Living with Terminal Capitalization Rates: A Look at Real Estate Valuation Model Parameter Setting

This paper examines assumptions about future prices used in real estate applications of DCF models. We confirm both the widespread reliance on an ad hoc rule of increasing period-zero capitalization rates by 50 to 100 basis points to obtain terminal capitalization rates and the inability of the rule to project future real estate pricing. To understand how investors form expectations about future prices, we model the spread between the contemporaneously period-zero going-in and terminal capitalization rates and the spread between terminal rates assigned in period zero and going-in rates assigned in period N. Our regression results confirm statistical relationships between the terminal and next holding period going-in capitalization rate spread and the period-zero discount rate, although other economically significant variables are statistically insignificant. Linking terminal capitalization rates by assumption to going-in capitalization rates implies investors view future real estate pricing with myopic expectations. We discuss alternative specifications devoid of such linkage that align more with a rational expectations view of future real estate pricing.

A Parameter Estimation and Identifiability Analysis Methodology Applied to a Street Canyon Air Pollution Model

Mathematical models are increasingly used in environmental science thus increasing the importance of uncertainty and sensitivity analyses. In the present study, an iterative parameter estimation and identifiability analysis methodology is applied to an atmospheric model – the Operational Street Pollution Model (OSPMr). To assess the predictive validity of the model, the data is split into an estimation and a prediction data set using two data splitting approaches and data preparation techniques (clustering and outlier detection) are analysed. The sensitivity analysis, being part of the identifiability analysis, showed that some model parameters were significantly more sensitive than others. The application of the determined optimal parameter values was shown to succesfully equilibrate the model biases among the individual streets and species. It was as well shown that the frequentist approach applied for the uncertainty calculations underestimated the parameter uncertainties. The model parameter uncertainty was qualitatively assessed to be significant, and reduction strategies were identified.

Thermodynamic efficiency of carbon capture and utilisation in anaerobic batch digestion process

Carbon capture and storage (CCS) in the oil and water industries is becoming common and a significant consumer of energy typically requiring 150–450 °C and or several hundred bar pressure [1] particularly in geological deposition. A biological carbon capture and conversion has been considered in conventional anaerobic digestion processes. The process has been utilised in biological mixed culture, where acetoclastic bacteria and hydrogenophilic methanogens play a major key role in the utilisation of carbon dioxide. However, the bio catalytic microorganisms, hydrogenophilic methanogens are reported to be unstable with acetoclastic bacteria. In this work the biochemical thermodynamic efficiency was investigated for the stabilisation of the microbial process in carbon capture and utilisation. The authors observed that a thermodynamic efficiency of biological carbon capture and utilisation (BCCU) had 32% of overall reduction in yield of carbon dioxide with complimentary increase of 30% in yield of methane, while the process was overall endothermic. Total consumption of energy (≈0.33 MJ l−1) was estimated for the carbonate solubility (0.1 mol l−1) in batched BCCU. This has a major influence on microbial composition in the bioreactor. This thermodynamic study is an essential tool to aid the understanding of the interactions between operating parameters and the mixed microbial culture.

Topics in equilibrium and nonequilibrium thermodynamics: computing crystalline free energies and engineering Maxwell’s demon.

This dissertation covers two separate topics in statistical physics. The first part of the dissertation focuses on computational methods of obtaining the free energies (or partition functions) of crystalline solids. We describe a method to compute the Helmholtz free energy of a crystalline solid by direct evaluation of the partition function. In the many-dimensional conformation space of all possible arrangements of N particles inside a periodic box, the energy landscape consists of localized islands corresponding to different solid phases. Calculating the partition function for a specific phase involves integrating over the corresponding island. Introducing a natural order parameter that quantifies the net displacement of particles from lattices sites, we write the partition function in terms of a one-dimensional integral along the order parameter, and evaluate this integral using umbrella sampling. We validate the method by computing free energies of both face-centered cubic (FCC) and hexagonal close-packed (HCP) hard sphere crystals with a precision of $10^{-5}k_BT$ per particle. In developing the numerical method, we find several scaling properties of crystalline solids in the thermodynamic limit. Using these scaling properties, we derive an explicit asymptotic formula for the free energy per particle in the thermodynamic limit. In addition, we describe several changes of coordinates that can be used to separate internal degrees of freedom from external, translational degrees of freedom. The second part of the dissertation focuses on engineering idealized physical devices that work as Maxwell's demon. We describe two autonomous mechanical devices that extract energy from a single heat bath and convert it into work, while writing information onto memory registers. Additionally, both devices can operate as Landauer's eraser, namely they can erase information from a memory register, while energy is dissipated into the heat bath. The phase diagrams and the efficiencies of the two models are solved and analyzed. These two models provide concrete physical illustrations of the thermodynamic consequences of information processing.

Parameter Identification in a Tuberculosis Model for Cameroon

A deterministic model of tuberculosis in Cameroon is designed and analyzed with respect to its transmission dynamics. The model includes lack of access to treatment and weak diagnosis capacity as well as both frequency-and density-dependent transmissions. It is shown that the model is mathematically well-posed and epidemiologically reasonable. Solutions are non-negative and bounded whenever the initial values are non-negative. A sensitivity analysis of model parameters is performed and the most sensitive ones are identified by means of a state-of-the-art Gauss-Newton method. In particular, parameters representing the proportion of individuals having access to medical facilities are seen to have a large impact on the dynamics of the disease. The model predicts that a gradual increase of these parameters could significantly reduce the disease burden on the population within the next 15 years.

Evaluating functions using tail recursion and parameter substitution

This article shows a general way to implement recursive functions calculation by linear tail recursion. It emphasizes the use of tail recursion to perform computations efficiently.

Three dimensional circulation of water with variable wind in the Caspian Sea

This research is based on a numerical model for forecasting the three-dimensional behavior of (sea) water motion due to the effect of a variable wind velocity. The results obtained are then analyzed and compared with observation. This model is based on the equations that overcome the current and distribution of temperature by applying the method of finite difference with assuming Δx, Δy as constant and Δz, variable. The model is based on the momentum equation, continuity equation and thermodynamic energy equation and tension at the surface and middle layers and bottom stress. The horizontal and vertical eddy viscosity and thermal diffusivity coefficients we used in accordance with that of the Bennet on Outario Lake (1977). Considering the Caspian Sea dimension in numerical model the Coriolis parameter used with β effects and the approximation Boussines have been used. For the program controlling some simple experiment with boundary condition similar to that of the Caspian Sea have been done. For modeling the Caspian Sea the grid of the field was done as follows: At horizontal surface grid size is 10×10km extension and at vertical in 10 layers with varying thickness from surface to bed respectively as: 5, 10, 20, 3, 50, 100, 150, 200, 25, 500 and higher. The data of wind as velocity، direction and temperature of water related to 15th September 1995 at 6،12 and 18 o’clock were obtained from synoptic station at the Caspian Sea shore and the research marine of Haji Alief. The information concerning shore wind was measured and by the method of SPM (shore protection manual) was transferred to far shore winds through interpolation and by use of inverse square distance of position distribution of the wind velocity at the Caspian surface field was obtained. The model has been evaluated according to the reports and observations. Through studying the position of the current in different layers، the velocity in the cross section in the northern، southern and the middle layers، will be discussed. The results reveal the presence of the circulation cells in the three above mentioned areas. The circulation with depth is reduced too. The results obtained through the numerical solution of the temperature equation have been compared with the observation. The temperature change in different layers in cross section illustrates the relative accordance of the model mentioned.

An experiment on the parameter uncertainty of hydrological models with different levels of complexity in a climate change context

La possibilité d’estimer l’impact du changement climatique en cours sur le comportement hydrologique des hydro-systèmes est une nécessité pour anticiper les adaptations inévitables et nécessaires que doivent envisager nos sociétés. Dans ce contexte, ce projet doctoral présente une étude sur l’évaluation de la sensibilité des projections hydrologiques futures à : (i) La non-robustesse de l’identification des paramètres des modèles hydrologiques, (ii) l’utilisation de plusieurs jeux de paramètres équifinaux et (iii) l’utilisation de différentes structures de modèles hydrologiques. Pour quantifier l’impact de la première source d’incertitude sur les sorties des modèles, quatre sous-périodes climatiquement contrastées sont tout d’abord identifiées au sein des chroniques observées. Les modèles sont calés sur chacune de ces quatre périodes et les sorties engendrées sont analysées en calage et en validation en suivant les quatre configurations du Different Splitsample Tests (Klemeš, 1986;Wilby, 2005; Seiller et al. (2012);Refsgaard et al. (2014)). Afin d’étudier la seconde source d’incertitude liée à la structure du modèle, l’équifinalité des jeux de paramètres est ensuite prise en compte en considérant pour chaque type de calage les sorties associées à des jeux de paramètres équifinaux. Enfin, pour évaluer la troisième source d’incertitude, cinq modèles hydrologiques de différents niveaux de complexité sont appliqués (GR4J, MORDOR, HSAMI, SWAT et HYDROTEL) sur le bassin versant québécois de la rivière Au Saumon. Les trois sources d’incertitude sont évaluées à la fois dans conditions climatiques observées passées et dans les conditions climatiques futures. Les résultats montrent que, en tenant compte de la méthode d’évaluation suivie dans ce doctorat, l’utilisation de différents niveaux de complexité des modèles hydrologiques est la principale source de variabilité dans les projections de débits dans des conditions climatiques futures. Ceci est suivi par le manque de robustesse de l’identification des paramètres. Les projections hydrologiques générées par un ensemble de jeux de paramètres équifinaux sont proches de celles associées au jeu de paramètres optimal. Par conséquent, plus d’efforts devraient être investis dans l’amélioration de la robustesse des modèles pour les études d’impact sur le changement climatique, notamment en développant les structures des modèles plus appropriés et en proposant des procédures de calage qui augmentent leur robustesse. Ces travaux permettent d’apporter une réponse détaillée sur notre capacité à réaliser un diagnostic des impacts des changements climatiques sur les ressources hydriques du bassin Au Saumon et de proposer une démarche méthodologique originale d’analyse pouvant être directement appliquée ou adaptée à d’autres contextes hydro-climatiques.

New Possibilities for Geophysical Parameter Retrievals Opened by GCOM-W1 AMSR2

A new approach to retrieve sea surface wind speed (SWS) in tropical cyclones (TCs) from the Advanced Microwave Scanning Radiometer 2 (AMSR2) data is presented. Analysis of all six AMSR2 C- and X-band channel measurements over TCs is shown to efficiently help to separate the rain contribution. Corrected measurements at 6.9 and 10.65 GHz are then used to retrieve the SWS. Spatial and temporal collocation of AMSR2 and tropical rain measurement mission (TRMM) microwave instrument (TMI) data is then further used to empirically relate TMI rain rate (RR) product to RR estimates from AMSR2 in hurricanes. SWS estimates are validated with measurements from the stepped frequency microwave radiometer (SFMR). As further tested, more than 100 North Atlantic and North Pacific TCs are analyzed for the 2012–2014 period. Despite few particular cases, most SWS fields are in a very good agreement with TC center data on maximum wind speeds, radii of storm, and hurricane winds. As also compared, very high consistency between AMSR2 and L-band SMOS wind speed estimates are obtained, especially for the super typhoon Haiyan, to prove the high potential of AMSR2 measurements in TCs.

Thermodynamic modeling and microcalorimetry of nanostructured materials for capacitive thermal management of electronics

Transient power dissipation profiles in handheld electronic devices alternate between high and low power states depending on usage. Capacitive thermal management based on phase change materials potentially offers a fan-less thermal management for such transient profiles. However, such capacitive management becomes feasible only if there is a significant enhancement in the enthalpy change per unit volume of the phase change material since existing bulk materials such as paraffin fall short of requirements. In this thesis I propose novel nanostructured thin-film materials that can potentially exhibit significantly enhanced volumetric enthalpy change. Using fundamental thermodynamics of phase transition, calculations regarding the enhancement resulting from superheating in such thin film systems is conducted. Furthermore design of a microfabricated calorimeter to measure such enhancements is explained in detail. This work advances the state-of-art of phase change materials for capacitive cooling of handheld devices.

Soft computing based parameter identification in pavements and geomechanical systems

Accurate estimation of road pavement geometry and layer material properties through the use of proper nondestructive testing and sensor technologies is essential for evaluating pavement’s structural condition and determining options for maintenance and rehabilitation. For these purposes, pavement deflection basins produced by the nondestructive Falling Weight Deflectometer (FWD) test data are commonly used. The nondestructive FWD test drops weights on the pavement to simulate traffic loads and measures the created pavement deflection basins. Backcalculation of pavement geometry and layer properties using FWD deflections is a difficult inverse problem, and the solution with conventional mathematical methods is often challenging due to the ill-posed nature of the problem. In this dissertation, a hybrid algorithm was developed to seek robust and fast solutions to this inverse problem. The algorithm is based on soft computing techniques, mainly Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) as well as the use of numerical analysis techniques to properly simulate the geomechanical system. A widely used pavement layered analysis program ILLI-PAVE was employed in the analyses of flexible pavements of various pavement types; including full-depth asphalt and conventional flexible pavements, were built on either lime stabilized soils or untreated subgrade. Nonlinear properties of the subgrade soil and the base course aggregate as transportation geomaterials were also considered. A computer program, Soft Computing Based System Identifier or SOFTSYS, was developed. In SOFTSYS, ANNs were used as surrogate models to provide faster solutions of the nonlinear finite element program ILLI-PAVE. The deflections obtained from FWD tests in the field were matched with the predictions obtained from the numerical simulations to develop SOFTSYS models. The solution to the inverse problem for multi-layered pavements is computationally hard to achieve and is often not feasible due to field variability and quality of the collected data. The primary difficulty in the analysis arises from the substantial increase in the degree of non-uniqueness of the mapping from the pavement layer parameters to the FWD deflections. The insensitivity of some layer properties lowered SOFTSYS model performances. Still, SOFTSYS models were shown to work effectively with the synthetic data obtained from ILLI-PAVE finite element solutions. In general, SOFTSYS solutions very closely matched the ILLI-PAVE mechanistic pavement analysis results. For SOFTSYS validation, field collected FWD data were successfully used to predict pavement layer thicknesses and layer moduli of in-service flexible pavements. Some of the very promising SOFTSYS results indicated average absolute errors on the order of 2%, 7%, and 4% for the Hot Mix Asphalt (HMA) thickness estimation of full-depth asphalt pavements, full-depth pavements on lime stabilized soils and conventional flexible pavements, respectively. The field validations of SOFTSYS data also produced meaningful results. The thickness data obtained from Ground Penetrating Radar testing matched reasonably well with predictions from SOFTSYS models. The differences observed in the HMA and lime stabilized soil layer thicknesses observed were attributed to deflection data variability from FWD tests. The backcalculated asphalt concrete layer thickness results matched better in the case of full-depth asphalt flexible pavements built on lime stabilized soils compared to conventional flexible pavements. Overall, SOFTSYS was capable of producing reliable thickness estimates despite the variability of field constructed asphalt layer thicknesses.