Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

Developing an Enhanced Model for Combined Heat and Air Infiltration Energy Simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building’s energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.

The impacts of trade policy reforms on the Sri Lankan economy

This dissertation presents an analysis of the impacts of trade policy reforms in Sri Lanka. A Computable General Equilibrium (CGE) model is constructed with detailed description of the domestic production structure and foreign trade. The model is then used to investigate the effects of trade policy reforms on resource allocation and welfare.^ Prior to 1977, Sri Lanka maintained stringent control over its imports through rigid quantitative restrictions. A new economic policy reform package was introduced in 1977, and it shifted Sri Lanka's development strategy toward an export oriented policy regime. The shift of policy focus from a restrictive trade regime toward a more open trade regime is expected to have a significant impact on the volume of external trade, domestic production structure, allocation of resources, and social welfare.^ Simulations are carried out to assess the effects of three major policy reforms: (1) a devaluation of the Sri Lanka rupee, (2) a partial or a complete elimination of export duties, and (3) a devaluation-cum-removal of export duties.^ Simulation results indicate that the macroeconomic impact of a devaluation-cum-removal of export duties can be substantial. They also suggest that the resource-pull effects of a devaluation and a devaluation-cum-export duty removal policy are significant. However, the model shows that a devaluation combined with an export duty reduction is likely to be a superior strategy. ^

Development and validation of an instrument to predict online student success using faculty perceptions

Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.

Proton nuclear magnetic resonance investigation of the native and modified active site structure of heme proteins

Hemoproteins are a very important class of enzymes in nature sharing the essentially same prosthetic group, heme, and are good models for exploring the relationship between protein structure and function. Three important hemoproteins, chloroperoxidase (CPO), horseradish peroxidase (HRP), and cytochrome P450cam (P450cam), have been extensively studied as archetypes for the relationship between structure and function. In this study, a series of 1D and 2D NMR experiments were successfully conducted to contribute to the structural studies of these hemoproteins. ^ During the epoxidation of allylbenzene, CPO is converted to an inactive green species with the prosthetic heme modified by addition of the alkene plus an oxygen atom forming a five-membered chelate ring. Complete assignment of the NMR resonances of the modified porphyrin extracted and demetallated from green CPO unambiguously established the structure of this porphyrin as an NIII-alkylated product. A novel substrate binding motif of CPO was proposed from this concluded regiospecific N-alkylation structure. ^ Soybean peroxidase (SBP) is considered as a more stable, more abundant and less expensive substitute of HRP for industrial applications. A NMR study of SBP using 1D and 2D NOE methods successfully established the active site structure of SBP and consequently fills in the blank of the SBP NMR study. All of the hyperfine shifts of the SBP-CN- complex are unambiguously assigned together with most of the prosthetic heme and all proximal His170 resonances identified. The active site structure of SBP revealed by this NMR study is in complete agreement with the recombinant SBP crystal structure and is highly similar to that of the HRP with minor differences. ^ The NMR study of paramagnetic P450cam had been greatly restricted for a long time. A combination of 2D NMR methods was used in this study for P450cam-CN - complexes with and without camphor bound. The results lead to the first unequivocal assignments of all heme hyperfine-shifted signals, together with certain correlated diamagnetic resonances. The observed alternation of the assigned novel proximal cysteine β-CH2 resonances induced by camphor binding indicated a conformational change near the proximal side.^

Molecular characterization of GcC8 alpha, the functional homologue of human C8 alpha in the shark, Ginglymostoma cirratum

The focus of this study is to elucidate the components of the nurse shark (Ginglymostoma cirratum) membrane attack complex (MAC), specifically complement component C8a (GcC8u). Nurse shark C8a gene was cloned, sequenced, and analyzed and Western blot analysis performed to identify components of shark MAC. GcC8a consists of 2341 nucleotides that translate into a 589 amino acid sequence that shares 41.1% and 47.4 % identity with human and xenopus C8a, respectively. GcC8a conserves the MAC modular architecture and cysteine-rich backbone characteristic of complement proteins, including the cysteine residue that forms the C8a-y bond as well as the indel that is unique to C8a. Conservation of MAC protein structure is evident from crossreactivity of antihuman-MAC antibodies with shark serum proteins in Western blots which confirmed the presence of C8 and C9-like proteins in shark serum, however, did not resolve the question of whether C6 and/or C7 like proteins are present in shark.

GIS-integrated mathematical modeling of social phenomena at macro- and micro- levels—a multivariate geographically-weighted regression model for identifying locations vulnerable to hosting terrorist safe-houses: France as case study

Adaptability and invisibility are hallmarks of modern terrorism, and keeping pace with its dynamic nature presents a serious challenge for societies throughout the world. Innovations in computer science have incorporated applied mathematics to develop a wide array of predictive models to support the variety of approaches to counterterrorism. Predictive models are usually designed to forecast the location of attacks. Although this may protect individual structures or locations, it does not reduce the threat—it merely changes the target. While predictive models dedicated to events or social relationships receive much attention where the mathematical and social science communities intersect, models dedicated to terrorist locations such as safe-houses (rather than their targets or training sites) are rare and possibly nonexistent. At the time of this research, there were no publically available models designed to predict locations where violent extremists are likely to reside. This research uses France as a case study to present a complex systems model that incorporates multiple quantitative, qualitative and geospatial variables that differ in terms of scale, weight, and type. Though many of these variables are recognized by specialists in security studies, there remains controversy with respect to their relative importance, degree of interaction, and interdependence. Additionally, some of the variables proposed in this research are not generally recognized as drivers, yet they warrant examination based on their potential role within a complex system. This research tested multiple regression models and determined that geographically-weighted regression analysis produced the most accurate result to accommodate non-stationary coefficient behavior, demonstrating that geographic variables are critical to understanding and predicting the phenomenon of terrorism. This dissertation presents a flexible prototypical model that can be refined and applied to other regions to inform stakeholders such as policy-makers and law enforcement in their efforts to improve national security and enhance quality-of-life.