Dynamic pressure sensors for hypersonic flow measurements

This Ph.D. dissertation will focus on the research and development of an acoustic pressure sensor tailored for hypersonic boundary layer flow measurements. Hypersonic boundary layer flows comprise shocks, laminar-to-turbulent transitions, and high-frequency turbulence with small (sub 1-mm) characteristic length scales. Non-invasive acoustic pressure measurements at the walls of such flows offer useful diagnostics and are desired by the hypersonic community. The desired sensor specification are as follows: operation up to 1,000-K temperature, 0.5-MHz bandwidth, and sensing elements spanning less than 1 mm. The chosen embodiment is a piezoelectric sensor employing AlN as the sensing material. Preliminary prototypes have been micromachined at the UT MRC. These sensors are comprised of diaphragms with 500-µm diameter and 2-µm thickness. The sensors have been packaged into a cylindrical form factor with 0.25-inch diameter for mounting in hypersonic test-tunnel facilities. The dissertation will focus on the rigorous performance characterization of these sensors, the exploration of an array embodiment to enable pressure gradient measurements, and sensor design and characterization at elevated temperatures.Mechanical Engineerin

FEATURE SELECTION AND PARAMETER OPTIMIZATION FOR SUPPORT VECTOR MACHINES USING PARTICLE SWARM OPTIMIZATION AND HARMONY SEARCH

The present paper proposes a mechanism, Diverse Particle Swarm Optimization and Harmony Search (DPSO_HS), which finds feature subsets and parameter values for Support Vector Machines (SVM) when addressing classification problems by incorporating Particle Swarm Optimization (PSO) and Harmony Search (HS). Specifically, we introduced HS to enhance diversity in the PSO process since it has the advantage of providing diverse solutions as compared to other methodologies, as it considers all solutions in memory when improvising a new solution. For performance evaluation, various datasets with a wide range of features, instances, and classes were considered. DPSO_HS showed an increased diversity and classification accuracy as compared to PSO where statistical significance was found in most datasets. In addition, with two different hybridized approaches based on PSO, we observed that the proposed method showed higher accuracy for most datasets. We also reviewed the results of previous research with identical datasets and found that DPSO_HS achieved higher or equal accuracy rates for most datasets

GOLDEN SECTION SEARCH AND HYBRID TABU SEARCH-SIMULATED ANNEALING FOR LAYOUT DESIGN OF UNEQUAL-SIZED FACILITIES WITH FIXED INPUT AND OUTPUT POINTS

The facility layout problem involves the positioning of facilities in order to minimize the total travel distance. This study deals with a layout design of unequal-sized facilities with fixed input and output points. Since a mixed integer programming model cannot solve large-sized problems in a reasonable computational time, a heuristic algorithm composed of a placing method based on golden section search and a hybrid tabu search-simulated annealing is developed. In the placing method, facilities are sequentially arranged by a given sequence and the optimal coordinates of facilities are determined using the golden section search. To find the sequence that yields the minimum total travel distance, the hybrid tabu search-simulated annealing is developed. Computational experiments show that the proposed algorithm generates the optimal layout result for test problems with less than 6 facilities and improves the best known results from Xiao et al.(2013) in a shorter time

A HYBRID HEURISTIC ALGORITHM FOR INTEGRATED PROBLEM OF MACHINE SCHEDULING AND UNIDIRECTIONAL FLOW PATH DESIGN

During the past few decades, unidirectional flow path design (UFD) and machines scheduling (MS) problems have been studied separately. However, the separate considerations of UFD and MS cannot guarantee the global optimal solution for the whole production. The reason is that UFD and MS are closely interrelated in the real production situation. This paper is to propose a new integrated model, called iUFD/MS, with the objective of minimizing makespan. In iUFD/MS, UFD andMS problems are simultaneously considered. Due to the high complexity of iUFD/MS, a hybrid heuristic algorithm based on particle swarm optimization is developed to get an optimal or near-optimal solution within a reasonable time period. To validate our integrated model, a set of experiments is solved by applying the proposed solution method and the traditional method, respectively. The result shows that our integratd modelcan efficiently reducemakespan by 9.6% on average

Intelligent Design for Simulation Models of Weapon Systems Using a Mathematical Structure and Case-Based Reasoning

The armed forces of major nations have utilized modeling and simulation technologies to develop weapon systems corresponding to changing modern battlefields and reducing the development cycle. However, model design is complex owing to the characteristics of current weapons, which require multiple functions. Therefore, this study proposes a method to support the automated design of weapon system models for simulation. We apply module-based modeling and an intelligent modeling process to our devised method. The former formalizes constituents and constraints regarding an element combination to design the required model, while the latter applies case-based reasoning (CBR) to intelligentize the modeling process based on the results of the former. Using a case study, our proposed method demonstrates that models that respond to operational circumstances can be designed based on simulation results. Consequently, when weapon systems can be represented in formalized structures and constituents, the weapon models can be reusable based on the addition, modification, and replacement of modules in the common structure. The CBR process can provide the models that satisfy the requirements by retrieving similar models and modifying the models. The proposed method is applicable to the process of weapon system design or improvement for changing battlefields

A Process-Based Modeling Method for Describing Production Processes of Ship Block Assembly Planning

Ship block assembly planning is very complex due to the various activities and characteristics of ship production. Therefore, competitiveness in the shipbuilding industry depends on how well a company operates its ship block assembly plan. Many shipbuilders are implementing various studies to improve their competitiveness in ship block assembly planning, specifically regarding technology usage, such as modeling and simulation (M&S) and Cyber-Physical Systems (CPS). Although these technologies are successfully applied in some production planning systems, it is difficult to tailor ship production planning systems with flexibility due to unexpected situations. Providing a flexible plan for these production planning systems requires a way to describe and review the organic relationships of ship production processes. In this research, a process-based modeling (PBM) method proposes a novel approach to describing the production process of ship block assembly planning by redefining production information based on changing instructions. The proposed method consists of four modeling steps. The first creates a unit model, which includes the products, processes, and resource information for the block. The second designs an integrated network process for linking unit models according to the bill of materials (BOM). The third creates a process-based model that describes the production processes by combining unit models. The fourth generates a simulation model by applying a Petri-net to the process-based model, which analyzes the productivity of the ship’s block assembly processes. PBM identifies the assembly process’ interrelationship and shows that productivity can be reviewed to uncover ship production problems

REPRESENTATION AND PERFORMANCE ANALYSIS OF MANUFACTURING CELL BASED ON GENERALIZED STOCHASTIC PETRI NET

To achieve high flexibility and agility for rapidly changing customer's demand, Petri net has been adopted as a modeling and performance analysis tool. The Purpose of this paper is to propose modeling and performance analysis schemes of flexible manufacturing line using a generalized stochastic Petri net. The manufacturing line can be represented using workflows which are composed of bill of material and processes. Bill of process shows the precedence of processes and the relationship among the manufacturing and assembly operations. An algorithm generating a Petri net from bill of material database is proposed. The scheme of generalized stochastic Petri net utilizing both immediate and exponential distributed transitions are adopted to model a manufacturing cell with flexible machines, assembly lines and buffers. Performance analyses are performed based on qualitative and quantitative properties. For the qualitative analysis, behavioral and structural analyses are applied. Quantitative analyses are conducted using a Petri net simulator