped with the AVEN, a feasible singularity-free approach for parallel manipulators applied in aerospace engineering via adjusting the input kinematic parameters is proposed.
Driver-Friendly Emergency Collision Avoidance System via Flatness Direct Yaw Moment Control
Authors: Wang Zejiang , Wang Junmin
Published: November 2019

Unlike an autonomous driving system, a shared control system keeps the driver in the loop to exploit human’s decision-making, path-planning, and control skills in vehicle motion control. In the meantime, a shared control system consistently provides support to the driver in hazardous situations. Typical shared control systems concentrate on altering vehicle steering actions through either active front steering or haptic steering torque. However, an active front steering system requires costly hardware and a haptic steering torque explicitly interferences with the driver hand-wheel steering. To overcome the drawbacks of the steering-based strategies, this paper introduces a driver support system based on direct yaw moment control for highspeed collision avoidance maneuvers. The new system maintains a hierarchical structure with a high-level lateral velocity planner and a low-level lateral velocity governor. In addition, the personally-preferred collision avoidance trajectories of each driver are taken into account to make the controller personalizable. Carsim-Simulink joint simulations demonstrate that this novel shared control system can successfully assist the driver in high-speed collision avoidance maneuvers. Moreover, both physical and mental loads of the driver are substantially reduced in contrast to using an active front steering system.
Do Autonomous Vehicle Driving Styles Affect User State?: A Preliminary Investigation
Authors: Shi Yuan , Huang Wenhui , Cheli Federico , Bordegoni Monica , Caruso Giandomenico
Published: November 2019

A bursting number of achievements in the autonomous vehicle industry have been obtained during the past decades. Various systems have been developed to make automated driving possible. Due to the algorithm used in the autonomous vehicle system, the performance of the vehicle differs from one to another. However, very few studies have given insight into the influence caused by implementing different algorithms from a human factors point of view. Two systems based on two algorithms with different characteristics are utilized to generate the two driving styles of the autonomous vehicle, which are implemented into a driving simulator in order to create the autonomous driving experience. User’s skin conductance (SC) data, which enables the evaluation of user’s cognitive workload and mental stress were recorded and analyzed. Subjective measures were applied by filling out Swedish occupational fatigue inventory (SOFI-20) to get a user self-reporting perspective view of their behavior changes along with the experiments. The results showed that human’s states were affected by the driving styles of different autonomous systems, especially in the period of speed variation. By analyzing users’ self-assessment data, a correlation was observed between the user “Sleepiness” and the driving style of the autonomous vehicle. These results would be meaningful for the future development of the autonomous vehicle systems, in terms of balancing the performance of the vehicle and user’s experience.
Objective Characterization of Brake Systems in Motorcycles
Authors: Eisele Andreas , Diermeyer Frank , Lienkamp Markus
Published: November 2019

This research presents an objective approach to the brake characteristics of state-of-the-art hydraulic motorcycle brake systems.

Research in literature reveals a lack of objective characterization criteria for motorcycles. The relevant characteristic parameters from studies on car brake systems are used to develop a measuring unit meeting the demands for a mobile, reproducible and precise testing system. The concept and validation of this device is presented. This measuring device has been used to measure different motorcycles representing different concepts, and their brake characteristics are shown. The effects on the brake stiffness of typical brake uncertainties, such as air intrusion, are measured and presented.

As the automobile brake system is a typical human machine interface used to control deceleration, both technical system parameters and psychophysical aspects are considered in order to objectify the brake characteristic. As a result, this research provides a novel definition of the colloquial pressure point, using measurable parameters such as the pedal characteristic defined by force as a function of displacement. Through an analytical approach two characteristic points, representing the force feedback at the lever and the deceleration feedback of the vehicle are defined. The difference between these points is an objective measure for controllability of the brake system.

The results show that the characteristics of a brake system depend on its specific components as well as the actuation velocity. For the first time, an objective explanation is found for the poor controllability of a brake system with entrained free air.
Kinematic Modeling of Origami-Based Forcep Designs
Authors: Abulon Dina Joy K. , McCarthy J. Michael
Published: November 2019

In the design of practical grasping tools such as forceps or grippers, it may be desirable to create a compact, lightweight, and easily manufactured tool. Origami inspired designs can help simplify gripper manufacturing to a single planar sheet of material while still allowing for deployment and actuation. Inflatable structures can reduce weight and be compacted. This paper explores the design of an inflatable, deployable, action origami inspired gripper through the development of a predictive model, prototype fabrication, and preliminary design assessments.
Global Emulation Through Normative Decision Making and Thrifty Adaptive Batch Sampling
Authors: van Beek Anton , Tao Siyu , Chen Wei
Published: November 2019

We consider the problem of adaptive sampling for global emulation (metamodeling) with a finite budget. Conventionally this problem is tackled through a greedy sampling strategy, which is optimal for taking either a single sample or a handful of samples at a single sampling stage but neglects the influence of future samples. This raises the question: “Can we optimize the number of sampling stages as well as the number of samples at each stage?” The proposed thrifty adaptive batch sampling (TABS) approach addresses this challenge by adopting a normative decision-making perspective to determine the total number of required samples and maximize a multistage reward function with respect to the total number of stages and the batch size at each stage. To amend TABS’ numerical complexity we propose two heuristic-based strategies that significantly reduce computational time with minimal reduction of reward optimality. Through numerical examples, TABS is shown to outperform or at least be comparable to conventional greedy sampling techniques. In this fashion, TABS provides modelers a flexible adaptive sampling tool for global emulation, effectively reducing computational cost while maintaining prediction accuracy.
Finite-State Automata-Based Representation of Device States for Function Modeling and Formal Definitions of Signal-Processing Functions
Authors: Chowdhury Ahmed , Mao Xiaoyang , Venkatanarasimhan Lakshmi N. A. , Sen Chiradeep
Published: November 2019

Graph-based function models used in early-stage systems design usually represent only one operational state and mode of the system. Currently, there is a need, but no rigorous formalism to model the different modes in the function model and logically predict the effects of the system transitioning between the modes. This paper presents a representation of operational modes and states of technical systems based on automata theory for both discrete and continuous state transitions. It then presents formal definitions of three signal-processing verbs that actuate or regulate energy flows: Actuate_E, Regulate_E_Discrete, and Regulate_E_Continuous. The graphical templates, definitions, and application of each verb in modeling is illustrated. Finally, a system-level model is used to illustrate the verbs’ modeling and reasoning ability, in terms of cause-and-effect propagation and the systems’ transition between operational modes.
An Extreme User Approach to Identify Latent Needs: Adaptation and Application in Medical Device Design
Authors: Raviselvam Sujithra , Subburaj Karupppasamy , Wood Kristin L. , Hölttä-Otto Katja
Published: November 2019

The perspectives of users who experience any form of physical or cognitive challenges have the potential to capture the latent design needs of the general population of users. These ‘extreme user perspectives’ are some of the extreme conditions that could influence the users’ experience with a design. This study applies a systematic approach that provides a step by step guidance to select the appropriate extreme user perspectives during the initial stages of a design process. This systematic approach is applied to identify the latent needs associated with six different medical devices. This research leverages the potential of simulated extreme user perspectives to amplify designers’ abilities to identify latent unarticulated needs through an empathic experience. The extreme user perspectives in this study are derived from user Activity Diagrams that represent the user interactions associated with the corresponding medical devices. A latency metric is introduced and evaluated for its potential to identify the latent needs. Six teams from a Healthcare Product Design course with 25 participants were involved in the study. Results demonstrate the application and effectiveness of the proposed systematic approach to capture the latent needs associated with all six devices. The potential applications of the proposed latency metric are discussed for future applications.
Exploring the Effectiveness of Providing Structured DfE Design Strategies During Conceptual Design
Authors: Ross Donovan , Ferrero Vincenzo , DuPont Bryony
Published: November 2019

The fuzzy front end of engineering design can present a difficult challenge, and as such, recent engineering design research has focused on guiding and influencing the way a designer ideates. Early ideation can be especially difficult when attempting to integrate specific design objectives in product design, called Design for X (DfX). Some examples of DfX are Design for Manufacturing (DfM), Design for Assembly (DfA), Design for Function (DfF), and Design for Safety (DfS). This paper will present two experiments exploring the efficacy of a structured Design for the Environment (DfE) design method called the GREEn Quiz (Guidelines and Regulations for Early design for the Environment) that provides designers with sustainable design knowledge during the conceptual design phase. The GREEn Quiz operates on a web-based platform and queries the designer about their design concepts; an end-of-quiz report provides abstract DfE knowledge to designers. While this abstract knowledge was able to be applied by designers in a former study, we hypothesize that providing targeted, specific design strategies during conceptual design may enable better integration in concept generation by novice designers. In this study, we created these DfE strategies, embedded these in the GREEn Quiz, and studied the efficacy of these strategies when presented to designers at both the expert and novice levels. Experimental results suggest that respondents with access to the strategy-based GREEn Quiz produced concepts with evidence of more sustainable design decisions and higher solution quality scores when compared to previous respondents and the control groups. This research encourages the consideration of downstream environmental impact knowledge during conceptual design, resulting in lower-impact products regardless of the previous DfE expertise of the designer.
Design and Tensorial Characterization of Rectangular Harmonic Shape-Morphing Mechanism Arrays
Authors: Lusk Craig
Published: November 2019

Shape-Morphing Mechanism Arrays (SMMAs) can be made by arraying harmonic four-bar mechanisms, i.e. four-bar mechanisms with a particular structure that insures high levels of symmetry. This paper discusses a particular genre of harmonic mechanism array that can forms rectangular grids without requiring the exclusive use of parallel mechanisms. Such arrays can be designed to preserve their harmonic (highly symmetric) structure through-out their range of motion, producing arrays capable of large deformations that nevertheless can be characterized by a 2D tensor, specifically, rectangular arrays deform as parallelograms.
Real-Time Simulation of Unmanned Rotorcraft With Ground Effect Through Adjoint Theorem
Authors: Huang Jianzhe
Published: November 2019

Unmamned rotorcraft requires automatic control system to adjust transient flight behaviors properly, and real-time computation of aerodynamic forces is also in demand. Finite-state inflow model is one of the most efficient models which can fulfill such a requirement. When a rotorcraft is flying close to ground, a strong downwash impinges on the ground surface and reflected airstream influences the flow field of the main rotor. Such a physical phenomenon makes the aerodynamic computations complex, and previous studies have solved such a problem by simulation ground effect with a ground rotor. But it still requires numerical integration to compute the flow field of main rotor downstream, and the computational efficiency degrades evidently. In this paper, adjoint theorem is proposed to calculate induced velocity in the rotor wake with closed form equations. The hover and forward flight conditions will be examined for different moment of inertia of blade and forward flight speeds.
Physics-Based Function Features for a Set of Material-Processing Verbs
Authors: Venkatanarasimhan Lakshmi N. A. , Mao Xiaoyang , Chowdhury Ahmed , Sen Chiradeep
Published: November 2019

Features are used in computer aided geometric modeling to encapsulate primitive and lower-abstraction entities to compose higher-level complex entities in order to support faster modeling, consistent data structures between features within the model, and feature-level reasoning that extends beyond reasoning supported by the primitives. In this paper, this idea is extended to computer-aided function modeling. Four function modeling features, which mainly operate on material flows but also involved energy flows, are formally defined. These features are: (1) Convergize_EM, (2) Handover_E, (3) Change_M, and (4) Changeover_EM. Each feature is composed of formerly established functional primitives that are formally defined, and by connecting those primitives in a controlled topology enforced by a feature-level grammar. The ability of these features to support consistent function modeling and model-based reasoning is illustrated using applications, both at the device level (simpler models) and at the system level (more complex models).
An Experimental Investigation of the Impact of Random Spacing Errors on the Dynamic Transmission Error of Spur Gear Pairs
Authors: Anandika Muhammad Nevin , Kahraman Ahmet , Talbot David
Published: November 2019

Noise and vibration performance of a gear system is critical in any engineering industry. Excessive vibrational amplitudes originated by the excitations at the gear meshes propagate to the transmission housing to cause noticeable noise, while also increasing gear tooth stresses to degrade durability. As such, gear designers must generate designs that are nominally quiet with low-vibration amplitudes. This implies a gear pair fabricated exactly to the specifications of its blue print will be acceptable for its vibration behavior. Achieving this, however, is not sufficient. As the manufacturing of gears require them to be subject to bands of tolerances afforded by the manufacturing processes employed, the designers must be concerned about variations to the performance of their presumably quite baseline designs within these tolerance bands. This research aims at demonstrating how one type of manufacturing error, random tooth spacing errors, alter the vibratory behavior of a spur gear pair.

Two pairs of spur gears are tested for their dynamic transmission error performance. One gear pair with no tooth spacing errors form the baseline. The second gear pair contain an intentionally induced random sequence of spacing errors. The forced vibration responses of both gear pairs are compared within wide ranges of speed and torque. This comparison shows that there is a clear and significant impact of random spacing errors on spur gear dynamics, measurable through examination of their respective transmission error signatures. In the off-resonance regions of speed, vibration amplitudes of the random error pair are higher than the no-error baseline spur gear pair. Meanwhile, at or near resonance peaks, the presence of random spacing errors tends to lower the peak amplitudes slightly as compared to the no-error baseline spur gear pair. The presence of random spacing errors introduces substantial harmonic content that are non-mesh harmonics. This results in a broadband frequency spectrum in addition to an otherwise well-defined frequency spectrum with gear-mesh order components, pointing to an additional concern of noise quality.
Extraction and Analysis of Spatial Correlation Micrograph Features for Traceability in Manufacturing
Authors: Dachowicz Adam , Atallah Mikhail , Panchal Jitesh H.
Published: November 2019

We propose a method for ensuring traceability of metal goods in an efficient and secure manner that leverages data obtained from micrographs of a part’s surface that is instance-specific (i.e., different for another instance of that same part). All stakeholders in modern supply chains face a growing need to ensure quality and trust in the goods they produce. Complex supply chains open many opportunities for counterfeiters, saboteurs, or other attackers to infiltrate supply networks, and existing methods for preventing such attacks can be costly, invasive, and ineffective. The proposed method extracts discriminatory-yet-robust intrinsic strings using features extracted from two-point autocorrelation data of surface microstructures. Using a synthetic dataset of three-phase micrographs similar to those obtained from metal alloy systems using low-cost optical microscopy techniques, we discuss the optimization of the method with respect to cost and security, and discuss the performance of the method in the context of anti-counterfeiting. Cryptographic extensions of this methodology are also discussed.
Using Automated Use Case Generation for Early Design Stage Functional Failure and Human Error Analysis
Authors: Irshad Lukman , Demirel H. Onan , Tumer Irem Y.
Published: November 2019

Human errors and poor ergonomics are attributed to a majority of large-scale accidents and malfunctions in complex engineered systems. Human Error and Functional Failure Reasoning (HEFFR) is a framework developed to assess potential functional failures, human errors, and their propagation paths during early design stages so that more reliable systems with improved performance and safety can be designed. In order to perform a comprehensive analysis using this framework, a wide array of potential failure scenarios need to be tested. Coming up with such use cases that can cover a majority of faults can be challenging or even impossible for a single engineer or a team of engineers. In the field of software engineering, automated test case generation techniques have been widely used for software testing. This research explores these methods to create a use case generation technique that covers both component-related and human-related fault scenarios. The proposed technique is a time based simulation that employs a modified Depth First Search (DFS) algorithm to simulate events as the event propagation is analyzed using HEFFR at each timestep. This approach is applied to a hold-up tank design problem and the results are analyzed to explore the capabilities and limitations.
Pixel to Stroke Sketch Generation Using Reinforcement Learning
Authors: Wang Haizhou , Tucker Conrad
Published: November 2019

Many engineering design tasks involve creating early conceptual sketches that do not require exact dimensions. Although some previous works focus on automatically generating sketches from reference images, many of them output exactly the same objects as the reference images. There are also models that generate sketches from scratch, which can be divided into pixel-based and stroke-based methods. Pixel-based methods generate sketches as a whole, without any information of the strokes, while stroke-based methods generate sketches by outputting strokes in a sequential manner. Pixel-based methods are frequently used to generate realistic color images. Although the pixel-based methods are more popular, stroke-based methods have the advantages to scale to a larger dimension without losing high fidelity. An image generated from stroke-based methods has only strokes on the canvas, resulting in no random noise in the blank areas of the canvas. However, one challenge in the engineering design community is that most of the sketches are saved as pixel-based images. Furthermore, many non-pixel-based methods rely on stroke-based training data, making them ill-suited for generating design conceptual sketches. In order to overcome these limitations, the authors proposed an agent that can learn from pixel-based images and generate stroke-based images. An advantage of such an agent is the ability to utilize pixel-based training data that is abundant in design repositories, to train stroke-based methods that are typically constrained by the lack of access to stroke-based training data.
A Performance Comprehension of Various Numerical Estimators for Variance-Based Sensitivity Analysis in Building Energy Simulations
Authors: Koosha Rasool , Shahsavari Fatemeh
Published: November 2019

In the building energy performance simulation, the uncertainty analysis (UA) couples to the sensitivity analysis (SA) to handle ever-existing uncertainties; induced by the sources of uncertainty including random occupants behavior and degradation of building materials over time. As a building simulation tool reaches to a high level of complexity, it becomes more challenging for the sensitivity analysis to deliver reliable outputs; thus the accuracy of the SA results substantially depends upon the number of sample sets or the type of analysis performed. This paper describes a variance-based SA tool integrated into a building Resistance-Capacitance (RC) thermal model. Then, for a hypothetical residential building test case, three distinct first-order sensitivity index simulators and three total sensitivity index simulators are implemented and compared in terms of the dependency of results on the sample size, i.e., the demand for the computational cost.
A Physics-Based Formal Vocabulary of Energy Verbs for Function Modeling
Authors: Sen Chiradeep , Summers Joshua D. , Mao Xiaoyang
Published: November 2019

Function modeling of complex systems relies on predefined vocabularies of functions and flows. These vocabularies are usually developed in a top-down approach, i.e., by starting with a survey of existing systems and identifying their functions empirically. These vocabularies, while highly useful in manual modeling due to their expressive power and coverage, can be unsuitable for computerized modeling and reasoning, esp. for physics-based reasoning. To this end, this paper presents a physics-based vocabulary of function verbs developed using the bottom-up approach, where the need for the verbs is identified through a survey of physics phenomena involving operations on various energy forms allowed in physics. This survey results in a minimal set of only six verbs and two logical nodes that are proposed here. Each term is formally defined as object-oriented classes derived from more foundational classes proposed in prior research. The paper shows many applications of these terms, for modeling both simpler devices and more complex engineered systems. Collectively, this new vocabulary provides sufficient coverage over modeling needs and ensures models that are logically consistent and physics-wise valid.
An Uncertainty and Sensitivity Analysis Tool for Building Thermal Energy Consumption: A Performance Comprehension of Static and Dynamic Response Analyses
Authors: Koosha Rasool , Shahsavari Fatemeh
Published: November 2019

Recent literature on building energy performance simulation leans toward implementing uncertainty analysis (UA), instead of deterministic solutions, to handle ever-existing and pivotal uncertainties in building design decision-making process. Variations in weather temperature, degradation of building envelope material properties over time, and random behavior of occupants, among all, are the key sources of uncertainty in building energy consumption predictions. The UA couples to the sensitivity analysis (SA) to identify the most influential inputs on the uncertainties of the building energy consumption. This paper describes a newly-developed UA and SA predictive tool for building energy performance simulations. Energy performance simulations are based on a resistance-capacitance thermal model for the building.

For a hypothetical residential building in College Station, Texas, USA, the present work describes and compares predicted probability distribution and sensitivity indexes produced by the UA-SA tool using a transient (dynamic) response analysis (TRA) and static response analysis (SRA). For brevity, the analysis considers uncertainty only for the exterior walls’ parameters including thickness, thermal conductivity, heat transfer coefficient, density, and heat capacity; i.e., a five-dimensional problem is solved. Compared to the TRA, predictions from the SRA underestimate the annual energy consumption up to 30%; however, SRA is significantly faster. Nonetheless, sensitivity indexes from the SRA and TRA closely match.
Reuse Potential of Used Textiles for American Industries
Authors: Bashir Asad , Clarke-Sather Abigail R.
Published: November 2019

Increasing the recovery of textiles from municipal solid waste (MSW) is important for improving environmental sustainability. In 2015, over 10.5 million tons of textile waste was landfilled, which is 7.6% of total landfilled MSW according to the U.S. EPA. For all materials, recycling in the U.S. has increased over the past decade to 25.8% of the weight of the waste generated, textile recycling is below this level at 15.3%. This research quantifies the availability of used textiles by material type from Goodwill of Delaware (Goodwill-DE), a thrift store franchise, between 2012 and 2014. It examines the feasibility of recycling this amount of available discarded textiles, specifically cotton, into U.S. industrial subsectors that traditionally use new cotton textiles. A hybrid product model was created using EIO-LCA to compare economic and environmental impacts in the cut and sew apparel, airplane and automotive seating, upholstered furniture, and textile bag manufacturing industrial subsectors. Economic impacts on supply purchases and profits were considered. Environmental impacts in energy use and CO2 equivalent emissions were examined. As a result, utilizing all of Goodwill-DE’s annual discarded cotton textiles by the cut and sew apparel industrial subsectors would have positive impacts in terms of supply purchase and energy savings and reduction in CO2 equivalent emissions, but negative impacts on profits. Supply purchase savings are greater than the profit loss, resulting in a net economic gain for the cut and sew apparel industrial subsectors. Of the seven industrial subsectors considered, the U.S. cut and sew apparel industries would benefit the most from utilizing used cotton textiles.
Classification of Compliant Mechanisms and Determination of the Degrees of Freedom Using the Concepts of Compliance Number and Pseudo-Rigid-Body Model
Authors: Bagivalu Prasanna Pratheek , Midha Ashok , Bapat Sushrut G.
Published: November 2019

Understanding the kinematic properties of a compliant mechanism has always proved to be a challenge. A concept of compliance number offered earlier emphasized the development of terminology that aided in its determination. A method to evaluate the elastic degrees of freedom associated with the flexible segments/links of a compliant mechanism using the pseudo-rigid-body model (PRBM) concept is provided. In this process, two distinct classes of compliant mechanisms are developed involving: (i) Active Compliance and (ii) Passive Compliance. Furthermore, these also aid in a better characterization of the kinematic behavior of a compliant mechanism. A more lucid interpretation of the significance of compliance number is provided. Applications of this method to both active and passive compliant mechanisms are exemplified. Finally, an experimental procedure that aids in visualizing the degrees of freedom as calculated is presented.
Evolution of Transferred Lubricant Distributions on the Slider Surface Under Ambient and Laser-Heating Conditions
Authors: Hetzel Ryan W. , Wang Shao , Lawry Jonathon R. , Alsafwani Ahmed H.
Published: November 2019

The dynamic equilibrium among the condensation, evaporation and shear flow of the lubricant on a slider has been modeled by solving a continuum-based partial differential equation, with temperatures obtained from a finite element model. Zero-flux and specified-flux boundary conditions were used to study the trailing pad of a slider. The results show that the average lubricant thickness on the trailing pad gradually approaches a steady state, and the steady-state value increases with increasing disk lubricant thickness. A reduction of the flying height leads to a reduced steady-state slider lubricant thickness. The temperature rise of the disk surface tends to promote the lubricant transfer to the slider in a region close to the trailing edge. However, this effect may be locally suppressed by the laser-induced local thinning of the lubricant film on the disk.
Design of a Magnetorheological Finishing Tool Manipulated by a Mechanical Magnetic Switch for Magnetic Field Assisted Finishing
Authors: Lee Ping-Hsun , Chang Jen-Yuan (James)
Published: November 2019

In this study we proposed a finishing tool where a slurry composited of magnetorheological (MR) fluid and abrasive particle was utilized as the polishing medium such that the rheological property and corresponding abrasive property could be controlled by changing the magnetic field. The MR abrasive fluid is magnetized by a permanent magnet. With a design of a steel C-shape structure (C-Structure) the magnetic field generated by the magnet can be directed to the tool tip. With a movable slider as a gate of the C-Structure the magnetic field directed to the tip can be adjusted continuously. The slurry was supplied from the tail and reached the tip through a fluid channel in the center of the tool. While the tool rotates with its tip near a workpiece filled with the magnetized slurry, the finishing machining process can be achieved. The usage of this finishing tool was designed to be similar as a conventional milling cutter’s tool allowing for handling surfaces of complex 3D geometries.
Eye-in-Hand Robotic Gripper Vision Fusion for Object Recognition and Tracking
Authors: Liu Shih-Wei , Chang Jen-Yuan (James)
Published: November 2019

With the development of Automation industry, a new industrial model has been born, and traditional human resources have gradually been replaced by machines. The World Economic Forum (WEF) pointed out in “The Future of Jobs Report 2018” that the world is experiencing a “workplace revolution”, which means that machine will play a more important role in the future. In response to this situation, in this paper, techniques for object recognition and tracking on a conveyor using eye-in-hand gripper are presented, which are useful in production line for automatic object classification. The eye-in-hand configuration is the most suitable for camera and gripper application because the camera coordinate is the same as the gripper coordinate. The main advantages of eye-in-hand configuration are as follow: (1) occlusion avoidance (2) intuitive teleoperation (3) image from different angles (4) simple calibration. The main difference with eye-on-hand configuration is that it may be out of view sight when the camera is too close to the object. The experimental result is using the eye-in-hand robotic gripper to establish a tracking system to chase the target object. Preliminary results show that the speed of the conveyor can be calculated and the moving distance between the robot and the object is very close after a period of time. It means that the tracking system is successful.
An Electromagnetic Targeting System With Semi-Circular Configuration for Navigating Endo-Bronchoscope
Authors: Hsu Shao-Wei , Lin Ching-Kai , Chen Chin-Chung , Cheng Yun-Chien , Chang Chen-Wei , Chung Tien-Kan
Published: November 2019

In this paper, we present an electromagnetic targeting system with semi-circular configuration for navigating endo-bronchoscope. This system consists of a magnetic-flux emitting electromagnets-arrays fixed on a semi-circular mechanical-support, magnetic-flux receiving electromagnets, and a magnetic-flux concentrator (i.e., silicon-steel collar) which fixed on distal end of a guide sheath of the endo-bronchoscope. In initial state, when the emitting electromagnets produce magnetic flux in sequence, the receiving electromagnets receive the magnetic flux and consequently produce voltage outputs by the electromagnetic induction. When the silicon-steel collar with the guide sheath travels through the system, the magnetic flux is concentrated by the collar. Thus, the voltage outputs of the receiving electromagnets are changed. By analyzing the change of voltage outputs, the location of the silicon-steel collar with the guide sheath is obtained/targeted. This means that the location of the endo-bronchoscope is also targeted.
Examination and Analysis of Four-Phase Four-Fluid Flow Techniques in Offshore Pipelines
Authors: Odan Mohamed , Ben Rajeb Faraj , Rahman Mohammad Azizur , Aborig Amer , Imtiaz Syed , Zhang Yan , Awad Mohamed M.
Published: November 2019

Many offshore drilling sites are plagued by infrastructure break-downs and other issues due to the complexity of the systems required for the subsea extraction of oil and gas (O&G). For the most part, the O&G industry uses multi-phase and multi-component pipeline flows to move their product from one site to another or to different areas of the same site. In extreme environments, such as offshore or Arctic sites, the development of Sand particles along the pipelines can bring additional challenges to the project. The present work examines the practicality of applying a system of four-phase four-fluid flows for transporting a multi-phase flow (sand, water, oil and CO2) along subsea pipelines. As a means for precisely measuring and predicting the characteristics of thermo- and hydro-dynamic multi-component mixtures, models representing phase behavior and hydrate equilibrium are built and tested. Additionally, the study looks at heat transfer, mass and momentum in both the flow and pipe walls and develops equations to describe their interrelationships. Another focus of this work it to investigate four-phase multi-component flow systems in order to obtain a deeper understanding of transient flow in various types of pipes, including conditions around the system of four-phase four-fluid flows, and hydro-dynamic variable effects on flow.
An Efficient System Reliability Approach Against Mooring Overload Failures
Authors: Leong Darrell , Low Ying Min , Kim Youngkook
Published: November 2019

As exploration for hydrocarbon resources venture into deeper waters, offshore floating structures are increasingly required to be stationed at sites of highly uncertain environmental loading conditions. Driven by high historical mooring failure rates of severe consequences, the need for effective long-term structural reliability methods arises for mooring lines. However, system nonlinearities, high problem dimensionality, and the diversity of conceivable failure causalities their extremely low probabilities complicates the analysis. Variations on the Monte Carlo approach are robust in addressing these challenges, but at the expense of high computational costs. In this study, distributions of environmental parameters and their correlations are modelled into a joint probabilistic description. By classifying conceivable sea states across the domain, an efficient uniform sampling scheme is presented as an efficient means of assessing long-term reliability against extreme events. The proposed method was performed on a floating production unit case study situated in the hurricane-prone Gulf of Mexico, exposed to irregular wave loads. The analysis was found to provide probability estimates with negligible bias when validated against subset simulation, with significant variance reduction of mean estimators by eliminating the need to over-simulate non-critical environmental conditions. The resulting sampling density has an added advantage of being non-failure specific, enabling system reliability assessments across multiple modes and locations of failure without the need for re-analysis.
The Average Shape of Large Waves in the Norwegian Sea: Is Non-Linear Physics Important?
Authors: Tang Tianning , Yelland Margaret J. , Adcock Thomas A. A.
Published: November 2019

Linear wave theory predicts that in a random sea, the shape of the average wave is given by the scaled autocorrelation function — the “NewWave”. However, the gravity wave problem is non-linear. Numerical simulations of waves on deep water have suggested that their average shape can become modified in a number of ways, including the largest wave in a group tending to move to the front of the group through non-linear dispersion. In this paper we examine whether this occurs for waves in the Norwegian Sea. Field data measured from the weather ship Polarfront is analysed for the period 2000 to 2009. We find that, at this location, the effect of non-linearity is small due to the moderate steepness of the sea-states.
Impact of the Swansea Bay Lagoon on Storm Surges in the Bristol Channel
Authors: Ma Qian , Moreira Tulio Marcondes , Adcock Thomas A. A.
Published: November 2019

The proposed Swansea Bay tidal energy lagoon is an example of a relatively small-scale tidal barrage demonstrator project. A key concern with this technology is that such structures may exacerbate other environmental problems. However, such structures might also create beneficial environmental effects in some areas, such as mitigating the impact of storm surges. In this paper we model the hydrodynamics of the Swansea lagoon and surrounding area using a depth-averaged numerical model. We simulate a number of storm surge events from the past 40 years and analyse how the presence of the Swansea Lagoon (under various operating strategies) modifies the resulting water levels.