Computational Engineering Commons^™

Early-Age Strength And Failure Characteristics Of 3d Printable Polymer Concrete: Numerical Modelling And Experimental Testing, Mohammad Amin Dehghani Najvani

Civil Engineering ETDs

The time-dependent rheological and early-age strength parameters of Polymer concrete (PC) were investigated. PC flow decreased, and the static yield stress and thixotropy increased as the specimen aged, while the dynamic yield stress remained unchanged. The study found that the Herschel-Bulkley model can accurately describe the PC’s rheological behavior over time. The change in cohesion strength and internal friction angle over time was observed using uniaxial unconfined compression and direct shear tests of fresh PC. A time-dependent MohrCoulomb failure criterion was established. Temperature analysis was used to determine the gel time and explain the evolution of the time-dependent early-age strength …

Vi Energy-Efficient Memristor-Based Neuromorphic Computing Circuits And Systems For Radiation Detection Applications, Jorge Iván Canales Verdial

Electrical and Computer Engineering ETDs

Radionuclide spectroscopic sensor data is analyzed with minimal power consumption through the use of neuromorphic computing architectures. Memristor crossbars are harnessed as the computational substrate in this non-conventional computing platform and integrated with CMOS-based neurons to mimic the computational dynamics observed in the mammalian brain’s visual cortex. Functional prototypes using spiking sparse locally competitive approximations are presented. The architectures are evaluated for classification accuracy and energy efficiency. The proposed systems achieve a 90% true positive accuracy with a high-resolution detector and 86% with a low-resolution detector.

Speaker Diarization And Identification From Single-Channel Classroom Audio Recording Using Virtual Microphones, Antonio Gomez

Electrical and Computer Engineering ETDs

Speaker identification in noisy audio recordings, specifically those from collaborative learning environments, can be extremely challenging. There is a need to identify individual students talking in small groups from other students talking at the same time. To solve the problem, we assume the use of a single microphone per student group without any access to previous large datasets for training.

This dissertation proposes a method of speaker identification using cross-correlation patterns associated to an array of virtual microphones, centered around the physical microphone. The virtual microphones are simulated by using approximate speaker geometry observed from a video recording. The patterns …

Method Of Embedded Imperfections For The Direct Simulation Of Deformation Instabilities In Film-Substrate Structures, Siavash Nikravesh Kazeroni

Mechanical Engineering ETDs

In this dissertation, a novel finite-element methodology called “embedded imperfections” is proposed and employed for computationally simulating various types of deformation instabilities observed in film-substrate structures subjected to mechanical loading. The approach involves the incorporation of elements having distinctive material properties within the film-substrate interface. One can interpret this practice as a deliberate distribution of material defects within the numerical model. It has been shown that embedded imperfections not only can trigger the onset of instability, but also can lead to “direct” simulation of deformation instability problems in that primary and subsequent instability modes can all be captured in a …

Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano

Electrical and Computer Engineering ETDs

Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …

New Development Of Neutrosophic Probability, Neutrosophic Statistics, Neutrosophic Algebraic Structures, And Neutrosophic Plithogenic Optimizations, Florentin Smarandache, Yanhui Guo

Branch Mathematics and Statistics Faculty and Staff Publications

This collective book presents state-of-the-art papers on new topics related to neutrosophic theories, such as neutrosophic algebraic structures, neutrosophic triplet algebraic structures, neutrosophic extended triplet algebraic structures, neutrosophic algebraic hyperstructures, neutrosophic triplet algebraic hyperstructures, neutrosophic n-ary algebraic structures, neutrosophic n-ary algebraic hyperstructures, refined neutrosophic algebraic structures, refined neutrosophic algebraic hyperstructures, quadruple neutrosophic algebraic structures, refined quadruple neutrosophic algebraic structures, neutrosophic image processing, neutrosophic image classification, neutrosophic computer vision, neutrosophic machine learning, neutrosophic artificial intelligence, neutrosophic data analytics, neutrosophic deep learning, and neutrosophic symmetry, as well as their applications in the real world.

Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann

Mathematics & Statistics ETDs

This thesis uses a geometric approach to derive and solve nonlinear least squares minimization problems to geolocate a signal source in three dimensions using time differences of arrival at multiple sensor locations. There is no restriction on the maximum number of sensors used. Residual errors reach the numerical limits of machine precision. Symmetric sensor orientations are found that prevent closed form solutions of source locations lying within the null space. Maximum uncertainties in relative sensor positions and time difference of arrivals, required to locate a source within a maximum specified error, are found from these results. Examples illustrate potential requirements …

Recipe For Disaster, Zac Travis

MFA Thesis Exhibit Catalogs

Today’s rapid advances in algorithmic processes are creating and generating predictions through common applications, including speech recognition, natural language (text) generation, search engine prediction, social media personalization, and product recommendations. These algorithmic processes rapidly sort through streams of computational calculations and personal digital footprints to predict, make decisions, translate, and attempt to mimic human cognitive function as closely as possible. This is known as machine learning.

The project Recipe for Disaster was developed by exploring automation in technology, specifically through the use of machine learning and recurrent neural networks. These algorithmic models feed on large amounts of data as a …

Elevated Temperature Progressive Damage And Failure Of Duplex Stainless Steel, Darren P. Luke

Civil Engineering ETDs

Ductile failure of metals has been the focus of research efforts within academia and industry for many years since it is tremendously important for understanding the failure of structures under extreme loading conditions. However, limited research has been dedicated to elevated temperature ductile failure, which is critical for evaluating catastrophic events such as industrial, structural or shipping vessel fires. A detailed investigation was conducted on the structural response of Duplex Stainless Steel at elevated temperatures. The temperature dependence of elastic modulus, yield strength, ultimate strength, and ductility was measured up to 1000°C and a continuum damage plasticity model was developed. …

Data-Driven Uncertainty Quantification Interpretation With High Density Regions, Matthew Gregor Peterson

Computer Science ETDs

In a time when data is being constantly generated by phones, vehicles, sensor net- works, social media, etc. detecting anomalies with in the data can be very crucial. In cases where we know little prior knowledge about the data, it becomes difficult to extract uncertainty about our results. In this thesis, we will propose a framework in which we can extract uncertainty distributions from data-driven modeling prob- lems. We will show some concrete examples of how to apply framework and provide some insight into what the uncertainty distributions are telling us using High Density Regions (HDRs).

Early Alert Of At-Risk Students: An Ontology-Driven Framework, Elias S. Lopez

Electrical and Computer Engineering ETDs

As higher education continues to adapt to the constantly shifting conditions that society places on institutions, the enigma of student attrition continues to trouble universities. Early alerts for students who are at-risk academically have been introduced as a method for solving student attrition at these institutions. Early alert systems are designed to provide students who are academically at-risk a prompt indication so that they may correct their performance and make progress towards successful semester completion. Many early alert systems have been introduced and implemented at various institutions with varying levels of success. Currently, early alert systems employ different techniques for …

Experimental Investigation Of And Constitutive Model For The Thermo-Poro-Mechanical Deformation Of Granular Salt Under Hydrostatic Compression, Brandon C. Lampe

Civil Engineering ETDs

The influence of pore pressure and porosity on the ductile deformation of granular salt was experimentally investigated under hydrostatic compression. Confining and pore pressures were independently controlled while granular salt samples exhibited rate-dependent deformation that resulted in large decreases of sample volume and porosity. The sample deformation rates were observed to correspond with both the sample porosity and the pressure difference between the confining and pore pressures. Post-test observations revealed that the reduced porosity was caused by the solid particles deforming in a ductile manner. Insight into the cause of ductile deformation was gained by considering the local stress distribution …

Neutrosophic Computing With Sympy (Computación Neutrosófica Mediante Sympy ), Maykel Leyva-Vazquez, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this article the concept of neutrosophic number is presented. Jupyter through Google Colaboratory is introduced for calculations. The Sympy library is used to perform the process of neutrosophic computation. Systems of linear neutrosóficas equations are solved by means of the symbolic computation in python. A case study was developed for the determination of vehicular traffic with indeterminacy. As future works are the development of new applications in different areas of engineering and science.

State-Based Peridynamic Particle Method, Siavash Nikravesh Kazeroni

Civil Engineering ETDs

In this study, a novel discrete Peridynamics framework called the “State-Based Peridynamic Particle Model (SPPM)” is introduced. In this approach, a solid body is simulated by neither solving differential equations nor integral equations; instead, the simulation is accomplished by directly solving discrete systems of equations using finite summations. SPPM is formulated for a random distribution of particles, hence, it can be considered as a meshfree method. The assumptions of continuity and homogeneity are not necessary for this approach. The SPPM is a generalization of the “State-Based Peridynamic Lattice Model (SPLM)”. In the SPLM formulation, for sake of simplicity and computational …

Ns-K-Nn: Neutrosophic Set-Based K-Nearest Neighbors Classifier, Florentin Smarandache, Yaman Akbulut, Abdulkadir Sengur, Yanhui Guo

Branch Mathematics and Statistics Faculty and Staff Publications

k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametric supervised classifier. It aims to determine the class label of an unknown sample by its k-nearest neighbors that are stored in a training set. The k-nearest neighbors are determined based on some distance functions. Although k-NN produces successful results, there have been some extensions for improving its precision. The neutrosophic set (NS) defines three memberships namely T, I and F. T, I, and F shows the truth membership degree, the false membership degree, and the indeterminacy membership degree, respectively. In this paper, the NS …

Evaluation And Enhancement Of Clean Energy Systems: Analytical, Computational And Experimental Study Of Solar And Nuclear Cycles, Nima Fathi

Mechanical Engineering ETDs

Clean (and specifically renewable) energy is steadily improving its global share. However, finite availability of fossil fuels and the growing effects of climate change make it an urgent priority to convince the industry and governments to incentivize investment in the renewable energy field and to make it more attractive by decreasing the capital cost. Until recently, uncertainties in funding limited renewable energy development, especially in the US. That limitation has been one of the barriers to progress. Another limitation of many renewable energy systems is the variability in their output, which makes them unsuitable for baseline power production. Therefore, fossil …

Ion Size Effects On The Properties Of Charge Regulating Electric Double Layers, Divya Jyoti Prakash

Nanoscience and Microsystems ETDs

The behavior of charged interfaces formed in various systems like colloidal solution, fuel cells, battery, electro-deposition, catalysis is governed by the properties of electrical double layer(EDL). Civilized model with charge regulation boundary condition determined by thermodynamic equilibrium at the interface has been used to model electrical double layer and shows that size of the solvent plays a critical role in characterizing the properties of EDL using classical density functional theory.This thesis investigates the impact of ion size in electrolyte solutions on the electrical double layer formed at the interface using a similar model. It is found that ion size greatly …

Detection Of Pheromone Laying Event In Foraging Data Of Harvester Ants Using Change Point Analysis Method, Safeeul Bashir Safee

Computer Science ETDs

Communication is an important factor in the foraging performance of social insects, such as ants. During foraging, ants keep track of food sources by using memory (site fidelity) or by communicating through pheromones. Previous field experiments showed that the rate of seed collection depends on the distribution of food in the environment. If food is spatially clustered, then it is beneficial for ants recruit nest mates to collect seeds from large clusters. However, we do not know when the recruitment occurs in natural ant population. To explore this question, we used a power law distribution to arrange seeds in piles …

Generalized Interval Valued Neutrosophic Graphs Of First Type, Florentin Smarandache, Said Broumi, Mohamed Talea, Assia Bakali, Ali Hassan

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper, motivated by the notion of generalized single valued neutrosophic graphs of first type, we defined a new neutrosophic graphs named generalized interval valued neutrosophic graphs of first type (GIVNG1) and presented a matrix representation for it and studied few properties of this new concept. The concept of GIVNG1 is an extension of generalized fuzzy graphs (GFG1) and generalized single valued neutrosophic of first type (GSVNG1).

An Operational View In Computational Construction Of Information, Florentin Smarandache, Stefan Vladutescu, Constantin Dima, Valeriu Voinea

Branch Mathematics and Statistics Faculty and Staff Publications

The paper aims to explain the technology of emergence of information. Our research proves that information as communicational product is the result of processing within some operations, actions, mechanisms and strategies of informational material meanings. Are determined eight computational-communicative operations of building information. Information occurs in two communication phases, syncretic and the segregation-synthetic. The syncretic phase consists of four operations: referral of significant field, primary delimitation of information, detection-looking information and an anticipative-draft constitution (feedforward). The segregation-synthetic phase also includes four operations: discrimination, identification, interpretation and confrontation (feedback). In the future we will investigate informational actions, mechanisms and strategies.

Automatic Segmentation Of Coronal Holes In Solar Images And Solar Prediction Map Classification, Venkatesh Jatla

Electrical and Computer Engineering ETDs

Solar image analysis relies on the detection of coronal holes for predicting disruptions to earth’s magnetic field. The coronal holes act as sources of solar wind that can reach the earth. Thus, coronal holes are used in physical models for predicting the evolution of solar wind and its potential for interfering with the earth’s magnetic field. Due to inherent uncertainties in the physical models, there is a need for a classification system that can be used to select the physical models that best match the observed coronal holes. The physical model classification problem is decomposed into three subproblems. First, the …

Importance Of Sources Using The Repeated Fusion Method And The Proportional Conflict Redistribution Rules #5 And #6, Florentin Smarandache, Jean Dezert

Branch Mathematics and Statistics Faculty and Staff Publications

We present in this paper some examples of how to compute by hand the PCR5 fusion rule for three sources, so the reader will better understand its mechanism. We also take into consideration the importance of sources, which is different from the classical discounting of sources.

Examples Where The Conjunctive And Dempster’S Rules Are Insensitive, Florentin Smarandache, Jean Dezert, Valeri Kroumov

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we present several counter-examples to the Conjunctive rule and to Dempster rule of combinations in information fusion.

Extended Pcr Rules For Dynamic Frames, Florentin Smarandache, Jean Dezert

Branch Mathematics and Statistics Faculty and Staff Publications

In most of classical fusion problems modeled from belief functions, the frame of discernment is considered as static. This means that the set of elements in the frame and the underlying integrity constraints of the frame are fixed forever and they do not change with time. In some applications, like in target tracking for example, the use of such invariant frame is not very appropriate because it can truly change with time. So it is necessary to adapt the Proportional Conflict Redistribution fusion rules (PCR5 and PCR6) for working with dynamical frames. In this paper, we propose an extension of …