Decentralized or centralized production : impacts to the environment, industry, and the economy

Since product take-back is mandated in Europe, and has effects for producers worldwide including the U.S., designing efficient forward and reverse supply chain networks is becoming essential for business viability. Centralizing production facilities may reduce costs but perhaps not environmental impacts. Decentralizing a supply chain may reduce transportation environmental impacts but increase capital costs. Facility location strategies of centralization or decentralization are tested for companies with supply chains that both take back and manufacture products. Decentralized and centralized production systems have different effects on the environment, industry and the economy. Decentralized production systems cluster suppliers within the geographical market region that the system serves. Centralized production systems have many suppliers spread out that meet all market demand. The point of this research is to help further the understanding of company decision-makers about impacts to the environment and costs when choosing a decentralized or centralized supply chain organizational strategy. This research explores; what degree of centralization for a supply chain makes the most financial and environmental sense for siting facilities; and which factories are in the best location to handle the financial and environmental impacts of particular processing steps needed for product manufacture. This research considered two examples of facility location for supply chains when products are taken back; the theoretical case involved shoe resoling and a real world case study considered the location of operations for a company that reclaims multiple products for use as material inputs. For the theoretical example a centralized strategy to facility location was optimal: whereas for the case study a decentralized strategy to facility location was best. In conclusion, it is not possible to say that a centralized or decentralized strategy to facility location is in general best for a company that takes back products. Each company’s specific concerns, needs, and supply chain details will determine which degree of centralization creates the optimal strategy for siting their facilities.

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Time-domain modeling of high-frequency electromagnetic wave propagation, overhead wires, and earth

Prediction of radiated fields from transmission lines has not previously been studied from a panoptical power system perspective. The application of BPL technologies to overhead transmission lines would benefit greatly from an ability to simulate real power system environments, not limited to the transmission lines themselves. Presently circuitbased transmission line models used by EMTP-type programs utilize Carson’s formula for a waveguide parallel to an interface. This formula is not valid for calculations at high frequencies, considering effects of earth return currents. This thesis explains the challenges of developing such improved models, explores an approach to combining circuit-based and electromagnetics modeling to predict radiated fields from transmission lines, exposes inadequacies of simulation tools, and suggests methods of extending the validity of transmission line models into very high frequency ranges. Electromagnetics programs are commonly used to study radiated fields from transmission lines. However, an approach is proposed here which is also able to incorporate the components of a power system through the combined use of EMTP-type models. Carson’s formulas address the series impedance of electrical conductors above and parallel to the earth. These equations have been analyzed to show their inherent assumptions and what the implications are. Additionally, the lack of validity into higher frequencies has been demonstrated, showing the need to replace Carson’s formulas for these types of studies. This body of work leads to several conclusions about the relatively new study of BPL. Foremost, there is a gap in modeling capabilities which has been bridged through integration of circuit-based and electromagnetics modeling, allowing more realistic prediction of BPL performance and radiated fields. The proposed approach is limited in its scope of validity due to the formulas used by EMTP-type software. To extend the range of validity, a new set of equations must be identified and implemented in the approach. Several potential methods of implementation have been explored. Though an appropriate set of equations has not yet been identified, further research in this area will benefit from a clear depiction of the next important steps and how they can be accomplished. Prediction of radiated fields from transmission lines has not previously been studied from a panoptical power system perspective. The application of BPL technologies to overhead transmission lines would benefit greatly from an ability to simulate real power system environments, not limited to the transmission lines themselves. Presently circuitbased transmission line models used by EMTP-type programs utilize Carson’s formula for a waveguide parallel to an interface. This formula is not valid for calculations at high frequencies, considering effects of earth return currents. This thesis explains the challenges of developing such improved models, explores an approach to combining circuit-based and electromagnetics modeling to predict radiated fields from transmission lines, exposes inadequacies of simulation tools, and suggests methods of extending the validity of transmission line models into very high frequency ranges. Electromagnetics programs are commonly used to study radiated fields from transmission lines. However, an approach is proposed here which is also able to incorporate the components of a power system through the combined use of EMTP-type models. Carson’s formulas address the series impedance of electrical conductors above and parallel to the earth. These equations have been analyzed to show their inherent assumptions and what the implications are. Additionally, the lack of validity into higher frequencies has been demonstrated, showing the need to replace Carson’s formulas for these types of studies. This body of work leads to several conclusions about the relatively new study of BPL. Foremost, there is a gap in modeling capabilities which has been bridged through integration of circuit-based and electromagnetics modeling, allowing more realistic prediction of BPL performance and radiated fields. The proposed approach is limited in its scope of validity due to the formulas used by EMTP-type software. To extend the range of validity, a new set of equations must be identified and implemented in the approach. Several potential methods of implementation have been explored. Though an appropriate set of equations has not yet been identified, further research in this area will benefit from a clear depiction of the next important steps and how they can be accomplished.

Computational fluids domain reduction to a simplified fluid network

The primary goal of this project is to demonstrate the practical use of data mining algorithms to cluster a solved steady-state computational fluids simulation (CFD) flow domain into a simplified lumped-parameter network. A commercial-quality code, “cfdMine” was created using a volume-weighted k-means clustering that that can accomplish the clustering of a 20 million cell CFD domain on a single CPU in several hours or less. Additionally agglomeration and k-means Mahalanobis were added as optional post-processing steps to further enhance the separation of the clusters. The resultant nodal network is considered a reduced-order model and can be solved transiently at a very minimal computational cost. The reduced order network is then instantiated in the commercial thermal solver MuSES to perform transient conjugate heat transfer using convection predicted using a lumped network (based on steady-state CFD). When inserting the lumped nodal network into a MuSES model, the potential for developing a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track temperatures near specific objects (such as equipment in vehicles).

PROPERTIES AND STRUCTURES OF Li-N BASED HYDROGEN STORAGE MATERIALS

Traditional transportation fuel, petroleum, is limited and nonrenewable, and it also causes pollutions. Hydrogen is considered one of the best alternative fuels for transportation. The key issue for using hydrogen as fuel for transportation is hydrogen storage. Lithium nitride (Li3N) is an important material which can be used for hydrogen storage. The decompositions of lithium amide (LiNH2) and lithium imide (Li2NH) are important steps for hydrogen storage in Li3N. The effect of anions (e.g. Cl-) on the decomposition of LiNH2 has never been studied. Li3N can react with LiBr to form lithium nitride bromide Li13N4Br which has been proposed as solid electrolyte for batteries. The decompositions of LiNH2 and Li2NH with and without promoter were investigated by using temperature programmed decomposition (TPD) and X-ray diffraction (XRD) techniques. It was found that the decomposition of LiNH2 produced Li2NH and NH3 via two steps: LiNH2 into a stable intermediate species (Li1.5NH1.5) and then into Li2NH. The decomposition of Li2NH produced Li, N2 and H2 via two steps: Li2NH into an intermediate species --- Li4NH and then into Li. The kinetic analysis of Li2NH decomposition showed that the activation energies are 533.6 kJ/mol for the first step and 754.2 kJ/mol for the second step. Furthermore, XRD demonstrated that the Li4NH, which was generated in the decomposition of Li2NH, formed a solid solution with Li2NH. In the solid solution, Li4NH possesses a similar cubic structure as Li2NH. The lattice parameter of the cubic Li4NH is 0.5033nm. The decompositions of LiNH2 and Li2NH can be promoted by chloride ion (Cl-). The introduction of Cl- into LiNH2 resulted in the generation of a new NH3 peak at low temperature of 250 °C besides the original NH3 peak at 330 °C in TPD profiles. Furthermore, Cl- can decrease the decomposition temperature of Li2NH by about 110 °C. The degradation of Li3N was systematically investigated with techniques of XRD, Fourier transform infrared (FT-IR) spectroscopy, and UV-visible spectroscopy. It was found that O2 could not affect Li3N at room temperature. However, H2O in air can cause the degradation of Li3N due to the reaction between H2O and Li3N to LiOH. The produced LiOH can further react with CO2 in air to Li2CO3 at room temperature. Furthermore, it was revealed that Alfa-Li3N is more stable in air than Beta-Li3N. The chemical stability of Li13N4Br in air has been investigated by XRD, TPD-MS, and UV-vis absorption as a function of time. The aging process finally leads to the degradation of the Li13N4Br into Li2CO3, lithium bromite (LiBrO2) and the release of gaseous NH3. The reaction order n = 2.43 is the best fitting for the Li13N4Br degradation in air reaction. Li13N4Br energy gap was calculated to be 2.61 eV.