Opening Autonomous Airspace–A Prologue, 2017 Oklahoma State University - Main Campus
Opening Autonomous Airspace–A Prologue, Samuel M. Vance
International Journal of Aviation, Aeronautics, and Aerospace
The proliferation of Unmanned Aerial Vehicles (UAV), and in particular small Unmanned Aerial Systems (sUAS), has significant operational implications for the Air Traffic Control (ATC) system of the future. Integrating unmanned aircraft safely presents long-standing challenges, especially during the lengthy transition period when unmanned vehicles will be mixed with piloted vehicles. Integration of dissimilar systems is not an easy, straight-forward task and in this case is complicated by the difficulty to truly know what is present in the airspace. Additionally, there are significant technology, security and liability issues that will need resolution to ensure property and life are protected and ...
Patient-Specific Bone Implants Using Subtractive Rapid Prototyping, 2017 Iowa State University
Patient-Specific Bone Implants Using Subtractive Rapid Prototyping, Matthew C. Frank, Ashish Mukund Joshi, Donald D. Anderson, Thaddeus P. Thomas, M. James Rudert, Yuki Tochigi, J. Lawrence Marsh, Thomas D. Brown
Matthew C. Frank
This research involves the development of rapid manufacturing for patient-specific bone implants using a Subtractive Rapid Prototyping process. The geometry of segmental defects in bone, resulting from traumatic injury or cancerous tumor resection, can be reverse-engineered from medical images (such as CT scans), and then accurate defect fillers can be automatically generated in advanced synthetic or otherwise bioactive/biocompatible materials. This paper presents a general process planning methodology that begins with CT imaging and results in the automatic generation of process plans for a subtractive RP system. This work uniquely enables the rapid manufacturing of implant fillers with several key ...
Creating Implants From Allograft Bone Using Subtractive Rapid Prototyping, 2017 Iowa State University
Creating Implants From Allograft Bone Using Subtractive Rapid Prototyping, Matthew C. Frank, Ashish Mukund Joshi, Shuangyan Lei, Donald D. Anderson, Yuki Tochigi, Thomas D. Brown
Matthew C. Frank
This research involves the development of rapid manufacturing for bone implants using human allograft bone in a Subtractive Rapid Prototyping process. Using CT-derived CAD models of missing bone due to high energy trauma or tumor resection, surgical reconstruction could be improved with custom rapid implants made from natural bone. The bone “stock” material is of arbitrary shape and material distribution in the form of frozen donated cadaveric bones. Each is unique in shape and has highly anisotropic material properties; likewise for each final bone implant geometry and its material distribution. This work utilizes a PLY input file, instead of the ...
Additive/Subtractive Rapid Pattern Manufacturing For Casting Patterns And Injection Mold Tooling, 2017 Iowa State University
Additive/Subtractive Rapid Pattern Manufacturing For Casting Patterns And Injection Mold Tooling, Matthew C. Frank, Frank Peters, Rajesh Kumar Karthikeyan
Matthew C. Frank
This paper presents a Rapid Pattern Manufacturing system that involves both additive and subtractive techniques whereby slabs are sequentially bonded and milled using layered toolpaths. Patterns are grown in a bottom-up fashion, both eliminating the need for multi-axis operations and allowing small features in deep cavities. Similar approaches exist in the literature; however, this system is able to provide a larger range of both materials and sizes, from smaller conventional injection mold tooling to very large wood or urethane sand casting patterns. This method introduces a novel sacrificial support structure approach by integrating a flask into the pattern build process ...
Evaluation Of The Display Of Cognitive State Feedback To Drive Adaptive Task Sharing, 2017 Iowa State University
Evaluation Of The Display Of Cognitive State Feedback To Drive Adaptive Task Sharing, Michael C. Dorneich, Břetislav Passinger, Christopher Hamblin, Claudia Keinrath, Jiři Vašek, Stephen D. Whitlow, Martijn Beekhuyzen
Industrial and Manufacturing Systems Engineering Publications
This paper presents an adaptive system intended to address workload imbalances between pilots in future flight decks. Team performance can be maximized when task demands are balanced within crew capabilities and resources. Good communication skills enable teams to adapt to changes in workload, and include the balancing of workload between team members This work addresses human factors priorities in the aviation domain with the goal to develop concepts that balance operator workload, support future operator roles and responsibilities, and support new task requirements, while allowing operators to focus on the most safety critical tasks. A traditional closed-loop adaptive system includes ...
Rapid Manufacturing In Biomedical Materials: Using Subtractive Rapid Prototyping For Bone Replacement, 2017 Iowa State University
Rapid Manufacturing In Biomedical Materials: Using Subtractive Rapid Prototyping For Bone Replacement, Matthew C. Frank, Christopher V. Hunt, Donald D. Anderson, Todd O. Mckinley, Thomas D. Brown
Matthew C. Frank
This paper presents methods for the rapid manufacturing of replacement bone fragments using a Subtractive Rapid Prototyping process called CNC-RP. The geometry of segmental defects in bone, resulting from traumatic injury or cancerous tumor resection, can be reverse-engineered working from medical images (such as CT scans), and then accurate defect fillers can be automatically generated in advanced synthetic biomaterials and other bioactive/biocompatible materials. The research provides evidence that suitable bone geometries can be created using subtractive RP from a variety of materials including Trabecular Metal® (porous tantalum), polymers, ceramics, and actual bone allografts. The research has implications in the ...
Advanced Process Planning For Subtractive Rapid Prototyping, 2017 Iowa State University
Advanced Process Planning For Subtractive Rapid Prototyping, Joseph Edward Petrzelka, Matthew C. Frank
Matthew C. Frank
This paper presents process planning methods for Subtractive Rapid Prototyping, which deals with multiple setup operations and the related issues of stock material management. Subtractive Rapid Prototyping (SRP) borrows from additive rapid prototyping technologies by using 2½D layer based toolpath processing; however, it is limited by tool accessibility. To counter the accessibility problem, SRP systems (such as desktop milling machines) employ a rotary fourth axis to provide more complete surface coverage. However, layer-based removal processing from different rotary positions can be inefficient due to double-coverage of certain volumes. This paper presents a method that employs STL models of the in-process ...
Economics Of Sacrificial Fixturing For Cnc Machining And Rapid Manufacturing, 2017 The Pennsylvania State University
Economics Of Sacrificial Fixturing For Cnc Machining And Rapid Manufacturing, Kevin Mcbrearty, Richard A. Wysk, Matthew C. Frank
Matthew C. Frank
This paper presents a fixturing method for sacrificial fixturing machining using CNC equipment. The focus of the paper is not on the method itself, but on the economics of sacrificial fixturing CNC machining, which defines the domain of use for the results described in the paper. The paper presents an economic model of machining, and then analyzes the use of the method as a function of: the number of parts to be produced, the ratio of material removed to final part volume, the number of features on the part, and the basic part geometry. We conclude that sacrificial fixturing is ...
Implementing Rapid Prototyping Using Cnc Machining (Cnc-Rp) Through A Cad/Cam Interface, 2017 Iowa State University
Implementing Rapid Prototyping Using Cnc Machining (Cnc-Rp) Through A Cad/Cam Interface, Matthew C. Frank
Matthew C. Frank
This paper presents the methodology and implementation of a rapid machining system using a CAD/CAM interface. Rapid Prototyping using CNC Machining (CNC-RP) is a method that has been developed which enables automatic generation of process plans for a machined component. The challenge with CNC-RP is not the technical problems of material removal, but with all of the required setup, fixture and toolpath planning, which has previously required a skilled machinist. Through the use of advanced geometric algorithms, we have implemented an interface with a CAD/CAM system that allows true automatic NC code generation directly from a CAD model ...
Automated Fixture Design For A Rapid Machining Process, 2017 Iowa State University
Automated Fixture Design For A Rapid Machining Process, Wutthigrai Boonsuk, Matthew C. Frank
Matthew C. Frank
Rapid prototyping techniques for CNC machining have been developed in an effort to produce functional prototypes in appropriate materials. One of the major challenges for rapid machining is to develop an automatic fixturing system for securing the part during the machining process. The method proposed in this paper is the use of sacrificial fixturing, similar to the support structures in existing rapid processes like Stereolithography. During the machining process, sacrificial supports emerge incrementally and, at the end of the process, are the only entities connecting the part to the stock material. This paper presents methodologies for the design of sacrificial ...
A Computational/Experimental Platform For Investigating Three- Dimensional Puzzle Solving Of Comminuted Articular Fractures, Thaddeus P. Thomas, Donald D. Anderson, Andrew Willis, Pengcheng Liu, Matthew C. Frank, J. Lawrence Marsh, Thomas D. Brown
Matthew C. Frank
Reconstructing highly comminuted articular fractures poses a difficult surgical challenge, akin to solving a complicated three-dimensional (3D) puzzle. Pre-operative planning using CT is critically important, given the desirability of less invasive surgical approaches. The goal of this work is to advance 3D puzzle solving methods toward use as a pre-operative tool for reconstructing these complex fractures. Methodology for generating typical fragmentation/dispersal patterns was developed. Five identical replicas of human distal tibia anatomy, were machined from blocks of high-density polyetherurethane foam (bone fragmentation surrogate), and were fractured using an instrumented drop tower. Pre- and post-fracture geometries were obtained using laser ...
A Method To Represent Heterogeneous Materials For Rapid Prototyping: The Matryoshka Approach, 2017 Iowa State University
A Method To Represent Heterogeneous Materials For Rapid Prototyping: The Matryoshka Approach, Shuangyan Lei, Matthew C. Frank, Donald D. Anderson, Thomas D. Brown
Matthew C. Frank
Purpose—The purpose of this paper is to present a new method for representing heterogeneous materials using nested STL shells, based, in particular, on the density distributions of human bones.
Design/methodology/approach—Nested STL shells, called Matryoshka models, are described, based on their namesake Russian nesting dolls. In this approach, polygonal models, such as STL shells, are “stacked” inside one another to represent different material regions. The Matryoshka model addresses the challenge of representing different densities and different types of bone when reverse engineering from medical images. The Matryoshka model is generated via an iterative process of thresholding the ...
An Improved Convergence Analysis Of Cyclic Block Coordinate Descent-Type Methods For Strongly Convex Minimization, 2017 University of Minnesota - Twin Cities
An Improved Convergence Analysis Of Cyclic Block Coordinate Descent-Type Methods For Strongly Convex Minimization, Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
The cyclic block coordinate descent-type (CBCD-type) methods have shown remarkable computational performance for solving strongly convex minimization problems. Typical applications include many popular statistical machine learning methods such as elastic-net regression, ridge penalized logistic regression, and sparse additive regression. Existing optimization literature has shown that the CBCD-type methods attain iteration complexity of O(p · log(1/e)), where e is a pre-specified accuracy of the objective value, and p is the number of blocks. However, such iteration complexity explicitly depends on p, and therefore is at least p times worse than those of gradient descent methods. To bridge this theoretical ...
Quantized Consensus Admm For Multi-Agent Distributed Optimization, 2017 Syracuse University
Quantized Consensus Admm For Multi-Agent Distributed Optimization, Shengyu Zhu, Mingyi Hong, Biao Chen
Abstract: This paper considers multi-agent distributed optimization with quantized communication which is needed when inter-agent communications are subject to finite capacity and other practical constraints. To minimize the global objective formed by a sum of local convex functions, we develop a quantized distributed algorithm based on the alternating direction method of multipliers (ADMM). Under certain convexity assumptions, it is shown that the proposed algorithm converges to a consensus within log1+η Ω iterations, where η > 0 depends on the network topology and the local objectives, and O is a polynomial fraction depending on the quantization resolution, the distance between initial ...
Convergence Analysis Of Alternating Direction Method Of Multipliers For A Family Of Nonconvex Problems, 2017 Iowa State University
Convergence Analysis Of Alternating Direction Method Of Multipliers For A Family Of Nonconvex Problems, Mingyi Hong, Zhi-Quan Luo, Mesiam Razaviyayn
The alternating direction method of multipliers (ADMM) is widely used to solve large-scale linearly constrained optimization problems, convex or nonconvex, in many engineering fields. However there is a general lack of theoretical understanding of the algorithm when the objective function is nonconvex. In this paper we analyze the convergence of the ADMM for solving certain nonconvex consensus and sharing problems. We show that the classical ADMM converges to the set of stationary solutions, provided that the penalty parameter in the augmented Lagrangian is chosen to be sufficiently large. For the sharing problems, we show that the ADMM is convergent regardless ...
Nestt: A Nonconvex Primal-Dual Splitting Method For Distributed And Stochastic Optimization, 2017 Iowa State University
Nestt: A Nonconvex Primal-Dual Splitting Method For Distributed And Stochastic Optimization, Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang
We study a stochastic and distributed algorithm for nonconvex problems whose objective consists a sum N/ nonconvex Li/N/ smooth functions, plus a nonsmooth regularizer. The proposed NonconvEx primal-dual SpliTTing (NESTT) algorithm splits the problem into N/ subproblems, and utilizes an augmented Lagrangian based primal-dual scheme to solve it in a distributed and stochastic manner. With a special non-uniform sampling, a version of NESTT achieves e-1 stationary solution using...gradient evaluations, which can be up to O(N)/ times better than the (proximal) gradient descent methods. It also achieves Q-linear convergence rate for nonconvex l1 penalized quadratic problems with polyhedral ...
Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, 2017 University of Alabama - Tuscaloosa
Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong
We consider the task of classification in the high dimensional setting where the number of features of the given data is significantly greater than the number of observations. To accomplish this task, we propose a heuristic, called sparse zero-variance discriminant analysis, for simultaneously performing linear discriminant analysis and feature selection on high dimensional data. This method combines classical zero-variance discriminant analysis, where discriminant vectors are identified in the null space of the sample within-class covariance matrix, with penalization applied to induce sparse structures in the resulting vectors. To approximately solve the resulting nonconvex problem, we develop a simple algorithm based ...
Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, 2017 Chinese Academy of Sciences
Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song
Consider the joint power and admission control (JPAC) problem for a multiuser single-input single-output (SISO) interference channel. Most existing works on JPAC assume the perfect instantaneous channel state information (CSI). In this paper, we consider the JPAC problem with the imperfect CSI, i.e., we assume that only the channel distribution information (CDI) is available. We formulate the JPAC problem into a chance (probabilistic)-constrained program, where each link's SINR outage probability is enforced to be less than or equal to a specified tolerance. To circumvent the computational difficulty of the chance SINR constraints, we propose to use the ...
Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, 2017 The Chinese University of Hong Kong
Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang
The alternating direction method of multipliers (ADMM) has been recognized as a versatile approach for solving modern large-scale machine learning and signal processing problems efficiently. When the data size and/or the problem dimension is large, a distributed version of ADMM can be used, which is capable of distributing the computation load and the data set to a network of computing nodes. Unfortunately, a direct synchronous implementation of such algorithm does not scale well with the problem size, as the algorithm speed is limited by the slowest computing nodes. To address this issue, in a companion paper, we have proposed ...
Joint Downlink Base Station Association And Power Control For Max-Min Fairness: Computation And Complexity, 2017 Southeast University
Joint Downlink Base Station Association And Power Control For Max-Min Fairness: Computation And Complexity, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu
The performance of full-duplex (FD) relay systems can be greatly impacted by the self-interference (SI) at relays. By exploiting multiple antennas, the spectral efficiency of FD relay systems can be enhanced through spatial SI mitigation. This paper studies joint source transmit beamforming and relay processing to achieve rate maximization for FD multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay systems with consideration of relay processing delay. The problem is difficult to solve mainly due to the SI constraint induced by the relay processing delay. In this paper, we first present a sufficient condition under which the relay amplification matrix has rank-one structure. Then ...