Margie and Bill Klesse College of Engineering and Integrated Design Faculty Research

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12588/829

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Development And Implementation Of Challenge Based Instruction In Statics And Dynamics
(American Society for Engineering Education, 2010-06-20) Freeman, Robert; Vasquez, Horacio; Knecht, Martin; Martin, Taylor; Fuentes, Arturo; Walker, Joan; Martinez Ortiz, Araceli
This paper discusses challenge-based instructional (CBI) materials developed for courses in Statics and Dynamics. This effort is a component of a funded College Cost Reduction and Access Act (CCRAA) grant from the Department of Education, and focuses on student retention and development of adaptive expertise. Studies have shown that minority science, technology, engineering, and math (STEM) students leave STEM undergraduate fields in part due to lack of real world connections to their classroom learning experiences. Furthermore, in STEM fields the conventional approach is to teach for efficiency first and for innovation only in the latter years of the curriculum. This focus on efficiency first can actually stifle attempts at innovation in later courses. Our response to these issues is to change the way we teach. CBI, a form of inquiry based learning, can be simply thought of as teaching backwards. In this approach, a challenge is presented first, and the supporting theory (required to solve the challenge) second. Our implementation of CBI is built around the How People Learn (HPL) framework for effective learning environments and is realized and anchored by the STAR Legacy Cycle, as developed and fostered by the VaNTH NSF ERC for Bioengineering Educational Technologies. The developed materials are a result of collaboration between faculty members at the University of Texas-Pan American (UTPA) and South Texas College (STC), a two year Hispanic Serving Institution (HSI).
Fifth Grade Students’ Understanding of Ratio and Proportion in an Engineering Robotics Program
(American Society for Engineering Education, 2011-06-26) Martinez Ortiz, Araceli
The research described in this study explores the impact of utilizing a LEGO-robotics integrated engineering and mathematics program to support fifth grade students’ learning of ratios and proportion in an extracurricular program. One of the research questions guiding this research study was “how do students’ test results compare for students learning ratio and proportion concepts within the LEGO‐robotics integrated engineering and mathematics program versus when using a non-engineering textbook‐based mathematics program?” A mixed method repeated measures experiment with a control group was conducted. The subjects were 30 fifth grade students from a large urban school district who participated in one of two intervention programs, a LEGO‐robotics integrated engineering and mathematics program (experimental) versus a non-engineering textbook-based mathematics program (control). The understanding of ratio and proportion through numerical computation was measured using the Intra‐Mathematical Proportional Reasoning Test (Intra‐Prop). The understanding of ratio and proportion in general‐context mathematical word problems was measured using the Extra‐Mathematical Proportional Reasoning Test in a General Context (Extra-Prop) and the understanding of ratio and proportion in a LEGO engineering context was measured using a mathematical tool called Extra-Mathematical Proportional Reasoning Test in an Engineering Context (Engin-Prop). Students’ understanding of select basic engineering and mathematics definitions was measured using the Background and Definitions Test (Definitions Test). Data collected included classroom video, student interviews and written mathematical assessments of ratio and proportion problems in the four forms defined above, using repeated measures across three time periods-- prior to the beginning of the intervention programs, after the conclusion of the intervention program and ten weeks after the conclusion of the intervention program. The results of this study indicated that all students were able to make significant progress in learning new concepts of ratio and proportion as a result of participating in the intervention program learning experiences. Experimental students’ performance on the Intra-Prop was not significantly higher than that of the control students’ performance. However, experimental students’ performance on the Extra-Prop, Engin-Prop, and Definitions tests was significantly higher than that of the control students, indicating that students that learn about ratio and proportion in an engineering related context improve in their understanding significantly and retain their learning for a longer period of time when they encounter these situations in an extra-mathematical context versus in an intra-mathematical context. In addition, and of special note to practitioners, is the fact that students in the experimental group were able to learn at least as much and as well (if not more) the mathematics content of ratio and proportion as compared to the control group of students, and in addition, within the same amount of time, control group students learned and retained engineering and related ratio and proportion mathematics concepts.
Advances in Membrane Distillation for Water Desalination and Purification Applications
(2013-01-25) Camacho, Lucy Mar; Dumée, Ludovic; Zhang, Jianhua; Li, Jun-de; Duke, Mikel; Gomez, Juan; Gray, Stephen
Membrane distillation is a process that utilizes differences in vapor pressure to permeate water through a macro-porous membrane and reject other non-volatile constituents present in the influent water. This review considers the fundamental heat and mass transfer processes in membrane distillation, recent advances in membrane technology, module configurations, and the applications and economics of membrane distillation, and identifies areas that may lead to technological improvements in membrane distillation as well as the application characteristics required for commercial deployment.
Multicomplex Taylor Series Expansion for Computing High-Order Derivatives
(Academic Publications, 2014) Millwater, Harry; Shirinkam, Sara
Multicomplex Taylor series expansion (MCTSE) is a numerical method for calculating higher-order partial derivatives of a multivariable real-valued and complex-valued analytic function based on Taylor series expansion without subtraction cancelation errors. The implementation has been facilitated using Cauchy-Riemann matrix representation of multicomplex variables. In this paper, we show steps for finding these matrices and, in addition, that the number of appearances of the k^th derivatives follows the Pascal's triangle. Also, the situations where the MCTSE is not applicable is determined. Finally, we investigate the application of the method for complex-valued functions.
Sensitivity of Distributed Hydrologic Simulations to Ground and Satellite Based Rainfall Products
(2014-05-07) Chintalapudi, Singaiah; Sharif, Hatim O.; Xie, Hongjie
In this study, seven precipitation products (rain gauges, NEXRAD MPE, PERSIANN 0.25 degree, PERSIANN CCS-3hr, PERSIANN CCS-1hr, TRMM 3B42V7, and CMORPH) were used to force a physically-based distributed hydrologic model. The model was driven by these products to simulate the hydrologic response of a 1232 km2 watershed in the Guadalupe River basin, Texas. Storm events in 2007 were used to analyze the precipitation products. Comparison with rain gauge observations reveals that there were significant biases in the satellite rainfall products and large variations in the estimated amounts. The radar basin average precipitation compared very well with the rain gauge product while the gauge-adjusted TRMM 3B42V7 precipitation compared best with observed rainfall among all satellite precipitation products. The NEXRAD MPE simulated streamflows matched the observed ones the best yielding the highest Nash-Sutcliffe Efficiency correlation coefficient values for both the July and August 2007 events. Simulations driven by TRMM 3B42V7 matched the observed streamflow better than other satellite products for both events. The PERSIANN coarse resolution product yielded better runoff results than the higher resolution product. The study reveals that satellite rainfall products are viable alternatives when rain gauge or ground radar observations are sparse or non-existent.
Implementing PBL in a Concrete Construction Course
(American Society for Engineering Education, 2014-06-18) Hu, Jiong; Martinez Ortiz, Araceli; Sriraman, Vedaraman
This paper presents an action-research case study detailing the evolutionary changes in the implementation of the problem-based learning (PBL) method in an undergraduate concrete construction course. The case study incorporates the perspective of the course instructor as action-researcher and the quantitative and qualitative student impact data. PBL was first implemented in this course in 2011 as a student centered active learning pedagogy. The first implementation adopted a minimalist approach owing to the issues typically associated with PBL adoption such as increased instructor effort and student resistance to a new learning paradigm. Through 2012 and 2013, the action researcher continued to adopt and increase the scope of PBL application. In 2013, the course moved from a summer offering to a spring offering. This change proved to be very positive for both instructor and students alike. Most significantly, the change in schedule permitted a longer time span in which the PBL activities could be more effectively implemented compared to the short, fast paced summer offering. The evolution in the adaptation of PBL pedagogy and key components for success in the implementation of PBL in the engineering and engineering technology classroom will be presented. In addition, a discussion of the assessment methods that also underwent an evolution in scope and detail will be presented. The paper concludes with recommendations for further research.
A Comprehensive Model for Motivating and Preparing Under-represented Students, Educators and Parents in Science, Engineering, and Technology
(American Society for Engineering Education, 2014-06-18) Martinez Ortiz, Araceli
A comprehensive informal learning STEM outreach program for kindergarten through grade 4 (K-4) students is described along with the program’s theory of change and findings based on the participation of more than 200 urban minority students and their parents over a four-year period. This NSF-funded informal learning program was grounded in parental engagement theory of planned behavior and integrated both active-learning pedagogies and in-situ professional development for teachers. A unique age-appropriate science, engineering and technology integrated curriculum was delivered as a series of Saturday workshops set in a community science museum. Each year, cohorts of K‐3 African American and Hispanic students and their parents participated in eight 3-hour workshops comprised of student/parent sessions of hands-on science and engineering activities as well as separate parent awareness and development sessions in STEM education and technology skill development. The aim of this program has been to increase the participation of underrepresented groups in the science, technology, engineering, and mathematics (STEM) fields by attending to students early in the educational process. To accomplish this, the program has been guided by the following goals: to increase the knowledge, skills, and interest of K–3 students from underrepresented population groups in STEM fields; to increase parents’ knowledge and skills in science and engineering and their capacity to support their children in pursuing education and careers in these fields; and to increase the effectiveness of teachers in engaging students and parents in the Saturday science-related learning activities. Mixed methods research methodology has been used to measure the program’s contribution to the advancement of the program goals. Learning, motivational, and efficacy outcomes have been measured with pre and post student, teacher and parent survey instruments. This program has incorporated major findings of more than 10-years of research that suggests that improving children’s academic outcomes are much more effective when the family is actively engaged. This program has offered opportunities for parents to work along side their children; provided strategies promoting positive parental/child engagement; and provided ongoing training and professional development for project teachers. Young minority children have been exposed to African American, Latino, and women scientists and engineers through personal contact at special events, and via a featured program website section. Preliminary evaluation findings based on pre and post surveys, interviews, and observational data will be presented that indicate this program is helping parents and students persist in the program for multiple years and is motivating positive changes in student content understanding and career motivation.
Implications of Stably Stratified Atmospheric Boundary Layer Turbulence on the Near-Wake Structure of Wind Turbines
(2014-09-02) Bhaganagar, Kiran; Debnath, Mithu
Turbulence structure in the wake behind a full-scale horizontal-axis wind turbine under the influence of real-time atmospheric inflow conditions has been investigated using actuator-line-model based large-eddy-simulations. Precursor atmospheric boundary layer (ABL) simulations have been performed to obtain mean and turbulence states of the atmosphere under stable stratification subjected to two different cooling rates. Wind turbine simulations have revealed that, in addition to wind shear and ABL turbulence, height-varying wind angle and low-level jets are ABL metrics that influence the structure of the turbine wake. Increasing stability results in shallower boundary layers with stronger wind shear, steeper vertical wind angle gradients, lower turbulence, and suppressed vertical motions. A turbulent mixing layer forms downstream of the wind turbines, the strength and size of which decreases with increasing stability. Height dependent wind angle and turbulence are the ABL metrics influencing the lateral wake expansion. Further, ABL metrics strongly impact the evolution of tip and root vortices formed behind the rotor. Two factors play an important role in wake meandering: tip vortex merging due to the mutual inductance form of instability and the corresponding instability of the turbulent mixing layer.
A Review of Methodological Approaches for the Design and Optimization of Wind Farms
(2014-10-29) Herbert-Acero, José F.; Probst, Oliver; Réthoré, Pierre-Elouan; Larsen, Gunner Chr.; Castillo-Villar, Krystel K.
This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research.
Metaheuristic Algorithms Applied to Bioenergy Supply Chain Problems: Theory, Review, Challenges, and Future
(2014-11-19) Castillo-Villar, Krystel K.
Bioenergy is a new source of energy that accounts for a substantial portion of the renewable energy production in many countries. The production of bioenergy is expected to increase due to its unique advantages, such as no harmful emissions and abundance. Supply-related problems are the main obstacles precluding the increase of use of biomass (which is bulky and has low energy density) to produce bioenergy. To overcome this challenge, large-scale optimization models are needed to be solved to enable decision makers to plan, design, and manage bioenergy supply chains. Therefore, the use of effective optimization approaches is of great importance. The traditional mathematical methods (such as linear, integer, and mixed-integer programming) frequently fail to find optimal solutions for non-convex and/or large-scale models whereas metaheuristics are efficient approaches for finding near-optimal solutions that use less computational resources. This paper presents a comprehensive review by studying and analyzing the application of metaheuristics to solve bioenergy supply chain models as well as the exclusive challenges of the mathematical problems applied in the bioenergy supply chain field. The reviewed metaheuristics include: (1) population approaches, such as ant colony optimization (ACO), the genetic algorithm (GA), particle swarm optimization (PSO), and bee colony algorithm (BCA); and (2) trajectory approaches, such as the tabu search (TS) and simulated annealing (SA). Based on the outcomes of this literature review, the integrated design and planning of bioenergy supply chains problem has been solved primarily by implementing the GA. The production process optimization was addressed primarily by using both the GA and PSO. The supply chain network design problem was treated by utilizing the GA and ACO. The truck and task scheduling problem was solved using the SA and the TS, where the trajectory-based methods proved to outperform the population-based methods.
Hydrologic Simulations Driven by Satellite Rainfall to Study the Hydroelectric Development Impacts on River Flow
(2014-11-27) Le, Tuan B.; Al-Juaidi, Farhan H.; Sharif, Hatim O.
This study assesses the impact of hydroelectric dams on the discharge and total suspended solids (TSS) concentration in the Huong River basin in Vietnam. The analysis is based on hydrologic and sediment transport simulations by the Soil and Water Assessment Tool (SWAT) model driven by the Tropical Rainfall Measuring Mission (TRMM) 3B42V6 rainfall data, from January 2003 through December 2010. An upstream sub-basin not affected by the hydroelectric dams was used for model calibration. The calibration results indicate good agreement between simulated and observed daily data (0.67 Nash-Sutcliffe efficiency, 0.82 Pearson correlation coefficient). The calibrated model for discharge and TSS simulation is then applied on another major sub-basin and then the whole Huong River basin. The simulation results indicate that dam operation in 2010 decreased downstream discharge during the rainy season by about 35% and augmented it during the dry season by about 226%. The downstream TSS concentration has decreased due to the dam operation but the total sediment loading increased during the dry season and decreased during the rainy season. On average, the dam construction and operation affected the pattern of discharge more than that of the sediment loading. Results indicate that SWAT, driven by remotely sensed inputs, can reasonably simulate discharge and water quality in ungauged or poorly gauged river basins and can be very useful for water resources assessment and climate change impact studies in such basins.
Analysis of a Multilevel Dual Active Bridge (ML-DAB) DC-DC Converter Using Symmetric Modulation
(2015-04-20) Moonem, M. A.; Pechacek, C. L.; Hernandez, R.; Krishnaswami, Hariharan
Dual active bridge (DAB) converters have been popular in high voltage, low and medium power DC-DC applications, as well as an intermediate high frequency link in solid state transformers. In this paper, a multilevel DAB (ML-DAB) has been proposed in which two active bridges produce two-level (2L)-5L, 5L-2L and 3L-5L voltage waveforms across the high frequency transformer. The proposed ML-DAB has the advantage of being used in high step-up/down converters, which deal with higher voltages, as compared to conventional two-level DABs. A three-level neutral point diode clamped (NPC) topology has been used in the high voltage bridge, which enables the semiconductor switches to be operated within a higher voltage range without the need for cascaded bridges or multiple two-level DAB converters. A symmetric modulation scheme, based on the least number of angular parameters rather than the duty-ratio, has been proposed for a different combination of bridge voltages. This ML-DAB is also suitable for maximum power point tracking (MPPT) control in photovoltaic applications. Steady-state analysis of the converter with symmetric phase-shift modulation is presented and verified using simulation and hardware experiments.
Minimizing the Discrepancy between Simulated and Historical Failures in Turbine Engines: A Simulation-Based Optimization Method
(Hindawi, 2015-05-18) Kibria, Ahmed; Castillo-Villar, Krystel K.; Millwater, Harry
The reliability modeling of a module in a turbine engine requires knowledge of its failure rate, which can be estimated by identifying statistical distributions describing the percentage of failure per component within the turbine module. The correct definition of the failure statistical behavior per component is highly dependent on the engineer skills and may present significant discrepancies with respect to the historical data. There is no formal methodology to approach this problem and a large number of labor hours are spent trying to reduce the discrepancy by manually adjusting the distribution’s parameters. This paper addresses this problem and provides a simulation-based optimization method for the minimization of the discrepancy between the simulated and the historical percentage of failures for turbine engine components. The proposed methodology optimizes the parameter values of the component’s failure statistical distributions within the component’s likelihood confidence bounds. A complete testing of the proposed method is performed on a turbine engine case study. The method can be considered as a decision-making tool for maintenance, repair, and overhaul companies and will potentially reduce the cost of labor associated to finding the appropriate value of the distribution parameters for each component/failure mode in the model and increase the accuracy in the prediction of the mean time to failures (MTTF).
Exploring Faculty Insights Into Why Undergraduate College Students Leave STEM Fields of Study - A Three-Part Organizational Self-Study
(The Clute Institute, 2015-06-01) Martinez Ortiz, Araceli; Sriraman, Vedaraman
An institutional self-study at a Hispanic Serving Institution (HSI) explored factors thought to impact students’ decisions to persist in science, technology, engineering and mathematics (STEM) fields of study. This self-study is presented as a model first step for Institutions of Higher Education interested in launching efforts to improve STEM education and STEM student success and persistence. A methodology combining qualitative and quantitative analysis approaches was used to examine different aspects of the overarching research question, “Why do undergraduate students leave college STEM fields of study?” A quantitative review of institutional data was used to identify four particular gaps in student persistence and success in STEM fields of study at Texas State University. An online survey and a focus group guide were developed based on existing but more broadly focused instruments and used to collect faculty insights regarding faculty and student experiences and possible reasons for student attrition in STEM. A review of retention theories was undertaken to better inform the process of generating remedies to the STEM persistence issue. Data were collected and analyzed separately for each component to produce two sets of findings. Findings indicated that there were retention issues in regard to STEM majors in general and underrepresented student groups in particular. Underrepresented students do not pursue STEM degrees percentage wise in comparison to other degrees. The self-study and retention theories suggest the following remedial measures: supporting faculty to transform their teaching, providing supplemental instruction in math and science and including discipline specific introductory courses and early internship experiences.
The Roots of Science, Mathematics and Engineering Self-confidence in College Students: Voices of Successful Undergraduate Women
(American Society for Engineering Education, 2015-06-14) Torres, Anthony; Talley, Kimberly Grau; Martinez Ortiz, Araceli
With the percentage of women in STEM majors at _____ University, a large Hispanic Serving Institution, significantly lower than the percentage of women attending the university in general, the authors sought to understand this gap by studying the perspectives of undergraduate women who have successfully persisted in a STEM field of study at the same university. Specifically, the goal of this study was to gain a deeper understanding of what experiences women credited for influencing their self-efficacy, the development of their career interest goals and their academic course outcomes as related to studying science, technology, engineering and mathematics (STEM). This study was also designed to identify experiences that appear to contribute to women’s identity development and self-confidence. Data was collected and analyzed to identify if similar patterns exist between subjects and if so, which are the greater influencers in their decision to select a STEM major and to persist beyond the critical first two years of undergraduate studies. The literature of socialization and identity development as related to women as STEM learners in diverse communities is reviewed. This study begins to create an understanding of how women think about their multiple social identities (field of study, gender, culture, etc.). Focus group strategies for obtaining in-depth feedback regarding young women’s attitudes, perceptions, motivations, and behaviors is discussed. Observations and recommendations regarding the 2015 ASEE Annual Conference & Exposition / Women in Engineering Division research methodologies for study design and data analysis are presented with particular attention to the rationale for cultural responsive practices in qualitative research. A mixed methods research approach including the use of surveys and focus groups was used to collect student perceptions from junior and senior status students in STEM fields of study. Preliminary results indicate that students identify early personal experiences as building their self-confidence and contributing to their identity development. Drawing on self-perception theory, women appear to develop a more robust sense of persistence and feel that they fit into STEM- even when faced with sexism from other students.
Engaging Students in Sustainability Education and Awareness of Green Engineering Design and Careers through a Pre-Engineering Program
(American Society for Engineering Education, 2015-06-17) Martinez Ortiz, Araceli; Asiabanpour, Bahram; Aslan, Semih; Jimenez, Jesus Alejandro; Kim, Yoo-Jae; Salamy, Hassan
A framework for an active learning summer program for middle school students is presented along with survey instruments and pre and post program data regarding student attitudes and awareness of sustainable design issues and career motivation in the field. This summer program was designed to attract students, especially from underrepresented groups, into early motivating experiences in the engineering fields and to increase their awareness of concepts and careers in renewable energy, and green engineering design principles and technologies. Twenty-four students from a low social economic school district were provided the opportunity to experience many state of the art engineering technologies at the university’s school of engineering and to learn from a diverse group of knowledgeable mentoring faculty. In the week-long program, students were involved in hands-on engineering and renewable energy activities appropriate to their age and knowledge. Topics covered included: the engineering design process, CAD solid modeling, 3D Printing and water jet cutting, hands-on assembly, renewable energy resources for homes, sustainable site selection, and water efficiency principles. Using project-based learning, student teams participated as designers of their own green home models by integrating their learning of renewable energy use, conservation practices, and appropriate design and material selection. Pre and post surveys revealed increases in student awareness of general engineering and renewable energy concepts as well as increased interest in pursuing engineering careers.
Modeling the Projected Changes of River Flow in Central Vietnam under Different Climate Change Scenarios
(2015-07-07) Le, Tuan B.; Sharif, Hatim O.
Recent studies by the United Nations Environment Programme (UNEP) and the Intergovernmental Panel on Climate Change (IPCC) indicate that Vietnam is one of the countries most affected by climate change. The variability of climate in this region, characterized by large fluctuations in precipitation and temperature, has caused significant changes in surface water resources. This study aims to project the impact of climate change on the seasonal availability of surface water of the Huong River in Central Vietnam in the twenty-first century through hydrologic simulations driven by climate model projections. To calibrate and validate the hydrologic model, the model was forced by the rain gage-based gridded Asian Precipitation–Highly Resolved Observational Data Integration Towards Evaluation of water resources (APHRODITE) V1003R1 Monsoon Asia precipitation data along with observed temperature, humidity, wind speed, and solar radiation data from local weather stations. The simulated discharge was compared to observations for the period from 1951 until present. Three Global Climate Models (GCMs) ECHAM5-OM, HadCM3 and GFDL-CM2.1 integrated into Long Ashton Research Station-Weather Generator (LARS-WG) stochastic weather generator were run for three IPCC–Special Report on Emissions Scenarios (IPCC-SRES) emissions scenarios A1B, A2, and B1 to simulate future climate conditions. The hydrologic model simulated the Huong River discharge for each IPCC-SRES scenario. Simulation results under the three GCMs generally indicate an increase in summer and fall river discharge during the twenty-first century in A2 and B1 scenarios. For A1B scenario, HadCM3 and GFDL-CM2.1 models project a decrease in river discharge from present to the 2051–2080 period and then increase until the 2071–2100 period while ECHAM5-OM model produces opposite projection that discharge will increase until the 2051–2080 period and then decrease for the rest of the century. Water management impacts, such as irrigation or dam regulation, were not considered in this study. However, the results provide local policy makers with quantitative data to consider possible adjustment of future dam capacities for development of flood control policies.
A New Compton Camera Imaging Model to Mitigate the Finite Spatial Resolution of Detectors and New Camera Designs for Implementation
(2015-10-27) Smith, Bruce
An intrinsic limitation of the accuracy that can be achieved with Compton cameras results from the inevitable fact that the detectors, which comprise the camera, cannot have infinitely-accurate spatial resolution. To mitigate this loss of accuracy, a new imaging model is proposed. The implementation of the new imaging model, however, requires new camera designs. The results of a computer simulation indicate that the new imaging model can produce reasonable images, at least when noiseless simulated data are used. In the future, more work is needed to determine if the use of the new imaging model will improve the imaging capabilities of Compton cameras despite the loss of sensitivity caused by the use of the new camera designs. Regardless of the outcome of this work, the results presented here illustrate that new models for imaging from Compton scatters are possible and motivate the development of further models that could be more advantageous than the ones already developed.
A Hierarchical Approach Using Machine Learning Methods in Solar Photovoltaic Energy Production Forecasting
(2016-01-19) Li, Zhaoxuan; Rahman, SM Mahbobur; Vega, Rolando; Dong, Bing
We evaluate and compare two common methods, artificial neural networks (ANN) and support vector regression (SVR), for predicting energy productions from a solar photovoltaic (PV) system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power measurements collected from 2014. The accuracy of the model is determined using computing error statistics such as mean bias error (MBE), mean absolute error (MAE), root mean square error (RMSE), relative MBE (rMBE), mean percentage error (MPE) and relative RMSE (rRMSE). This work provides findings on how forecasts from individual inverters will improve the total solar power generation forecast of the PV system.
Quantifying the Impact of Feedstock Quality on the Design of Bioenergy Supply Chain Networks
(2016-03-16) Castillo-Villar, Krystel K.; Minor-Popocatl, Hertwin; Webb, Erin
Logging residues, which refer to the unused portions of trees cut during logging, are important sources of biomass for the emerging biofuel industry and are critical feedstocks for the first-type biofuel facilities (e.g., corn-ethanol facilities). Logging residues are under-utilized sources of biomass for energetic purposes. To support the scaling-up of the bioenergy industry, it is essential to design cost-effective biofuel supply chains that not only minimize costs, but also consider the biomass quality characteristics. The biomass quality is heavily dependent upon the moisture and the ash contents. Ignoring the biomass quality characteristics and its intrinsic costs may yield substantial economic losses that will only be discovered after operations at a biorefinery have begun. This paper proposes a novel bioenergy supply chain network design model that minimizes operational costs and includes the biomass quality-related costs. The proposed model is unique in the sense that it supports decisions where quality is not unrealistically assumed to be perfect. The effectiveness of the proposed methodology is proven by assessing a case study in the state of Tennessee, USA. The results demonstrate that the ash and moisture contents of logging residues affect the performance of the supply chain (in monetary terms). Higher-than-target moisture and ash contents incur in additional quality-related costs. The quality-related costs in the optimal solution (with final ash content of 1% and final moisture of 50%) account for 27% of overall supply chain cost. Based on the numeral experimentation, the total supply chain cost increased 7%, on average, for each additional percent in the final ash content.

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